From 5fb33adf13bd8c2196add44a54309e031a604047 Mon Sep 17 00:00:00 2001 From: Fe-r-oz Date: Sat, 14 Jun 2025 23:25:56 +0500 Subject: [PATCH 1/2] =?UTF-8?q?=F0=9F=93=9D=20polish=20documentation,=20an?= =?UTF-8?q?d=20add=20makefile=20for=20automatic=20formatting,=20tests,=20d?= =?UTF-8?q?ocs=20checking=20etc.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Makefile | 28 + benchmarks/iterators_bench.jl | 26 +- benchmarks/weight_dist_bench.jl | 95 +- docs/make.jl | 106 +- docs/src/Tutorials/message_passing_tests.jl | 482 ++++-- docs/src/references.bib | 86 +- ext/JLD2Ext/JLD2Ext.jl | 7 +- ext/JLD2Ext/Quantum/misc_known_codes.jl | 20 +- ext/JuMPExt/JuMPExt.jl | 8 +- ext/JuMPExt/LDPC/analysis.jl | 106 +- ext/JuMPExt/LDPC/decoders.jl | 43 +- ext/MakieExt/Classical/Tanner.jl | 24 +- ext/MakieExt/Classical/weight_dist.jl | 6 +- ext/MakieExt/LDPC/analysis.jl | 10 +- ext/MakieExt/LDPC/codes.jl | 48 +- ext/MakieExt/LDPC/cycles.jl | 82 +- ext/MakieExt/MakieExt.jl | 27 +- ext/MakieExt/Quantum/weight_dist.jl | 56 +- src/Classical/GRS_alternate.jl | 178 +- src/Classical/Gabidulin.jl | 47 +- src/Classical/Goppa.jl | 57 +- src/Classical/MatrixProductCode.jl | 45 +- src/Classical/McEliece.jl | 186 +- src/Classical/ReedMuller.jl | 83 +- src/Classical/Tanner.jl | 117 +- src/Classical/TwistedReedSolomon.jl | 106 +- src/Classical/concatenation.jl | 125 +- src/Classical/cyclic_code.jl | 397 ++++- src/Classical/cyclotomic.jl | 47 +- src/Classical/linear_code.jl | 390 +++-- src/Classical/misc_known_codes.jl | 162 +- src/Classical/new_codes_from_old.jl | 412 +++-- src/Classical/quasi-cyclic_code.jl | 153 +- src/Classical/types.jl | 132 +- src/Classical/weight_dist.jl | 869 +++++++--- src/Classical/weight_reduction.jl | 107 +- src/CodingTheory.jl | 870 +++++++--- src/Convolutional/convolutional_code.jl | 111 +- src/Convolutional/types.jl | 18 +- src/LDPC/GBP.jl | 76 +- src/LDPC/LP_decoders.jl | 2 +- src/LDPC/MP_decoders.jl | 1519 ++++++++++++----- src/LDPC/algorithms.jl | 5 +- src/LDPC/analysis.jl | 84 +- src/LDPC/channels.jl | 15 +- src/LDPC/codes.jl | 124 +- src/LDPC/cycles.jl | 302 ++-- src/LDPC/decoders.jl | 316 +++- src/LDPC/simulations.jl | 1059 ++++++++++-- src/LDPC/types.jl | 20 +- src/Project.toml | 1 + src/Quantum/GeneralizedToricCode.jl | 32 +- src/Quantum/decoders/OTF.jl | 206 ++- src/Quantum/graph_state.jl | 20 +- src/Quantum/homological_measurements.jl | 176 +- src/Quantum/misc_known_codes.jl | 1014 +++++++---- src/Quantum/product_codes.jl | 567 ++++-- src/Quantum/simulation.jl | 804 ++++++--- src/Quantum/stabilizer_code.jl | 823 +++++++-- src/Quantum/subsystem_code.jl | 1344 ++++++++++----- src/Quantum/types.jl | 579 ++++--- src/Quantum/weight_dist.jl | 681 ++++++-- src/Quantum/weight_reduction.jl | 603 +++++-- src/chain_complex.jl | 42 +- src/iterators.jl | 110 +- src/tilings.jl | 56 +- src/trellis.jl | 822 +++++---- src/utils.jl | 709 +++++--- test/Classical/GRS_alternate_test.jl | 16 +- test/Classical/Goppa_test.jl | 10 +- test/Classical/ReedMuller_test.jl | 106 +- test/Classical/TwistedReedSolomon_test.jl | 4 +- test/Classical/concatenation_test.jl | 100 +- test/Classical/cyclic_code_test.jl | 14 +- test/Classical/cyclotomic_test.jl | 7 +- test/Classical/linear_code_test.jl | 61 +- test/Classical/misc_known_codes_test.jl | 52 +- test/Classical/quasi-cyclic_code_test.jl | 33 +- test/LDPC/MP_decoders_test.jl | 2 +- test/LDPC/codes_test.jl | 16 +- test/Quantum/GeneralizedToricCode_test.jl | 52 +- test/Quantum/decoders/OFT_test.jl | 50 +- test/Quantum/homological_measurements_test.jl | 4 +- test/Quantum/misc_known_codes_test.jl | 2 +- test/Quantum/product_codes_test.jl | 198 ++- test/Quantum/stabilizer_code_test.jl | 30 +- test/Quantum/subsystem_code_test.jl | 17 +- test/chain_complex_test.jl | 182 +- test/iterators_test.jl | 32 +- test/runtests.jl | 4 +- test/testcases.jl | 35 +- test/utils_test.jl | 105 +- 92 files changed, 13384 insertions(+), 5731 deletions(-) create mode 100644 Makefile create mode 100644 src/Project.toml diff --git a/Makefile b/Makefile new file mode 100644 index 00000000..c1a24cb1 --- /dev/null +++ b/Makefile @@ -0,0 +1,28 @@ +JULIA:=julia + +default: help + +setup: + ${JULIA} -e 'import Pkg; Pkg.add(["JuliaFormatter"])' + +format: + ${JULIA} -e 'using JuliaFormatter; format(".")' + +test: + ${JULIA} --project -e 'using Pkg; Pkg.resolve(); Pkg.test()' + +docs: + ${JULIA} --project=docs -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()' + ${JULIA} --project=docs docs/make.jl + +all: setup format test docs + +help: + @echo "The following make commands are available:" + @echo " - make setup: install the dependencies for make command" + @echo " - make format: format codes with JuliaFormatter" + @echo " - make test: run the tests" + @echo " - make docs: instantiate and build the documentation" + @echo " - make all: run every commands in the above order" + +.PHONY: default setup format test doc all help diff --git a/benchmarks/iterators_bench.jl b/benchmarks/iterators_bench.jl index 39bab499..86e7f158 100644 --- a/benchmarks/iterators_bench.jl +++ b/benchmarks/iterators_bench.jl @@ -4,18 +4,18 @@ using LinearAlgebra using BenchmarkTools function visit_all_subsets(mutate, g_len, v_weight, subset) - if subset - gi=CodingTheory.SubsetGrayCode(g_len, v_weight) - else - gi=CodingTheory.GrayCode(g_len, v_weight; mutate = mutate) - end - for subset in gi - # BenchmarkTools can elide simple computations so we need to do some nontrivial calculation here. - # In any realistic situation we need to look at least look at all entries of the vector. - # Ill model the task of looking at the entries using the 'all' function - Base.all(i->(i==0), subset) - end - return + if subset + gi=CodingTheory.SubsetGrayCode(g_len, v_weight) + else + gi=CodingTheory.GrayCode(g_len, v_weight; mutate = mutate) + end + for subset in gi + # BenchmarkTools can elide simple computations so we need to do some nontrivial calculation here. + # In any realistic situation we need to look at least look at all entries of the vector. + # Ill model the task of looking at the entries using the 'all' function + Base.all(i->(i==0), subset) + end + return end #= @@ -47,4 +47,4 @@ BenchmarkTools.Trial: 65 samples with 1 evaluation. 51.2 ms Histogram: frequency by time 89.3 ms < Memory estimate: 238.05 MiB, allocs estimate: 5200308. -=# \ No newline at end of file +=# diff --git a/benchmarks/weight_dist_bench.jl b/benchmarks/weight_dist_bench.jl index a10f8c7b..b4153b09 100644 --- a/benchmarks/weight_dist_bench.jl +++ b/benchmarks/weight_dist_bench.jl @@ -9,55 +9,70 @@ CodingTheory.Random.seed!(0) function white_n70_k35(use_new, terse_description) F = Oscar.Nemo.Native.GF(2) - mat = matrix(F, [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 1 0 1 1 1 0 1 0 1 1 1 1 0 1 1 0 1 1 0 0 1 0 0 1 1 0 1; - 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 1 1 1 0 1 1 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1 0 0 0 0 1 0 1 0 1 1 0 1 0 1 0 0 1 1 1 0 0 1 0 1 1 0 0 0 0 0 1 0 0 1 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 1 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 1 1 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 0 0 1 1 1 0 1 0 1 1 1 0 1 0 1 0 1 0 0 1 1 0 0 0 0 0 1 0 1 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 1 1 0 1 0 1 0 0 1 1 1 0 0 1 0 1 1 0 0 0 0 0 1 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 1 1 0 1 0 1 0 0 1 1 1 0 0 1 0 1 1 0 0 0 0 0 1; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 1 1 1 0 0 0 1 1 1 1 0 0 0 1 0 0 0 1 0 0 0 1 1; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 1 1 1 0 0 1 1 1 1 1 1 0 0 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 1 0 1 0 0 0 1 1 1 0 1 0 1 0 0 1 1 0 1 0 0 0 1 1 0 1 1 0 0 1 0 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 1 1 1 1 0 0 0 1 1 0 0 0 1 0 1 0 1 1 0 1 0 0 0 1 0 1 1 1 1 0 0 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 1 0 0 0 0 1 1 1 0 1 1 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 1 1 1 1 0 0; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 1 1 1 0 1 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 1 1 1 0 0 0 1 0 0 1 1; + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 1 0 0 0 0 1 1 1 + ], + ) num_thrds = Threads.nthreads() println("Benchmarking with $num_thrds threads.") if use_new function_description = "_minimum_distance_BZ(codeN70K35,:Brouwer;false)" - terse_description ? println(function_description) : println(benchmark_description(function_description)) - return @benchmark CodingTheory._minimum_distance_BZ(codeN70K35, info_set_alg = :Brouwer; verbose = false) setup = (codeN70K35=LinearCode($mat, false, false)) + terse_description ? println(function_description) : + println(benchmark_description(function_description)) + return @benchmark CodingTheory._minimum_distance_BZ( + codeN70K35, + info_set_alg = :Brouwer; + verbose = false, + ) setup = (codeN70K35=LinearCode($mat, false, false)) else function_description = "_minimum_distance_enumeration_with_matrix_multiply(codeN70K35,:Brouwer;false)" - terse_description ? println(function_description) : println(benchmark_description(function_description)) - return @benchmark CodingTheory._minimum_distance_enumeration_with_matrix_multiply(codeN70K35, info_set_alg = :Brouwer; verbose = false) setup = (codeN70K35=LinearCode($mat, false, false)) + terse_description ? println(function_description) : + println(benchmark_description(function_description)) + return @benchmark CodingTheory._minimum_distance_enumeration_with_matrix_multiply( + codeN70K35, + info_set_alg = :Brouwer; + verbose = false, + ) setup = (codeN70K35=LinearCode($mat, false, false)) end end use_new=false t = white_n70_k35(use_new, true) -t \ No newline at end of file +t diff --git a/docs/make.jl b/docs/make.jl index ede7741e..551ea029 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -3,62 +3,58 @@ using DocumenterCitations, Documenter, CodingTheory bib = CitationBibliography(joinpath(@__DIR__, "src", "references.bib"); style = :numeric) Documenter.makedocs(; - plugins=[bib], - clean = true, - doctest = false, - modules = Module[CodingTheory], - repo = "", - highlightsig = true, - sitename = "CodingTheory.jl", - expandfirst = [], - warnonly = [:missing_docs], - pages = ["Introduction" => "index.md", - "Tutorials" => [ - "Tutorials/Linear Codes.md", - "Tutorials/Cyclic Codes.md", - "Tutorials/Quantum Codes.md", - "Tutorials/Weight Reduction.md" - ], - "Examples" => [ - "Examples/The Vardy-Be’ery Decomposition.md", - "Examples/Quantum Reed-Muller Codes.md" - ], - "Classical" => [ - "Classical/linear_code.md", - "Classical/concatenation.md", - "Classical/cyclic_code.md", - "Classical/quasi-cyclic_code.md", - "Classical/GeneralizedReedSolomon.md", - "Classical/ReedMuller.md", - "Classical/new_codes_from_old.md", - "Classical/product_codes.md", - "Classical/misc_known_codes.md" - ], - "LDPC" => [ - "LDPC/codes.md", - "LDPC/Tanner_codes.md", - "LDPC/analysis.md", - "LDPC/channels.md", - "LDPC/decoders.md" - ], - "Quantum" => [ - "Quantum/quantum_code.md", - "Quantum/product_codes.md", - "Quantum/misc_known_codes.md", - "Quantum/weight_reduction.md" - ], - "Misc" => [ - "tilings.md", - "trellis.md", - "utils.md", - "weight_dist.md" - ], - "References" => "references.md", - "Index" => "theindex.md" - # "Developer Documentation" => [ + plugins = [bib], + clean = true, + doctest = false, + modules = Module[CodingTheory], + repo = "", + highlightsig = true, + sitename = "CodingTheory.jl", + expandfirst = [], + warnonly = [:missing_docs], + pages = [ + "Introduction" => "index.md", + "Tutorials" => [ + "Tutorials/Linear Codes.md", + "Tutorials/Cyclic Codes.md", + "Tutorials/Quantum Codes.md", + "Tutorials/Weight Reduction.md", + ], + "Examples" => [ + "Examples/The Vardy-Be’ery Decomposition.md", + "Examples/Quantum Reed-Muller Codes.md", + ], + "Classical" => [ + "Classical/linear_code.md", + "Classical/concatenation.md", + "Classical/cyclic_code.md", + "Classical/quasi-cyclic_code.md", + "Classical/GeneralizedReedSolomon.md", + "Classical/ReedMuller.md", + "Classical/new_codes_from_old.md", + "Classical/product_codes.md", + "Classical/misc_known_codes.md", + ], + "LDPC" => [ + "LDPC/codes.md", + "LDPC/Tanner_codes.md", + "LDPC/analysis.md", + "LDPC/channels.md", + "LDPC/decoders.md", + ], + "Quantum" => [ + "Quantum/quantum_code.md", + "Quantum/product_codes.md", + "Quantum/misc_known_codes.md", + "Quantum/weight_reduction.md", + ], + "Misc" => ["tilings.md", "trellis.md", "utils.md", "weight_dist.md"], + "References" => "references.md", + "Index" => "theindex.md", + # "Developer Documentation" => [ - # ], - ] + # ], + ], ) deploydocs(repo = "github.com/esabo/CodingTheory.git", devbranch = "dev") diff --git a/docs/src/Tutorials/message_passing_tests.jl b/docs/src/Tutorials/message_passing_tests.jl index ae9be02e..1a803a59 100644 --- a/docs/src/Tutorials/message_passing_tests.jl +++ b/docs/src/Tutorials/message_passing_tests.jl @@ -17,23 +17,25 @@ function CSS_decoder_simple(S::AbstractStabilizerCode) num_threads = Threads.nthreads() runs_per_thread = cld(num_runs, num_threads) new_num_runs = runs_per_thread * num_threads - println("Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs") + println( + "Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs", + ) # preallocate places to store results FER = zeros(Float64, len_noise) local_log_failure_counts = zeros(Int, num_threads) local_conv_failure_counts = zeros(Int, num_threads) - X_local_iters = [zeros(Int, max_iter) for _ in 1:num_threads] - Z_local_iters = [zeros(Int, max_iter) for _ in 1:num_threads] + X_local_iters = [zeros(Int, max_iter) for _ = 1:num_threads] + Z_local_iters = [zeros(Int, max_iter) for _ = 1:num_threads] - for i in 1:len_noise + for i = 1:len_noise p = noise[i] println("Starting p = $p") # setup noise model chn = Dict(0 => 1 - p, 1 => p / 3, 2 => p / 3, 3 => p / 3) Pauli_types = Int[0, 1, 2, 3] - Pauli_weights = Float64[1 - p, p / 3, p / 3, p / 3] + Pauli_weights = Float64[1-p, p/3, p/3, p/3] PrII::Float64 = Pauli_weights[1] / (Pauli_weights[1] + Pauli_weights[4]) PrIX::Float64 = Pauli_weights[2] / (Pauli_weights[1] + Pauli_weights[2]) PrZI::Float64 = Pauli_weights[4] / (Pauli_weights[1] + Pauli_weights[4]) @@ -43,13 +45,34 @@ function CSS_decoder_simple(S::AbstractStabilizerCode) Pauli_weights_W = Weights(Pauli_weights) Pauli_op::Vector{Int} = [0] - Threads.@threads for th in 1:num_threads - X_stabs, Z_stabs, logs, X_err, Z_err, X_var_adj_list, - X_check_adj_list, Z_var_adj_list, Z_check_adj_list, X_chn_inits, - Z_chn_inits, X_check_to_var_messages, X_var_to_check_messages, - Z_check_to_var_messages, Z_var_to_check_messages, current_bits, - totals, X_syn, Z_syn = CodingTheory._message_passing_init_CSS(S, chn, max_iter, - missing, missing, schedule, erasures) + Threads.@threads for th = 1:num_threads + X_stabs, + Z_stabs, + logs, + X_err, + Z_err, + X_var_adj_list, + X_check_adj_list, + Z_var_adj_list, + Z_check_adj_list, + X_chn_inits, + Z_chn_inits, + X_check_to_var_messages, + X_var_to_check_messages, + Z_check_to_var_messages, + Z_var_to_check_messages, + current_bits, + totals, + X_syn, + Z_syn = CodingTheory._message_passing_init_CSS( + S, + chn, + max_iter, + missing, + missing, + schedule, + erasures, + ) nr_X = size(X_stabs, 1) nr_Z = size(Z_stabs, 1) @@ -58,9 +81,9 @@ function CSS_decoder_simple(S::AbstractStabilizerCode) Z_meas_syn = zeros(Int, nr_Z) skip = false - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread # sample - @inbounds @simd for j in 1:n + @inbounds @simd for j = 1:n sample!(Pauli_types, Pauli_weights_W, Pauli_op) # println(Pauli_op) if Pauli_op[1] == 0 @@ -85,17 +108,30 @@ function CSS_decoder_simple(S::AbstractStabilizerCode) # bypass = false # X syndrome LinearAlgebra.mul!(X_meas_syn, X_stabs, Z_err) - @inbounds @simd for i in 1:nr_X + @inbounds @simd for i = 1:nr_X X_meas_syn[i] %= 2 end # decode X - X_flag, X_out, X_iter = CodingTheory._message_passing_layered(X_stabs, X_meas_syn, - X_chn_inits, CodingTheory._SP_check_node_message_box_plus, X_var_adj_list, - X_check_adj_list, max_iter, schedule, current_bits, totals, - X_syn, X_check_to_var_messages, X_var_to_check_messages, 0.0, X_layers) + X_flag, X_out, X_iter = CodingTheory._message_passing_layered( + X_stabs, + X_meas_syn, + X_chn_inits, + CodingTheory._SP_check_node_message_box_plus, + X_var_adj_list, + X_check_adj_list, + max_iter, + schedule, + current_bits, + totals, + X_syn, + X_check_to_var_messages, + X_var_to_check_messages, + 0.0, + X_layers, + ) + - if !X_flag # did not converge skip = true @@ -104,7 +140,7 @@ function CSS_decoder_simple(S::AbstractStabilizerCode) # shouldn't matter if I mod 2 this now or later # a non-allocating version of Z_err += X_out # Z_err += X_out - @inbounds @simd for i in 1:n + @inbounds @simd for i = 1:n Z_err[i] = Z_err[i] + X_out[i] end X_local_iters[th][X_iter] += 1 @@ -112,51 +148,66 @@ function CSS_decoder_simple(S::AbstractStabilizerCode) # skip Z if X failed because the result will not end up in the codespace # if !skip - # Z syndrome - # this allocates ~400 MB for 15k samples - LinearAlgebra.mul!(Z_meas_syn, Z_stabs, X_err) - @inbounds @simd for i in 1:nr_Z - Z_meas_syn[i] %= 2 - end - - # Bayes' Theorem: update priors on Z given the results from X - # always log(Pr(no error) / Pr(error)) so now - # log((Pr(I | I) + Pr(I | X)) / (Pr(Z | I) + Pr(Z | X))) etc - - # this single loop allocates 0.6 GB for 15k samples - @inbounds @simd for i in 1:n - if X_out[i] == 0 - Z_chn_inits[i] = without_X_err - else - Z_chn_inits[i] = with_X_err - end - end - - # if bypass - Z_flag, Z_out, Z_iter = CodingTheory._message_passing_layered(Z_stabs, Z_meas_syn, - Z_chn_inits, CodingTheory._SP_check_node_message_box_plus, Z_var_adj_list, - Z_check_adj_list, max_iter, schedule, current_bits, totals, - Z_syn, Z_check_to_var_messages, Z_var_to_check_messages, 0.0, Z_layers) - - if !Z_flag - # did not converge - skip = true + # Z syndrome + # this allocates ~400 MB for 15k samples + LinearAlgebra.mul!(Z_meas_syn, Z_stabs, X_err) + @inbounds @simd for i = 1:nr_Z + Z_meas_syn[i] %= 2 + end + + # Bayes' Theorem: update priors on Z given the results from X + # always log(Pr(no error) / Pr(error)) so now + # log((Pr(I | I) + Pr(I | X)) / (Pr(Z | I) + Pr(Z | X))) etc + + # this single loop allocates 0.6 GB for 15k samples + @inbounds @simd for i = 1:n + if X_out[i] == 0 + Z_chn_inits[i] = without_X_err else - # did converge - # shouldn't matter if I mod 2 this now or later - # a non-allocating version of X_err += Z_out - @inbounds @simd for i in 1:n - X_err[i] = X_err[i] + Z_out[i] - end - Z_local_iters[th][Z_iter] += 1 + Z_chn_inits[i] = with_X_err + end + end + + # if bypass + Z_flag, Z_out, Z_iter = CodingTheory._message_passing_layered( + Z_stabs, + Z_meas_syn, + Z_chn_inits, + CodingTheory._SP_check_node_message_box_plus, + Z_var_adj_list, + Z_check_adj_list, + max_iter, + schedule, + current_bits, + totals, + Z_syn, + Z_check_to_var_messages, + Z_var_to_check_messages, + 0.0, + Z_layers, + ) + + if !Z_flag + # did not converge + skip = true + else + # did converge + # shouldn't matter if I mod 2 this now or later + # a non-allocating version of X_err += Z_out + @inbounds @simd for i = 1:n + X_err[i] = X_err[i] + Z_out[i] end + Z_local_iters[th][Z_iter] += 1 + end # end if !skip # converged, check for logical errors - @inbounds for j in 1:nr_logs - iseven(dot(view(logs, j, 1:n), Z_err) - dot(view(logs, j, n + - 1:2 * n), X_err)) || (local_log_failure_counts[th] += 1; break;) + @inbounds for j = 1:nr_logs + iseven( + dot(view(logs, j, 1:n), Z_err) - + dot(view(logs, j, (n+1):(2*n)), X_err), + ) || (local_log_failure_counts[th] += 1; break;) end else # did not converge @@ -173,7 +224,8 @@ function CSS_decoder_simple(S::AbstractStabilizerCode) end println("logical failures: $local_log_failure_counts") println("convergence failures: $local_conv_failure_counts") - @inbounds FER[i] = (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / new_num_runs + @inbounds FER[i] = + (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / new_num_runs println("FER = $(FER[i])") println("Finished p = $p") @@ -182,8 +234,8 @@ function CSS_decoder_simple(S::AbstractStabilizerCode) end # reduce iteration counts - @inbounds for i in 2:num_threads - @simd for j in 1:max_iter + @inbounds for i = 2:num_threads + @simd for j = 1:max_iter X_local_iters[1][j] += X_local_iters[i][j] Z_local_iters[1][j] += Z_local_iters[i][j] end @@ -259,7 +311,7 @@ end # Metachecks -function _make_single_shot_Tanner_graph(H::T, M::T) where T <: CodingTheory.CTMatrixTypes +function _make_single_shot_Tanner_graph(H::T, M::T) where {T<:CodingTheory.CTMatrixTypes} # internal function, so skip checks on correctness F = base_ring(H) Fone = F(1) @@ -267,7 +319,7 @@ function _make_single_shot_Tanner_graph(H::T, M::T) where T <: CodingTheory.CTMa nc_M = ncols(M) single_shot_matrix = CodingTheory.direct_sum(H, M) row = 1 - @inbounds @simd for c in nc_H + 1:nc_H + nc_M + @inbounds @simd for c = (nc_H+1):(nc_H+nc_M) single_shot_matrix[row, c] = Fone row += 1 end @@ -275,20 +327,26 @@ function _make_single_shot_Tanner_graph(H::T, M::T) where T <: CodingTheory.CTMa return single_shot_matrix end -function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T <: CodingTheory.CTMatrixTypes +function CSS_metachecks( + X_stabs::T, + X_logs::T, + X_meta::T, + X_meta_L::T, +) where {T<:CodingTheory.CTMatrixTypes} nr, n = size(X_stabs) n == ncols(X_logs) || throw(ArgumentError("Logs are the wrong size")) ncols(X_meta) == nr || throw(ArgumentError("Metacheck is the wrong size")) - iszero(X_meta * X_stabs) || throw(ArgumentError("Either metachecks or stabilizers wrong")) + iszero(X_meta * X_stabs) || + throw(ArgumentError("Either metachecks or stabilizers wrong")) X_ss = _make_single_shot_Tanner_graph(X_stabs, X_meta) # noise details p_meas = 1e-3 - chn_meas = MPNoiseModel(:BSC, p_meas) - chn_inits_meta_in = Float64[log((1 - p_meas) / p_meas) for _ in 1:nr] - syn_err_weights = Weights(Float64[1 - p_meas, p_meas]) + chn_meas = MPNoiseModel(:BSC, p_meas) + chn_inits_meta_in = Float64[log((1 - p_meas) / p_meas) for _ = 1:nr] + syn_err_weights = Weights(Float64[1-p_meas, p_meas]) # noise = 10 .^(-3:.25:-1.3) - noise = 10 .^(-1.5:.1:-1) + noise = 10 .^ (-1.5:0.1:-1) len_noise = length(noise) # BP details @@ -313,46 +371,108 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < num_threads = Threads.nthreads() runs_per_thread = cld(num_runs, num_threads) new_num_runs = runs_per_thread * num_threads - println("Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs") + println( + "Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs", + ) # preallocate places to store results FER_scheme_1 = zeros(Float64, len_noise) FER_scheme_2 = zeros(Float64, len_noise) - local_log_failure_counts_scheme_1 = [zeros(Int, nr_logs) for _ in 1:num_threads] - local_log_failure_counts_scheme_2 = [zeros(Int, nr_logs) for _ in 1:num_threads] + local_log_failure_counts_scheme_1 = [zeros(Int, nr_logs) for _ = 1:num_threads] + local_log_failure_counts_scheme_2 = [zeros(Int, nr_logs) for _ = 1:num_threads] local_failure_counts_scheme_1 = zeros(Int, num_threads) local_failure_counts_scheme_2 = zeros(Int, num_threads) - for i in 1:len_noise + for i = 1:len_noise p = noise[i] println("Starting p = $p") # setup noise model chn = MPNoiseModel(:BSC, p) - Pauli_weights = Weights(Float64[1 - p, p]) - chn_inits_stabs_in = Float64[log((1 - p) / p) for _ in 1:n] + Pauli_weights = Weights(Float64[1-p, p]) + chn_inits_stabs_in = Float64[log((1 - p) / p) for _ = 1:n] chn_inits_ss_in = Float64[chn_inits_stabs_in; chn_inits_meta_in] - Threads.@threads for th in 1:num_threads + Threads.@threads for th = 1:num_threads # Tanner graph for the stabilizers - X_stabs_Int, _, var_adj_list_stabs, check_adj_list_stabs, chn_inits_stabs, - check_to_var_messages_stabs, var_to_check_messages_stabs, current_bits_stabs, - totals_stabs, syn_stabs = CodingTheory._message_passing_init(X_stabs, v, chn, max_iter, :SP, - chn_inits_stabs_in, schedule, erasures) + X_stabs_Int, + _, + var_adj_list_stabs, + check_adj_list_stabs, + chn_inits_stabs, + check_to_var_messages_stabs, + var_to_check_messages_stabs, + current_bits_stabs, + totals_stabs, + syn_stabs = CodingTheory._message_passing_init( + X_stabs, + v, + chn, + max_iter, + :SP, + chn_inits_stabs_in, + schedule, + erasures, + ) # Tanner graph for the metachecks - X_meta_Int, _, var_adj_list_meta, check_adj_list_meta, chn_inits_meta, - check_to_var_messages_meta, var_to_check_messages_meta, current_bits_meta, - totals_meta, syn_meta = CodingTheory._message_passing_init(X_meta, v2, chn_meas, max_iter, :SP, - chn_inits_meta_in, schedule, erasures) + X_meta_Int, + _, + var_adj_list_meta, + check_adj_list_meta, + chn_inits_meta, + check_to_var_messages_meta, + var_to_check_messages_meta, + current_bits_meta, + totals_meta, + syn_meta = CodingTheory._message_passing_init( + X_meta, + v2, + chn_meas, + max_iter, + :SP, + chn_inits_meta_in, + schedule, + erasures, + ) # Tanner graph for the second metacheck matrix - X_meta_L_Int, _, var_adj_list_meta_L, check_adj_list_meta_L, chn_inits_meta_L, - check_to_var_messages_meta_L, var_to_check_messages_meta_L, current_bits_meta_L, - totals_meta_L, syn_meta_L = CodingTheory._message_passing_init(X_meta_L, v2, chn_meas, max_iter, :SP, - chn_inits_meta_in, schedule, erasures) + X_meta_L_Int, + _, + var_adj_list_meta_L, + check_adj_list_meta_L, + chn_inits_meta_L, + check_to_var_messages_meta_L, + var_to_check_messages_meta_L, + current_bits_meta_L, + totals_meta_L, + syn_meta_L = CodingTheory._message_passing_init( + X_meta_L, + v2, + chn_meas, + max_iter, + :SP, + chn_inits_meta_in, + schedule, + erasures, + ) # Tanner graph for scheme 2 - X_ss_Int, _, var_adj_list_ss, check_adj_list_ss, chn_inits_ss, check_to_var_messages_ss, - var_to_check_messages_ss, current_bits_ss, totals_ss, syn_ss = - CodingTheory._message_passing_init(X_ss, v3, chn, max_iter, :SP, chn_inits_ss_in, schedule, - erasures) + X_ss_Int, + _, + var_adj_list_ss, + check_adj_list_ss, + chn_inits_ss, + check_to_var_messages_ss, + var_to_check_messages_ss, + current_bits_ss, + totals_ss, + syn_ss = CodingTheory._message_passing_init( + X_ss, + v3, + chn, + max_iter, + :SP, + chn_inits_ss_in, + schedule, + erasures, + ) X_meas_syn_scheme_1 = zeros(Int, nr) X_meas_syn_scheme_2 = zeros(Int, nr) X_syn_err = zeros(Int, nr) @@ -365,15 +485,15 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < m2 = zeros(Int, size(X_meta_L_Int, 1)) logs_check = zeros(Int, nr_logs, 1) - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread X_flag_stabs = false X_flag_ss = false X_out_stabs = Int[0] X_out_ss = Int[0] - for ss_iter in 1:single_shot_rounds + for ss_iter = 1:single_shot_rounds # sample sample!(Pauli_types, Pauli_weights, Z_err) - @inbounds @simd for j in i:n + @inbounds @simd for j = i:n state_scheme_1[j] += Z_err[j] state_scheme_2[j] += Z_err[j] end @@ -381,7 +501,7 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < # syndrome LinearAlgebra.mul!(X_meas_syn_scheme_1, X_stabs_Int, state_scheme_1) LinearAlgebra.mul!(X_meas_syn_scheme_2, X_stabs_Int, state_scheme_2) - @inbounds @simd for j in 1:nr + @inbounds @simd for j = 1:nr X_meas_syn_scheme_1[j] %= 2 X_meas_syn_scheme_2[j] %= 2 end @@ -390,9 +510,11 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < if ss_iter != single_shot_rounds # add measurement errors sample!(Pauli_types, syn_err_weights, X_syn_err) - @inbounds @simd for j in 1:nr - X_meas_syn_scheme_1[j] = (X_meas_syn_scheme_1[j] + X_syn_err[j]) % 2 - X_meas_syn_scheme_2[j] = (X_meas_syn_scheme_2[j] + X_syn_err[j]) % 2 + @inbounds @simd for j = 1:nr + X_meas_syn_scheme_1[j] = + (X_meas_syn_scheme_1[j] + X_syn_err[j]) % 2 + X_meas_syn_scheme_2[j] = + (X_meas_syn_scheme_2[j] + X_syn_err[j]) % 2 end end @@ -402,19 +524,30 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < LinearAlgebra.mul!(m, X_meta_Int, X_meas_syn_scheme_1) LinearAlgebra.mul!(m_2, X_meta_Int, X_meas_syn_scheme_2) - @inbounds @simd for j in 1:length(m) + @inbounds @simd for j = 1:length(m) m[j] %= 2 m_2[j] %= 2 end if !iszero(m) # decode with metachecks - X_flag_meta, X_out_meta, _, = CodingTheory._message_passing_layered(X_meta_Int, - X_meas_syn_scheme_1, chn_inits_meta, - CodingTheory._SP_check_node_message_box_plus, var_adj_list_meta, - check_adj_list_meta, max_iter, schedule, current_bits_meta, - totals_meta, syn_meta, check_to_var_messages_meta, - var_to_check_messages_meta, 0.0, X_layers_meta) + X_flag_meta, X_out_meta, _, = CodingTheory._message_passing_layered( + X_meta_Int, + X_meas_syn_scheme_1, + chn_inits_meta, + CodingTheory._SP_check_node_message_box_plus, + var_adj_list_meta, + check_adj_list_meta, + max_iter, + schedule, + current_bits_meta, + totals_meta, + syn_meta, + check_to_var_messages_meta, + var_to_check_messages_meta, + 0.0, + X_layers_meta, + ) # println("meta flag: $X_flag_meta") # reset inputs for next run, but don't re-allocate new memory @@ -422,55 +555,77 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < var_to_check_messages_meta .= 0.0 if X_flag_meta - @inbounds @simd for j in 1:nr + @inbounds @simd for j = 1:nr X_syn_temp[j] = (X_meas_syn_scheme_1[j] + X_out_meta[j]) % 2 end # check if has element of homology LinearAlgebra.mul!(m2, X_meta_L_Int, X_syn_temp) - @inbounds @simd for j in 1:length(m2) + @inbounds @simd for j = 1:length(m2) m2[j] %= 2 end if !iszero(m2) # println("decoding other metachecks") - X_flag_meta_L, X_out_meta_L, _, = - CodingTheory._message_passing_layered(X_meta_L_Int, X_meas_syn_scheme_1, - chn_inits_meta_L, CodingTheory._SP_check_node_message_box_plus, - var_adj_list_meta_L, check_adj_list_meta_L, max_iter, schedule, - current_bits_meta_L, totals_meta_L, syn_meta_L, - check_to_var_messages_meta_L, var_to_check_messages_meta_L, - 0.0, X_layers_meta_L) + X_flag_meta_L, X_out_meta_L, _, = + CodingTheory._message_passing_layered( + X_meta_L_Int, + X_meas_syn_scheme_1, + chn_inits_meta_L, + CodingTheory._SP_check_node_message_box_plus, + var_adj_list_meta_L, + check_adj_list_meta_L, + max_iter, + schedule, + current_bits_meta_L, + totals_meta_L, + syn_meta_L, + check_to_var_messages_meta_L, + var_to_check_messages_meta_L, + 0.0, + X_layers_meta_L, + ) # println("meta_L flag: $X_flag_meta_L") - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_meta_L .= 0.0 var_to_check_messages_meta_L .= 0.0 - + # this is new and still doesn't seem to help if X_flag_meta_L - @inbounds @simd for j in i:nr + @inbounds @simd for j = i:nr X_meas_syn_scheme_1[j] += X_out_meta_L[j] X_meas_syn_scheme_1[j] %= 2 end else - @inbounds @simd for j in i:nr + @inbounds @simd for j = i:nr X_meas_syn_scheme_1[j] = X_syn_temp[j] end - end + end else - @inbounds @simd for j in i:nr + @inbounds @simd for j = i:nr X_meas_syn_scheme_1[j] = X_syn_temp[j] end end else - X_flag_meta_L, X_out_meta_L, _, = - CodingTheory._message_passing_layered(X_meta_L_Int, X_meas_syn_scheme_1, - chn_inits_meta_L, CodingTheory._SP_check_node_message_box_plus, - var_adj_list_meta_L, check_adj_list_meta_L, max_iter, schedule, - current_bits_meta_L, totals_meta_L, syn_meta_L, - check_to_var_messages_meta_L, var_to_check_messages_meta_L, - 0.0, X_layers_meta_L) + X_flag_meta_L, X_out_meta_L, _, = + CodingTheory._message_passing_layered( + X_meta_L_Int, + X_meas_syn_scheme_1, + chn_inits_meta_L, + CodingTheory._SP_check_node_message_box_plus, + var_adj_list_meta_L, + check_adj_list_meta_L, + max_iter, + schedule, + current_bits_meta_L, + totals_meta_L, + syn_meta_L, + check_to_var_messages_meta_L, + var_to_check_messages_meta_L, + 0.0, + X_layers_meta_L, + ) # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_meta_L .= 0.0 @@ -478,7 +633,7 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < # this is new and still doesn't seem to help if X_flag_meta_L - @inbounds @simd for j in i:nr + @inbounds @simd for j = i:nr X_meas_syn_scheme_1[j] += X_out_meta_L[j] X_meas_syn_scheme_1[j] %= 2 end @@ -487,18 +642,30 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < end # decode stabilizers - X_flag_stabs, X_out_stabs, _, = CodingTheory._message_passing_layered(X_stabs_Int, - X_meas_syn_scheme_1, chn_inits_stabs, CodingTheory._SP_check_node_message_box_plus, - var_adj_list_stabs, check_adj_list_stabs, max_iter, schedule, - current_bits_stabs, totals_stabs, syn_stabs, check_to_var_messages_stabs, - var_to_check_messages_stabs, 0.0, X_layers_stabs) + X_flag_stabs, X_out_stabs, _, = CodingTheory._message_passing_layered( + X_stabs_Int, + X_meas_syn_scheme_1, + chn_inits_stabs, + CodingTheory._SP_check_node_message_box_plus, + var_adj_list_stabs, + check_adj_list_stabs, + max_iter, + schedule, + current_bits_stabs, + totals_stabs, + syn_stabs, + check_to_var_messages_stabs, + var_to_check_messages_stabs, + 0.0, + X_layers_stabs, + ) # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_stabs .= 0.0 var_to_check_messages_stabs .= 0.0 if X_flag_stabs - @inbounds @simd for j in 1:n + @inbounds @simd for j = 1:n state_scheme_1[j] += X_out_stabs[j] end end @@ -508,17 +675,30 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < ########### # decode single-shot matrix - X_flag_ss, X_out_ss, _, = CodingTheory._message_passing_layered(X_ss_Int, Int[X_meas_syn_scheme_2; m_2], - chn_inits_ss, CodingTheory._SP_check_node_message_box_plus, var_adj_list_ss, - check_adj_list_ss, max_iter, schedule, current_bits_ss, totals_ss, - syn_ss, check_to_var_messages_ss, var_to_check_messages_ss, 0.0, X_layers_ss) + X_flag_ss, X_out_ss, _, = CodingTheory._message_passing_layered( + X_ss_Int, + Int[X_meas_syn_scheme_2; m_2], + chn_inits_ss, + CodingTheory._SP_check_node_message_box_plus, + var_adj_list_ss, + check_adj_list_ss, + max_iter, + schedule, + current_bits_ss, + totals_ss, + syn_ss, + check_to_var_messages_ss, + var_to_check_messages_ss, + 0.0, + X_layers_ss, + ) # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_ss .= 0.0 var_to_check_messages_ss .= 0.0 # only take the bits corresponding to the data error - @inbounds @simd for j in 1:n + @inbounds @simd for j = 1:n state_scheme_2[j] += X_out_ss[j] end end @@ -533,7 +713,7 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < # check for logical error logs_flag = false LinearAlgebra.mul!(logs_check, X_logs_Int, state_scheme_1) - @inbounds for j in 1:nr_logs + @inbounds for j = 1:nr_logs logs_check[j, 1] %= 2 if logs_check[j, 1] == 1 logs_flag = true @@ -559,7 +739,7 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < # check for logical error logs_flag = false LinearAlgebra.mul!(logs_check, X_logs_Int, state_scheme_2) - @inbounds for j in 1:nr_logs + @inbounds for j = 1:nr_logs logs_check[j, 1] %= 2 if logs_check[j, 1] == 1 logs_flag = true @@ -580,12 +760,14 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < state_scheme_2 .= 0 end end - + # reduce iteration counts - @inbounds for i in 2:num_threads - @simd for j in 1:nr_logs - local_log_failure_counts_scheme_1[1][j] += local_log_failure_counts_scheme_1[i][j] - local_log_failure_counts_scheme_2[1][j] += local_log_failure_counts_scheme_2[i][j] + @inbounds for i = 2:num_threads + @simd for j = 1:nr_logs + local_log_failure_counts_scheme_1[1][j] += + local_log_failure_counts_scheme_1[i][j] + local_log_failure_counts_scheme_2[1][j] += + local_log_failure_counts_scheme_2[i][j] end end @@ -600,7 +782,7 @@ function CSS_metachecks(X_stabs::T, X_logs::T, X_meta::T, X_meta_L::T) where T < println("Finished p = $p") # reset inputs for next run, but don't re-allocate new memory - @inbounds for i in 1:num_threads + @inbounds for i = 1:num_threads local_log_failure_counts_scheme_1[i] .= 0 local_log_failure_counts_scheme_2[i] .= 0 end diff --git a/docs/src/references.bib b/docs/src/references.bib index 4de5f4f7..f69fa2ec 100644 --- a/docs/src/references.bib +++ b/docs/src/references.bib @@ -7,13 +7,13 @@ @misc{hastings2021quantum } @misc{hastings2016, - title={Weight Reduction for Quantum Codes}, - author={M. B. Hastings}, - year={2016}, - eprint={1611.03790}, - archivePrefix={arXiv}, - primaryClass={quant-ph}, - url={https://arxiv.org/abs/1611.03790}, + title={Weight Reduction for Quantum Codes}, + author={M. B. Hastings}, + year={2016}, + eprint={1611.03790}, + archivePrefix={arXiv}, + primaryClass={quant-ph}, + url={https://arxiv.org/abs/1611.03790}, } @inproceedings{hastings2021fiber, @@ -241,3 +241,75 @@ @article{bitner1976efficient year={1976}, publisher={ACM New York, NY, USA} } + +@article{Poulin_2005, + title={Stabilizer Formalism for Operator Quantum Error Correction}, + volume={95}, + ISSN={1079-7114}, + url={http://dx.doi.org/10.1103/PhysRevLett.95.230504}, + DOI={10.1103/physrevlett.95.230504}, + number={23}, + journal={Physical Review Letters}, + publisher={American Physical Society (APS)}, + author={Poulin, David}, + year={2005}, + month=dec +} + +@article{Bravyi_2011, + title={Subsystem codes with spatially local generators}, + volume={83}, + ISSN={1094-1622}, + url={http://dx.doi.org/10.1103/PhysRevA.83.012320}, + DOI={10.1103/physreva.83.012320}, + number={1}, + journal={Physical Review A}, + publisher={American Physical Society (APS)}, + author={Bravyi, Sergey}, + year={2011}, + month=jan +} + +@misc{napp2012optimalbaconshorcodes, + title={Optimal Bacon-Shor codes}, + author={John Napp and John Preskill}, + year={2012}, + eprint={1209.0794}, + archivePrefix={arXiv}, + primaryClass={quant-ph}, + url={https://arxiv.org/abs/1209.0794}, +} + +@misc{bacon2006qecsubsystem, + title={Quantum Error Correcting Subsystem Codes From Two Classical Linear Codes}, + author={Dave Bacon and Andrea Casaccino}, + year={2006}, + eprint={quant-ph/0610088}, + archivePrefix={arXiv}, + primaryClass={quant-ph}, + url={https://arxiv.org/abs/quant-ph/0610088}, +} + +@misc{bravyi2013subsystemsurfacecodesthreequbit, + title={Subsystem surface codes with three-qubit check operators}, + author={Sergey Bravyi and Guillaume Duclos-Cianci and David Poulin and Martin Suchara}, + year={2013}, + eprint={1207.1443}, + archivePrefix={arXiv}, + primaryClass={quant-ph}, + url={https://arxiv.org/abs/1207.1443}, +} + +@article{Tomita_2014, + title={Low-distance surface codes under realistic quantum noise}, + volume={90}, + ISSN={1094-1622}, + url={http://dx.doi.org/10.1103/PhysRevA.90.062320}, + DOI={10.1103/physreva.90.062320}, + number={6}, + journal={Physical Review A}, + publisher={American Physical Society (APS)}, + author={Tomita, Yu and Svore, Krysta M.}, + year={2014}, + month=dec +} diff --git a/ext/JLD2Ext/JLD2Ext.jl b/ext/JLD2Ext/JLD2Ext.jl index 8e90cc36..4262c923 100644 --- a/ext/JLD2Ext/JLD2Ext.jl +++ b/ext/JLD2Ext/JLD2Ext.jl @@ -1,7 +1,12 @@ module JLD2Ext import CodingTheory -import CodingTheory: TriangularColorCode488, TriangularColorCode666, StabilizerCode, set_logicals!, set_minimum_distance! #PlanarSurfaceCode3D, PlanarSurfaceCode3D_X, ToricCode3D, +import CodingTheory: + TriangularColorCode488, + TriangularColorCode666, + StabilizerCode, + set_logicals!, + set_minimum_distance! #PlanarSurfaceCode3D, PlanarSurfaceCode3D_X, ToricCode3D, import JLD2 import JLD2: @load import Oscar: GF, matrix diff --git a/ext/JLD2Ext/Quantum/misc_known_codes.jl b/ext/JLD2Ext/Quantum/misc_known_codes.jl index 7a3dc142..cf2eee4b 100644 --- a/ext/JLD2Ext/Quantum/misc_known_codes.jl +++ b/ext/JLD2Ext/Quantum/misc_known_codes.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ################################ - # Triangular Color Codes 4.8.8 +# Triangular Color Codes 4.8.8 ################################ """ @@ -45,7 +45,7 @@ function CodingTheory.TriangularColorCode488(d::Int) end ################################ - # Triangular Color Codes 6.6.6 +# Triangular Color Codes 6.6.6 ################################ """ @@ -78,7 +78,7 @@ function CodingTheory.TriangularColorCode666(d::Int) elseif d == 19 @load joinpath(path, "666d19stabslogs_trellis.jld2") S l elseif d == 21 - @load joinpath(path, "666d21stabslogs_trellis.jld2") S l + @load joinpath(path, "666d21stabslogs_trellis.jld2") S l end F = CodingTheory.Oscar.Nemo.Native.GF(2) Q = StabilizerCode(CodingTheory.Oscar.matrix(F, S)) @@ -88,7 +88,7 @@ function CodingTheory.TriangularColorCode666(d::Int) end ################################ - # 3D PlanarSurfaceCode +# 3D PlanarSurfaceCode ################################ # TODO missing Z matrices @@ -136,12 +136,13 @@ function CodingTheory.PlanarSurfaceCode3D_X(d::Int) X_meta = load_alist(joinpath(path, "surface3D_9_mx.alist")) end F = CodingTheory.Oscar.Nemo.Native.GF(2) - return CodingTheory.Oscar.matrix(F, X_stabs), CodingTheory.Oscar.matrix(F, X_logs), - CodingTheory.Oscar.matrix(F, X_meta) + return CodingTheory.Oscar.matrix(F, X_stabs), + CodingTheory.Oscar.matrix(F, X_logs), + CodingTheory.Oscar.matrix(F, X_meta) end ################################# - # 3D Toric codes +# 3D Toric codes ################################# # TODO missing Z matrices @@ -209,6 +210,7 @@ function CodingTheory.ToricCode3D_X(d::Int) X_meta = load_alist(joinpath(path, "toric3D_13_mx.alist")) end F = CodingTheory.Oscar.Nemo.Native.GF(2) - return CodingTheory.Oscar.matrix(F, X_stabs), CodingTheory.Oscar.matrix(F, X_logs), - CodingTheory.Oscar.matrix(F, X_meta) + return CodingTheory.Oscar.matrix(F, X_stabs), + CodingTheory.Oscar.matrix(F, X_logs), + CodingTheory.Oscar.matrix(F, X_meta) end diff --git a/ext/JuMPExt/JuMPExt.jl b/ext/JuMPExt/JuMPExt.jl index 76295f29..e3a40b93 100644 --- a/ext/JuMPExt/JuMPExt.jl +++ b/ext/JuMPExt/JuMPExt.jl @@ -1,7 +1,13 @@ module JuMPExt import CodingTheory -import CodingTheory: optimal_lambda, optimal_rho, optimal_lambda_and_rho, LP_decoder_LDPC, AbstractLinearCode, BinarySymmetricChannel +import CodingTheory: + optimal_lambda, + optimal_rho, + optimal_lambda_and_rho, + LP_decoder_LDPC, + AbstractLinearCode, + BinarySymmetricChannel import JuMP import JuMP: @variable, @constraint, @objective import GLPK diff --git a/ext/JuMPExt/LDPC/analysis.jl b/ext/JuMPExt/LDPC/analysis.jl index ee3ae118..baba6427 100644 --- a/ext/JuMPExt/LDPC/analysis.jl +++ b/ext/JuMPExt/LDPC/analysis.jl @@ -4,37 +4,51 @@ # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. -function _find_lambda_given_rho(ρ::Union{Vector{Float64}, CodingTheory.Oscar.PolyRingElem}, - ε::Float64, l_max::Int; Δ = 0.001) +function _find_lambda_given_rho( + ρ::Union{Vector{Float64},CodingTheory.Oscar.PolyRingElem}, + ε::Float64, + l_max::Int; + Δ = 0.001, +) model = Model(GLPK.Optimizer) - @variable(model, λ[1:l_max - 1] >= 0) + @variable(model, λ[1:(l_max-1)] >= 0) @constraint(model, sum(λ) == 1) - for x in 0:Δ:1 - @constraint(model, ε * sum(λ[i] * (1 - CodingTheory._poly_eval(1 - x, ρ))^i for i in - 1:l_max - 1) - x <= 0) + for x = 0:Δ:1 + @constraint( + model, + ε * sum(λ[i] * (1 - CodingTheory._poly_eval(1 - x, ρ))^i for i = 1:(l_max-1)) - + x <= 0 + ) end @constraint(model, ε * CodingTheory._d_poly_eval(1, ρ) * λ[1] <= 1) - @objective(model, Max, sum(λ[i] / (i + 1) for i in 1:l_max - 1)) + @objective(model, Max, sum(λ[i] / (i + 1) for i = 1:(l_max-1))) optimize!(model) termination_status(model) == MOI.INFEASIBLE && throw(DomainError("No solution exists")) @assert termination_status(model) == MOI.OPTIMAL "Didn't find an optimal point" return [0.0; value.(λ)], model end -function _find_rho_given_lambda(λ::Union{Vector{Float64}, CodingTheory.Oscar.PolyRingElem}, - ε::Float64, r_max::Int; Δ = 0.001) +function _find_rho_given_lambda( + λ::Union{Vector{Float64},CodingTheory.Oscar.PolyRingElem}, + ε::Float64, + r_max::Int; + Δ = 0.001, +) model = Model(GLPK.Optimizer) - @variable(model, ρ[1:r_max - 1] >= 0) + @variable(model, ρ[1:(r_max-1)] >= 0) @constraint(model, sum(ρ) == 1) - for x in 0:Δ:1 - @constraint(model, 1 - x - sum(ρ[i] * (1 - ε * CodingTheory._poly_eval(x, λ))^i for i in - 1:r_max - 1) <= 0) + for x = 0:Δ:1 + @constraint( + model, + 1 - x - + sum(ρ[i] * (1 - ε * CodingTheory._poly_eval(x, λ))^i for i = 1:(r_max-1)) <= 0 + ) end temp = isa(λ, PolyRingElem) ? Float64(coeff(λ, 1)) : λ[2] @constraint(model, ε * sum(i * ρ[i] for i in eachindex(ρ)) * temp <= 1) - @objective(model, Min, sum(ρ[i] / (i + 1) for i in 1:r_max - 1)) + @objective(model, Min, sum(ρ[i] / (i + 1) for i = 1:(r_max-1))) optimize!(model) termination_status(model) == MOI.INFEASIBLE && throw(DomainError("No solution exists")) @assert termination_status(model) == MOI.OPTIMAL "Didn't find an optimal point" @@ -51,13 +65,21 @@ distribution `ρ`, maximum variable node degree `l_max`, and target parameter # Notes * `Δ` refers to the step size for `x` in the LP to solve for `λ`. """ -function CodingTheory.optimal_lambda(ρ, l_max::Int, param::Float64, var_type::Symbol; Δ = 0.001) - var_type ∈ (:r, :ε) || throw(ArgumentError("var_type must be :r for target rate or :ε for threshold")) - var_type == :r && param >= 1 - 2 * CodingTheory._integrate_poly_0_1(ρ) && throw( - ArgumentError("This rate is unachieveable with the given ρ.")) +function CodingTheory.optimal_lambda( + ρ, + l_max::Int, + param::Float64, + var_type::Symbol; + Δ = 0.001, +) + var_type ∈ (:r, :ε) || + throw(ArgumentError("var_type must be :r for target rate or :ε for threshold")) + var_type == :r && + param >= 1 - 2 * CodingTheory._integrate_poly_0_1(ρ) && + throw(ArgumentError("This rate is unachieveable with the given ρ.")) # TODO: check for when var_type == :ε as well - λ_vec, r, ε = _optimal_distributions(ρ, :ρ, l_max, param, var_type, Δλ = 0.001) + λ_vec, r, ε = _optimal_distributions(ρ, :ρ, l_max, param, var_type, Δλ = 0.001) _, x = CodingTheory.Oscar.PolynomialRing(CodingTheory.Oscar.RealField(), :x) λ = sum(c * x^(i - 1) for (i, c) in enumerate(λ_vec)) return (λ = λ, r = r, ε = ε) @@ -74,8 +96,10 @@ which refers to threshold if `var_type == :ε` or rate if `var_type == :r`. * `Δ` refers to the step size for x in the LP to solve for ρ. """ function CodingTheory.optimal_rho(λ, r_max::Int, param::Float64, var_type::Symbol, Δ = 1e-3) - var_type ∈ (:r, :ε) || throw(ArgumentError("var_type must be :r for target rate or :ε for threshold")) - var_type == :r && param >= 1 - 1 / (r_max * CodingTheory._integrate_poly_0_1(λ)) && + var_type ∈ (:r, :ε) || + throw(ArgumentError("var_type must be :r for target rate or :ε for threshold")) + var_type == :r && + param >= 1 - 1 / (r_max * CodingTheory._integrate_poly_0_1(λ)) && throw(ArgumentError("This rate is unachieveable with the given r_max and λ.")) # TODO: check for when var_type == :ε as well @@ -86,8 +110,15 @@ function CodingTheory.optimal_rho(λ, r_max::Int, param::Float64, var_type::Symb end # TODO: add a type on poly -function _optimal_distributions(poly, poly_type::Symbol, var_max::Int, real_param::Float64, - var_type::Symbol; Δλ = 0.001, Δρ = 0.001) +function _optimal_distributions( + poly, + poly_type::Symbol, + var_max::Int, + real_param::Float64, + var_type::Symbol; + Δλ = 0.001, + Δρ = 0.001, +) int_poly = CodingTheory._integrate_poly_0_1(poly) if var_type == :r @@ -115,7 +146,9 @@ function _optimal_distributions(poly, poly_type::Symbol, var_max::Int, real_para end Δ > 0 ? (low = mid;) : (high = mid;) end - 0 <= Δ <= tolerance || error("Solution for $(poly_type == :ρ ? :λ : :ρ) did not converge in $max_iters iterations") + 0 <= Δ <= tolerance || error( + "Solution for $(poly_type == :ρ ? :λ : :ρ) did not converge in $max_iters iterations", + ) return sol, sol_rate, mid else if poly_type == :ρ @@ -136,14 +169,17 @@ function _find_lambda_and_rho(l_max::Int, r_max::Int, ε::Float64; Δρ = 0.01, ρ = zeros(r_max, iters) λ = zeros(l_max, iters) rates = fill(-Inf, iters) - for i in 1:iters + for i = 1:iters ρ[end, i] = c[i] - ρ[end - 1, i] = (1 - c[i]) + ρ[end-1, i] = (1 - c[i]) try λ[:, i] .= _find_lambda_given_rho(ρ[:, i], ε, l_max, Δ = Δλ)[1] - rates[i] = 1 - CodingTheory._integrate_poly_0_1(ρ[:, i]) / + rates[i] = + 1 - + CodingTheory._integrate_poly_0_1(ρ[:, i]) / CodingTheory._integrate_poly_0_1(λ[:, i]) - catch end + catch + end end i = argmax(rates) isfinite(rates[i]) || throw(ArgumentError("No solution for given parameters")) @@ -161,8 +197,14 @@ either a threshold if `var_type == :ε` or a target rate if `var_type == :r`. ρ = (1 - c) * x^(r_max - 2) + c * x^(r_max - 1) * `Δλ` gives the step size for values of `x` in the LP for finding λ given ρ. """ -function CodingTheory.optimal_lambda_and_rho(l_max::Int, r_max::Int, param::Float64, - var_type::Symbol; Δρ = 0.01, Δλ = 0.001) +function CodingTheory.optimal_lambda_and_rho( + l_max::Int, + r_max::Int, + param::Float64, + var_type::Symbol; + Δρ = 0.01, + Δλ = 0.001, +) if var_type == :r tolerance = 1e-6 @@ -183,7 +225,9 @@ function CodingTheory.optimal_lambda_and_rho(l_max::Int, r_max::Int, param::Floa end Δ > 0 ? (low = mid;) : (high = mid;) end - 0 <= Δ <= tolerance || error("Solution for $(poly_type == :ρ ? :λ : :ρ) did not converge in $max_iters iterations") + 0 <= Δ <= tolerance || error( + "Solution for $(poly_type == :ρ ? :λ : :ρ) did not converge in $max_iters iterations", + ) _, x = CodingTheory.Oscar.PolynomialRing(CodingTheory.Oscar.RealField(), :x) λ = sum(c * x^(i - 1) for (i, c) in enumerate(λ_vec)) ρ = sum(c * x^(i - 1) for (i, c) in enumerate(ρ_vec)) diff --git a/ext/JuMPExt/LDPC/decoders.jl b/ext/JuMPExt/LDPC/decoders.jl index 38b8827a..84f9b204 100644 --- a/ext/JuMPExt/LDPC/decoders.jl +++ b/ext/JuMPExt/LDPC/decoders.jl @@ -5,14 +5,16 @@ # LICENSE file in the root directory of this source tree. ############################# - # LP Decoders +# LP Decoders ############################# -function _init_LP_decoder_LDPC(H::Union{CodingTheory.CTMatrixTypes, AbstractMatrix{<:Number}}) +function _init_LP_decoder_LDPC( + H::Union{CodingTheory.CTMatrixTypes,AbstractMatrix{<:Number}}, +) check_adj_list, _ = CodingTheory._node_adjacencies(H) subsets = Vector{Vector{Vector{Int}}}() nr, nc = size(H) - hasi = [[Vector{Int}() for _ in 1:nc] for _ in 1:nr] + hasi = [[Vector{Int}() for _ = 1:nc] for _ = 1:nr] wmap = zeros(Int, nr) curr = 1 for (j, cn) in enumerate(check_adj_list) @@ -32,28 +34,31 @@ function _init_LP_decoder_LDPC(H::Union{CodingTheory.CTMatrixTypes, AbstractMatr model = Model(GLPK.Optimizer) @variable(model, 0 <= f[1:nc] <= 1) - @variable(model, 0 <= w[1:curr - 1] <= 1) - for i in 1:nr + @variable(model, 0 <= w[1:(curr-1)] <= 1) + for i = 1:nr if i != nr - @constraint(model, sum(w[wmap[i]:wmap[i + 1] - 1]) == 1) + @constraint(model, sum(w[wmap[i]:(wmap[i+1]-1)]) == 1) else @constraint(model, sum(w[wmap[i]:end]) == 1) end end - for j in 1:nr - for i in 1:nc + for j = 1:nr + for i = 1:nc if !isempty(hasi[j][i]) @constraint(model, f[i] == sum(w[hasi[j][i]])) end end end - @objective(model, Min, sum(0 * f[i] for i in 1:nc)) + @objective(model, Min, sum(0 * f[i] for i = 1:nc)) return model end _init_LP_decoder_LDPC(C::AbstractLinearCode) = _init_LP_decoder_LDPC(parity_check_matrix(C)) -function _LP_decoder_LDPC(model::JuMP.Model, v::Union{CodingTheory.CTMatrixTypes, - Vector{<:Integer}}, Ch::BinarySymmetricChannel) +function _LP_decoder_LDPC( + model::JuMP.Model, + v::Union{CodingTheory.CTMatrixTypes,Vector{<:Integer}}, + Ch::BinarySymmetricChannel, +) γ = CodingTheory._channel_init_BSC(isa(v, Vector) ? v : Int.(data.(v))[:], Ch.param) @objective(model, Min, dot(γ, model[:f])) @@ -65,11 +70,17 @@ function _LP_decoder_LDPC(model::JuMP.Model, v::Union{CodingTheory.CTMatrixTypes return w end -function CodingTheory.LP_decoder_LDPC(H::Union{CodingTheory.CTMatrixTypes, AbstractMatrix{<:Number}}, v::Union{CodingTheory.CTMatrixTypes, Vector{<:Integer}}, Ch::BinarySymmetricChannel) - +function CodingTheory.LP_decoder_LDPC( + H::Union{CodingTheory.CTMatrixTypes,AbstractMatrix{<:Number}}, + v::Union{CodingTheory.CTMatrixTypes,Vector{<:Integer}}, + Ch::BinarySymmetricChannel, +) + model = _init_LP_decoder_LDPC(H) return _LP_decoder_LDPC(model, v, Ch) end -CodingTheory.LP_decoder_LDPC(C::AbstractLinearCode, v::Union{CodingTheory.CTMatrixTypes, - Vector{<:Integer}}, Ch::BinarySymmetricChannel) = CodingTheory.LP_decoder_LDPC( - parity_check_matrix(C), v, Ch) +CodingTheory.LP_decoder_LDPC( + C::AbstractLinearCode, + v::Union{CodingTheory.CTMatrixTypes,Vector{<:Integer}}, + Ch::BinarySymmetricChannel, +) = CodingTheory.LP_decoder_LDPC(parity_check_matrix(C), v, Ch) diff --git a/ext/MakieExt/Classical/Tanner.jl b/ext/MakieExt/Classical/Tanner.jl index c1004461..81beb66e 100644 --- a/ext/MakieExt/Classical/Tanner.jl +++ b/ext/MakieExt/Classical/Tanner.jl @@ -12,21 +12,25 @@ Return the Tanner graph of the matrix `H` as a `Figure` object. # Note - Run `using Makie` to activate this extension. """ -function CodingTheory.Tanner_graph_plot(H::Union{CodingTheory.CTMatrixTypes, Matrix{Int}}) +function CodingTheory.Tanner_graph_plot(H::Union{CodingTheory.CTMatrixTypes,Matrix{Int}}) # convert H to A M = CodingTheory._Flint_matrix_to_Julia_int_matrix(H) nr, nc = size(M) A = zeros(Int, nr + nc, nr + nc) # put in top right corner in order to get parents, children working - A[1:nc, nc + 1:end] = transpose(M) + A[1:nc, (nc+1):end] = transpose(M) fig = CairoMakie.Figure(); - ax = CairoMakie.Axis(fig[1, 1], yreversed = true, xautolimitmargin = (0.15, 0.20), - yautolimitmargin = (0.15, 0.20)) + ax = CairoMakie.Axis( + fig[1, 1], + yreversed = true, + xautolimitmargin = (0.15, 0.20), + yautolimitmargin = (0.15, 0.20), + ) CairoMakie.hidespines!(ax) CairoMakie.hidedecorations!(ax) - left_x, left_y = zeros(nc), 1.:nc + left_x, left_y = zeros(nc), 1.0:nc right_x, right_y = ones(nr) * nr, range(1, nc, nr) x = vcat(left_x, right_x) y = vcat(left_y, right_y) @@ -39,8 +43,12 @@ function CodingTheory.Tanner_graph_plot(H::Union{CodingTheory.CTMatrixTypes, Mat for (i, v) in enumerate(children) for node in parents[v] - CairoMakie.lines!([CairoMakie.Point2f(x[[node, v]])...], [CairoMakie.Point2f(y[[node, - v]])...], color = cols[i % 6 + 1], linewidth = 5) + CairoMakie.lines!( + [CairoMakie.Point2f(x[[node, v]])...], + [CairoMakie.Point2f(y[[node, v]])...], + color = cols[i%6+1], + linewidth = 5, + ) end CairoMakie.text!(points[v], text = L"c_{%$i}", offset = (20, -15)) end @@ -50,7 +58,7 @@ function CodingTheory.Tanner_graph_plot(H::Union{CodingTheory.CTMatrixTypes, Mat CairoMakie.text!(point, text = L"v_{%$i}", offset = (-30, -10)) end - for (i, point) in enumerate(points[nc + 1:end]) + for (i, point) in enumerate(points[(nc+1):end]) CairoMakie.scatter!(point, color = :black, marker = :rect, markersize = 25) end display(fig) diff --git a/ext/MakieExt/Classical/weight_dist.jl b/ext/MakieExt/Classical/weight_dist.jl index b195f92c..ebff2fb2 100644 --- a/ext/MakieExt/Classical/weight_dist.jl +++ b/ext/MakieExt/Classical/weight_dist.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # Weight Enumerators +# Weight Enumerators ############################# """ @@ -19,9 +19,9 @@ Return a bar graph of the weight distribution of `C`. function CodingTheory.weight_plot(C::AbstractLinearCode; alg::Symbol = :auto) wt_dist = weight_distribution(C, alg = alg, compact = true) x_ticks = findall(x -> x > 0, vec(wt_dist)) .- 1 - y_ticks = [wt_dist[i] for i in 1:length(wt_dist) if !iszero(wt_dist[i])] + y_ticks = [wt_dist[i] for i = 1:length(wt_dist) if !iszero(wt_dist[i])] ismissing(C.d) ? (title = "Weight Distribution - [$(C.n), $(C.k)]";) : - title = "Weight Distribution - [$(C.n), $(C.k), $(C.d)]" + title = "Weight Distribution - [$(C.n), $(C.k), $(C.d)]" fig = Figure() ax = Axis(fig[1, 1], xlabel = "Weight", ylabel = "Number of Terms", title = title) diff --git a/ext/MakieExt/LDPC/analysis.jl b/ext/MakieExt/LDPC/analysis.jl index 46d9e3ac..d20295c8 100644 --- a/ext/MakieExt/LDPC/analysis.jl +++ b/ext/MakieExt/LDPC/analysis.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # general functions +# general functions ############################# """ @@ -16,8 +16,12 @@ Return a plot of the EXIT chart for the ensemble given the channel up to a numer # Note - Run `using Makie` to activate this extension. """ -function CodingTheory.EXIT_chart_plot(E::LDPCEnsemble, Ch::AbstractClassicalNoiseChannel; tol::Float64 = 1e-9) - +function CodingTheory.EXIT_chart_plot( + E::LDPCEnsemble, + Ch::AbstractClassicalNoiseChannel; + tol::Float64 = 1e-9, +) + @assert isa(Ch, BinaryErasureChannel) "Only BEC is implemented so far" x = 0:0.01:1 c = 1 .- [CodingTheory._poly_eval(x, E.ρ) for x in 1 .- x] diff --git a/ext/MakieExt/LDPC/codes.jl b/ext/MakieExt/LDPC/codes.jl index cab1f927..56d88e5e 100644 --- a/ext/MakieExt/LDPC/codes.jl +++ b/ext/MakieExt/LDPC/codes.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # general functions +# general functions ############################# """ @@ -33,12 +33,25 @@ function CodingTheory.degree_distributions_plot(C::AbstractLDPCCode) # f = Plots.plot(f1, f2, layout = (1, 2)) fig = Figure() - ax1 = Axis(fig[1, 1], xlabel = "Degree", ylabel = "Occurrences", title = "Variable Nodes") + ax1 = + Axis(fig[1, 1], xlabel = "Degree", ylabel = "Occurrences", title = "Variable Nodes") ax2 = Axis(fig[1, 1], xlabel = "Degree", ylabel = "Occurrences", title = "Check Nodes") - barplot!(ax1, cols_x_data, cols_y_data, bar_width = 1, xticks = cols_x_data, - yticks = cols_y_data) - barplot!(ax2, rows_x_data, rows_y_data, bar_width = 1, xticks = rows_x_data, - yticks = rows_y_data) + barplot!( + ax1, + cols_x_data, + cols_y_data, + bar_width = 1, + xticks = cols_x_data, + yticks = cols_y_data, + ) + barplot!( + ax2, + rows_x_data, + rows_y_data, + bar_width = 1, + xticks = rows_x_data, + yticks = rows_y_data, + ) display(f) return f end @@ -55,12 +68,20 @@ for node `v`. If `v_type` is `:v`, `v` is interpreted as a variable node; otherw # Note - Run `using Makie` to activate this extension. """ -function CodingTheory.computation_graph(C::AbstractLDPCCode, lvl::Int, v::Int, v_type::Symbol = :v) +function CodingTheory.computation_graph( + C::AbstractLDPCCode, + lvl::Int, + v::Int, + v_type::Symbol = :v, +) v_type ∈ (:v, :c) || throw(ArgumentError("Unknown argument for v_type")) if v_type == :v - 1 <= v <= C.n || throw(DomainError("Variable node index must be between 1 and length(C)")) + 1 <= v <= C.n || + throw(DomainError("Variable node index must be between 1 and length(C)")) else - 1 <= v <= nrows(C.H) || throw(DomainError("Check node index must be between 1 and the number of rows of H")) + 1 <= v <= nrows(C.H) || throw( + DomainError("Check node index must be between 1 and the number of rows of H"), + ) end lvl > 0 || throw(DomainError("Graph recipe requires at least one level")) @@ -83,7 +104,7 @@ function CodingTheory.computation_graph(C::AbstractLDPCCode, lvl::Int, v::Int, v push!(colors, :red) push!(markers, :rect) end - + queue = Queue{_ComputationGraphNode}() enqueue!(queue, root) while length(queue) > 0 @@ -119,13 +140,16 @@ function CodingTheory.computation_graph(C::AbstractLDPCCode, lvl::Int, v::Int, v end # TODO: fix plot - count number of added nodes in level and manually pass in a calculated image size - f, ax, p = graphplot(G, layout = Buchheim(), + f, ax, p = graphplot( + G, + layout = Buchheim(), nlabels = labels, node_marker = markers, node_color = colors, nlabels_textsize = 10, nlabels_align = (:left, :center), - nlabels_distance = 7); + nlabels_distance = 7, + ); hidedecorations!(ax) hidespines!(ax) display(f) diff --git a/ext/MakieExt/LDPC/cycles.jl b/ext/MakieExt/LDPC/cycles.jl index f74df9f4..134a7fd7 100644 --- a/ext/MakieExt/LDPC/cycles.jl +++ b/ext/MakieExt/LDPC/cycles.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # simple cycles +# simple cycles ############################# """ @@ -21,14 +21,23 @@ enumerated. An empty figure and dictionary are returned when there are no cycles already cached. - Run `using Makie` to activate this extension. """ -function CodingTheory.simple_cycle_length_distribution_plot(L::AbstractLDPCCode; len::Int = -1) +function CodingTheory.simple_cycle_length_distribution_plot( + L::AbstractLDPCCode; + len::Int = -1, +) dist = simple_cycle_length_distribution(L, len = len) x_data = collect(keys(dist)) y_data = collect(values(dist)) - + fig = Figure(); - ax = Axis(fig[1, 1], xlabel = "Cycle Length", ylabel = "Occurrences", - title = "Simple Cycle Counts", xticks = x_data, yticks = y_data) + ax = Axis( + fig[1, 1], + xlabel = "Cycle Length", + ylabel = "Occurrences", + title = "Simple Cycle Counts", + xticks = x_data, + yticks = y_data, + ) barplot!(ax, x_data, y_data, strokewidth = 1) display(fig) return fig @@ -47,23 +56,31 @@ empty figure and dictionary are returned when there are no cycles. already cached. - Run `using Makie` to activate this extension. """ -function CodingTheory.simple_cycle_distribution_by_variable_node_plot(L::AbstractLDPCCode; - len::Int = -1) +function CodingTheory.simple_cycle_distribution_by_variable_node_plot( + L::AbstractLDPCCode; + len::Int = -1, +) dist = simple_cycle_distribution_by_variable_node(L, len = len) collect(keys(dist)) collect(values(dist)) fig = Figure(); - ax = Axis(fig[1, 1], xlabel = "Variable Node Index", ylabel = "Occurrences", - title = "Simple Cycles By Variable Node", xticks = x_data, yticks = y_data) + ax = Axis( + fig[1, 1], + xlabel = "Variable Node Index", + ylabel = "Occurrences", + title = "Simple Cycles By Variable Node", + xticks = x_data, + yticks = y_data, + ) barplot!(ax, x_data, y_data, strokewidth = 1) display(fig) return fig end ############################# - # short cycles +# short cycles ############################# """ @@ -80,14 +97,23 @@ enumerated. An empty figure and dictionary are returned when there are no cycles already cached. - Run `using Makie` to activate this extension. """ -function CodingTheory.short_cycle_length_distribution_plot(L::AbstractLDPCCode; len::Int = -1) +function CodingTheory.short_cycle_length_distribution_plot( + L::AbstractLDPCCode; + len::Int = -1, +) dist = short_cycle_length_distribution(L, len = len) x_data = collect(keys(dist)) y_data = collect(values(dist)) fig = Figure() - ax = Axis(fig[1, 1], xlabel = "Cycle Length", ylabel = "Occurrences", - title = "Short Cycle Counts", xticks = x_data, yticks = y_data) + ax = Axis( + fig[1, 1], + xlabel = "Cycle Length", + ylabel = "Occurrences", + title = "Short Cycle Counts", + xticks = x_data, + yticks = y_data, + ) barplot!(ax, x_data, y_data, strokewidth = 1) display(fig) return fig @@ -107,23 +133,31 @@ empty figure and dictionary are returned when there are no cycles. already cached. - Run `using Makie` to activate this extension. """ -function CodingTheory.short_cycle_distribution_by_variable_node_plot(L::AbstractLDPCCode; - len::Int = -1) +function CodingTheory.short_cycle_distribution_by_variable_node_plot( + L::AbstractLDPCCode; + len::Int = -1, +) dist = short_cycle_distribution_by_variable_node(L, len = len) x_data = collect(keys(dist)) y_data = collect(values(dist)) fig = Figure(); - ax = Axis(fig[1, 1], xlabel = "Variable Node Index", ylabel = "Occurrences", - title = "Short Cycles By Variable Node", xticks = x_data, yticks = y_data) + ax = Axis( + fig[1, 1], + xlabel = "Variable Node Index", + ylabel = "Occurrences", + title = "Short Cycles By Variable Node", + xticks = x_data, + yticks = y_data, + ) barplot!(ax, x_data, y_data, strokewidth = 1) display(fig) return fig end ############################# - # lollipops +# lollipops ############################# @@ -135,7 +169,7 @@ end ############################# - # ACE +# ACE ############################# """ @@ -152,8 +186,10 @@ function CodingTheory.ACE_spectrum_plot(C::AbstractLDPCCode) # TODO: remove WGLMakie as a default use and only use for interactive plots fig = Figure(); ax = Axis(fig[1, 1], xlabel = "ACE", ylabel = "Occurrences", title = "ACE Spectrum") - sg = SliderGrid(fig[2, 1], (label = "Cycle Length", range = grth:2:2 * grth - 2, - startvalue = 4)) + sg = SliderGrid( + fig[2, 1], + (label = "Cycle Length", range = grth:2:(2*grth-2), startvalue = 4), + ) x_max = maximum(reduce(vcat, vs_ACEs)) y_max = 0 @@ -161,8 +197,8 @@ function CodingTheory.ACE_spectrum_plot(C::AbstractLDPCCode) X_data = Observable(Vector{Int}()) Y_data = Observable(Vector{Int}()) barplot!(ax, X_data, Y_data, strokewidth = 1, xticks = X_data, yticks = Y_data) - for (k, l) in enumerate(grth:2:2 * grth - 2) - + for (k, l) in enumerate(grth:2:(2*grth-2)) + ys = collect(values(counts[k])) y_max = maximum([y_max; ys]) diff --git a/ext/MakieExt/MakieExt.jl b/ext/MakieExt/MakieExt.jl index 791b9e64..f241fe52 100644 --- a/ext/MakieExt/MakieExt.jl +++ b/ext/MakieExt/MakieExt.jl @@ -1,10 +1,29 @@ module MakieExt import CodingTheory, Oscar -import CodingTheory: Tanner_graph_plot, weight_plot, EXIT_chart_plot, degree_distributions_plot, simple_cycle_length_distribution_plot, ACE_spectrum_plot, computation_graph, weight_plot_CSS_X, weight_plot_CSS_Z, weight_plot_CSS, AbstractLinearCode, AbstractLDPCCode, - LDPCEnsemble, AbstractClassicalNoiseChannel, AbstractStabilizerCode, AbstractStabilizerCodeCSS, - simple_cycle_length_distribution, simple_cycle_distribution_by_variable_node, ACE_distribution, - short_cycle_length_distribution, short_cycle_distribution_by_variable_node, girth +import CodingTheory: + Tanner_graph_plot, + weight_plot, + EXIT_chart_plot, + degree_distributions_plot, + simple_cycle_length_distribution_plot, + ACE_spectrum_plot, + computation_graph, + weight_plot_CSS_X, + weight_plot_CSS_Z, + weight_plot_CSS, + AbstractLinearCode, + AbstractLDPCCode, + LDPCEnsemble, + AbstractClassicalNoiseChannel, + AbstractStabilizerCode, + AbstractStabilizerCodeCSS, + simple_cycle_length_distribution, + simple_cycle_distribution_by_variable_node, + ACE_distribution, + short_cycle_length_distribution, + short_cycle_distribution_by_variable_node, + girth # import Makie using Makie, NetworkLayout, CairoMakie, GraphMakie, GLMakie, WGLMakie#, GraphPlot import CairoMakie: @L_str #, Figure, Axis, hidespines!, hidedecorations!, lines!, text! diff --git a/ext/MakieExt/Quantum/weight_dist.jl b/ext/MakieExt/Quantum/weight_dist.jl index 09ca6ef9..ae1ac09f 100644 --- a/ext/MakieExt/Quantum/weight_dist.jl +++ b/ext/MakieExt/Quantum/weight_dist.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # Weight Enumerators +# Weight Enumerators ############################# # """ @@ -21,14 +21,18 @@ # # Note # - Run `using Makie` to activate this extension. # """ -function CodingTheory.weight_plot(S::AbstractStabilizerCode; alg::Symbol = :auto, - type::Symbol = :stabilizer) +function CodingTheory.weight_plot( + S::AbstractStabilizerCode; + alg::Symbol = :auto, + type::Symbol = :stabilizer, +) - type ∈ (:stabilizer, :normalizer, :quotient) || throw(ArgumentError("Unknown value $type for parameter type.")) + type ∈ (:stabilizer, :normalizer, :quotient) || + throw(ArgumentError("Unknown value $type for parameter type.")) wt_dist = weight_distribution(S, alg = alg, type = type, compact = false) x_ticks = findall(x -> x > 0, vec(wt_dist)) .- 1 - y_ticks = [wt_dist[i] for i in 1:length(wt_dist) if !iszero(wt_dist[i])] + y_ticks = [wt_dist[i] for i = 1:length(wt_dist) if !iszero(wt_dist[i])] if type == :stabilizer title_str = "Stabilizer Weight Distribution" elseif type == :normalizer @@ -37,7 +41,7 @@ function CodingTheory.weight_plot(S::AbstractStabilizerCode; alg::Symbol = :auto title_str = "Quotient Weight Distribution" end ismissing(S.d) ? (title = "$title_str - [$(S.n), $(S.k)]";) : - title = "$title_str - [$(S.n), $(S.k), $(S.d)]" + title = "$title_str - [$(S.n), $(S.k), $(S.d)]" fig = Figure() ax = Axis(fig[1, 1], xlabel = "Weight", ylabel = "Number of Terms", title = title) @@ -60,10 +64,14 @@ function CodingTheory.weight_plot_CSS_X(S::AbstractStabilizerCodeCSS; alg::Symbo C = LinearCode(S.X_stabs) wt_dist = weight_distribution(C, alg = alg, compact = false) x_ticks = findall(x -> x > 0, vec(wt_dist)) .- 1 - y_ticks = [wt_dist[i] for i in 1:length(wt_dist) if !iszero(wt_dist[i])] + y_ticks = [wt_dist[i] for i = 1:length(wt_dist) if !iszero(wt_dist[i])] fig = Figure() - ax = Axis(fig[1, 1], xlabel = "Weight", ylabel = "Number of Terms", - title = "X-Weight Distribution") + ax = Axis( + fig[1, 1], + xlabel = "Weight", + ylabel = "Number of Terms", + title = "X-Weight Distribution", + ) barplot!(ax, 0:C.n, wt_dist', bar_width = 1, xticks = x_ticks, yticks = y_ticks) # fig = bar(0:C.n, wt_dist', bar_width = 1, xticks = x_ticks, yticks = y_ticks, # legend = false, xlabel = "Weight", ylabel = "Number of Terms", @@ -84,10 +92,14 @@ function CodingTheory.weight_plot_CSS_Z(S::AbstractStabilizerCodeCSS; alg::Symbo C = LinearCode(S.Z_stabs) wt_dist = weight_distribution(C, alg = alg, compact = false) x_ticks = findall(x -> x > 0, vec(wt_dist)) .- 1 - y_ticks = [wt_dist[i] for i in 1:length(wt_dist) if !iszero(wt_dist[i])] + y_ticks = [wt_dist[i] for i = 1:length(wt_dist) if !iszero(wt_dist[i])] fig = Figure() - ax = Axis(fig[1, 1], xlabel = "Weight", ylabel = "Number of Terms", - title = "Z-Weight Distribution") + ax = Axis( + fig[1, 1], + xlabel = "Weight", + ylabel = "Number of Terms", + title = "Z-Weight Distribution", + ) barplot!(ax, 0:C.n, wt_dist', bar_width = 1, xticks = x_ticks, yticks = y_ticks) # fig = bar(0:C.n, wt_dist', bar_width = 1, xticks = x_ticks, yticks = y_ticks, # legend = false, xlabel = "Weight", ylabel = "Number of Terms", @@ -108,10 +120,14 @@ function CodingTheory.weight_plot_CSS(S::AbstractStabilizerCodeCSS; alg::Symbol C = LinearCode(S.X_stabs) wt_dist = weight_distribution(C, alg = alg, compact = false) x_ticks = findall(x -> x > 0, vec(wt_dist)) .- 1 - y_ticks = [wt_dist[i] for i in 1:length(wt_dist) if !iszero(wt_dist[i])] + y_ticks = [wt_dist[i] for i = 1:length(wt_dist) if !iszero(wt_dist[i])] fig = Figure() - ax1 = Axis(fig[1, 1], xlabel = "Weight", ylabel = "Number of Terms", - title = "X-Weight Distribution") + ax1 = Axis( + fig[1, 1], + xlabel = "Weight", + ylabel = "Number of Terms", + title = "X-Weight Distribution", + ) barplot!(ax1, 0:C.n, wt_dist', bar_width = 1, xticks = x_ticks, yticks = y_ticks) # f_X = bar(0:C.n, wt_dist', bar_width = 1, xticks = x_ticks, yticks = y_ticks, # legend = false, xlabel = "Weight", ylabel = "Number of Terms", @@ -121,9 +137,13 @@ function CodingTheory.weight_plot_CSS(S::AbstractStabilizerCodeCSS; alg::Symbol C = LinearCode(S.Z_stabs) wt_dist = weight_distribution(C, alg = alg, compact = false) x_ticks = findall(x -> x > 0, vec(wt_dist)) .- 1 - y_ticks = [wt_dist[i] for i in 1:length(wt_dist) if !iszero(wt_dist[i])] - ax2 = Axis(fig[1, 2], xlabel = "Weight", ylabel = "Number of Terms", - title = "Z-Weight Distribution") + y_ticks = [wt_dist[i] for i = 1:length(wt_dist) if !iszero(wt_dist[i])] + ax2 = Axis( + fig[1, 2], + xlabel = "Weight", + ylabel = "Number of Terms", + title = "Z-Weight Distribution", + ) barplot!(ax2, 0:C.n, wt_dist', bar_width = 1, xticks = x_ticks, yticks = y_ticks) display(fig) return fig diff --git a/src/Classical/GRS_alternate.jl b/src/Classical/GRS_alternate.jl index 478d7ac5..5f01718f 100644 --- a/src/Classical/GRS_alternate.jl +++ b/src/Classical/GRS_alternate.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -21,20 +21,28 @@ evaluation points `γ`. """ function GeneralizedReedSolomonCode(k::Int, v::Vector{FqFieldElem}, γ::Vector{FqFieldElem}) n = length(v) - 1 <= k <= n || throw(DomainError("The dimension of the code must be between `1` and `n`.")) - n == length(γ) || throw(DomainError("Lengths of scalars and evaluation points must be equal.")) + 1 <= k <= n || + throw(DomainError("The dimension of the code must be between `1` and `n`.")) + n == length(γ) || + throw(DomainError("Lengths of scalars and evaluation points must be equal.")) F = parent(v[1]) - 1 <= n <= Int(order(F)) || throw(DomainError("The length of the code must be between `1` and the order of the field.")) + 1 <= n <= Int(order(F)) || throw( + DomainError( + "The length of the code must be between `1` and the order of the field.", + ), + ) for (i, x) in enumerate(v) iszero(x) && throw(ArgumentError("The elements of `v` must be nonzero.")) - parent(x) == F || throw(ArgumentError("The elements of `v` must be over the same field.")) - parent(γ[i]) == F || throw(ArgumentError("The elements of `γ` must be over the same field as `v`.")) + parent(x) == F || + throw(ArgumentError("The elements of `v` must be over the same field.")) + parent(γ[i]) == F || + throw(ArgumentError("The elements of `γ` must be over the same field as `v`.")) end length(unique(γ)) == n || throw(ArgumentError("The elements of `γ` must be distinct.")) G = zero_matrix(F, k, n) - for c in 1:n - for r in 1:k + for c = 1:n + for r = 1:k G[r, c] = v[c] * γ[c]^(r - 1) end end @@ -42,14 +50,14 @@ function GeneralizedReedSolomonCode(k::Int, v::Vector{FqFieldElem}, γ::Vector{F # evaluation points are the same for the parity check, but scalars are now # w_i = (v_i * \prod(γ_j - γ_i))^-1 # which follows from Lagrange interpolation - w = [F(0) for _ in 1:n] - for i in 1:n - w[i] = (v[i] * prod(γ[j] - γ[i] for j in 1:n if j ≠ i))^-1 + w = [F(0) for _ = 1:n] + for i = 1:n + w[i] = (v[i] * prod(γ[j] - γ[i] for j = 1:n if j ≠ i))^-1 end H = zero_matrix(F, n - k, n) - for c in 1:n - for r in 1:n - k + for c = 1:n + for r = 1:(n-k) H[r, c] = w[c] * γ[c]^(r - 1) end end @@ -58,8 +66,23 @@ function GeneralizedReedSolomonCode(k::Int, v::Vector{FqFieldElem}, γ::Vector{F G_stand, H_stand, P, rnk = _standard_form(G) rnk == k || error("Computed rank not equal to desired input rank") d = n - k + 1 - return GeneralizedReedSolomonCode(F, n, k, d, d, d, v, w, γ, G, H, - G_stand, H_stand, P, missing) + return GeneralizedReedSolomonCode( + F, + n, + k, + d, + d, + d, + v, + w, + γ, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end # using notation of MacWilliams & Sloane, p. 340 @@ -68,7 +91,11 @@ end Return the generalized Reed-Solomon code associated with the Goppa code `C`. """ -GeneralizedReedSolomonCode(C::AbstractGoppaCode) = GeneralizedReedSolomonCode(C.n - degree(C.g), [C.g(C.L[i]) * prod(C.L[j] - C.L[i] for j in 1:C.n if i ≠ j)^(-1) for i in 1:C.n], C.L) +GeneralizedReedSolomonCode(C::AbstractGoppaCode) = GeneralizedReedSolomonCode( + C.n - degree(C.g), + [C.g(C.L[i]) * prod(C.L[j] - C.L[i] for j = 1:C.n if i ≠ j)^(-1) for i = 1:C.n], + C.L, +) # doesn't have it's own struct """ @@ -76,20 +103,41 @@ GeneralizedReedSolomonCode(C::AbstractGoppaCode) = GeneralizedReedSolomonCode(C. Return the alternate code as a subfield subcode of `GRS_k(v, γ)^⟂` over `F`. """ -function AlternateCode(F::CTFieldTypes, k::Int, v::Vector{FqFieldElem}, - γ::Vector{FqFieldElem}) +function AlternateCode( + F::CTFieldTypes, + k::Int, + v::Vector{FqFieldElem}, + γ::Vector{FqFieldElem}, +) E = parent(v[1]) flag, _ = is_subfield(F, E) - flag || throw(ArgumentError("Given field is not a subfield of the base ring of the vectors")) + flag || throw( + ArgumentError("Given field is not a subfield of the base ring of the vectors"), + ) # let this do the rest of the type checking GRS = GeneralizedReedSolomonCode(k, v, γ) GRS = dual(GRS) basis, _ = primitive_basis(E, F) C = subfield_subcode(GRS, F, basis) - return AlternateCode(F, E, C.n, C.k, C.d, C.l_bound, C.u_bound, v, γ, C.G, C.H, C.G_stand, - C.H_stand, C.P_stand, C.weight_enum) + return AlternateCode( + F, + E, + C.n, + C.k, + C.d, + C.l_bound, + C.u_bound, + v, + γ, + C.G, + C.H, + C.G_stand, + C.H_stand, + C.P_stand, + C.weight_enum, + ) end """ @@ -99,7 +147,8 @@ Return the subfield subcode of `C` over `F`. """ function AlternateCode(F::CTFieldTypes, C::GeneralizedReedSolomonCode) flag, _ = is_subfield(F, C.F) - flag || throw(ArgumentError("Given field is not a subfield of the base ring of the code")) + flag || + throw(ArgumentError("Given field is not a subfield of the base ring of the code")) basis, _ = primitive_basis(C.F, F) return subfield_subcode(C, F, basis) @@ -110,7 +159,8 @@ end Return the generalized Reed-Solomon code associated with the alternate code `C`. """ -GeneralizedReedSolomonCode(C::AbstractAlternateCode) = dual(GeneralizedReedSolomonCode(C.k, C.scalars, C.eval_pts)) +GeneralizedReedSolomonCode(C::AbstractAlternateCode) = + dual(GeneralizedReedSolomonCode(C.k, C.scalars, C.eval_pts)) """ GeneralizedSrivastavaCode(F::CTFieldTypes, a::Vector{T}, w::Vector{T}, z::Vector{T}, t::Int) where T <: CTFieldElem @@ -120,8 +170,13 @@ Return the generalized Srivastava code over `F` given `a`, `w`, `z`, and `t`. # Notes - These inputs are defined on page 357 of MacWilliams & Sloane """ -function GeneralizedSrivastavaCode(F::CTFieldTypes, a::Vector{T}, w::Vector{T}, z::Vector{T}, - t::Int) where T <: CTFieldElem +function GeneralizedSrivastavaCode( + F::CTFieldTypes, + a::Vector{T}, + w::Vector{T}, + z::Vector{T}, + t::Int, +) where {T<:CTFieldElem} is_empty(a) && throw(ArgumentError("The input vector `a` cannot be empty.")) is_empty(w) && throw(ArgumentError("The input vector `w` cannot be empty.")) @@ -130,20 +185,37 @@ function GeneralizedSrivastavaCode(F::CTFieldTypes, a::Vector{T}, w::Vector{T}, n = length(a) n == length(z) || throw(ArgumentError("Vectors `a` and `z` must be the same length")) s = length(w) - length(unique([a; w])) == n + s || throw(ArgumentError("Elements of `a` and `w` must be distinct")) + length(unique([a; w])) == n + s || + throw(ArgumentError("Elements of `a` and `w` must be distinct")) any(iszero, z) && throw(DomainError(z, "Elements of `z` must be nonzero")) E = parent(a[1]) - all(parent(pt) == E for pt in a) || throw(ArgumentError("All elements of the input vector `a` must be over the same base ring.")) - all(parent(pt) == E for pt in w) || throw(ArgumentError("All elements of the input vector `w` must be over the same base ring as `a`.")) - all(parent(pt) == E for pt in z) || throw(ArgumentError("All elements of the input vector `z` must be over the same base ring as `a`.")) + all(parent(pt) == E for pt in a) || throw( + ArgumentError( + "All elements of the input vector `a` must be over the same base ring.", + ), + ) + all(parent(pt) == E for pt in w) || throw( + ArgumentError( + "All elements of the input vector `w` must be over the same base ring as `a`.", + ), + ) + all(parent(pt) == E for pt in z) || throw( + ArgumentError( + "All elements of the input vector `z` must be over the same base ring as `a`.", + ), + ) flag, _ = is_subfield(F, E) - flag || throw(ArgumentError("Input field is not a subfield of the base ring of the input veectors")) + flag || throw( + ArgumentError( + "Input field is not a subfield of the base ring of the input veectors", + ), + ) H = zero_matrix(E, s * t, n) - for l in 1:s + for l = 1:s count = 1 - for r in (l - 1) * s + 1:(l - 1) * s + t - for c in 1:n + for r = ((l-1)*s+1):((l-1)*s+t) + for c = 1:n H[r, c] = z[c] * (a[c] - w[l])^(-count) end count += 1 @@ -154,11 +226,31 @@ function GeneralizedSrivastavaCode(F::CTFieldTypes, a::Vector{T}, w::Vector{T}, if typeof(E) === typeof(F) H_exp = transpose(expand_matrix(transpose(H), F, basis)) else - H_exp = change_base_ring(F, transpose(expand_matrix(transpose(H), GF(Int(order(F))), basis))) + H_exp = change_base_ring( + F, + transpose(expand_matrix(transpose(H), GF(Int(order(F))), basis)), + ) end C = LinearCode(H_exp, true) - C2 = GeneralizedSrivastavaCode(F, E, C.n, C.k, C.d, C.l_bound, C.u_bound, a, w, z, t, C.G, C.H, - C.G_stand, C.H_stand, C.P_stand, C.weight_enum) + C2 = GeneralizedSrivastavaCode( + F, + E, + C.n, + C.k, + C.d, + C.l_bound, + C.u_bound, + a, + w, + z, + t, + C.G, + C.H, + C.G_stand, + C.H_stand, + C.P_stand, + C.weight_enum, + ) ismissing(C2.d) && set_distance_lower_bound!(C2, s * t + 1) return C2 @@ -172,11 +264,15 @@ Return the Srivastava code over `F` given `a`, `w`, and `z`. # Notes - These inputs are defined on page 357 of MacWilliams & Sloane """ -SrivastavaCode(F::CTFieldTypes, a::Vector{T}, w::Vector{T}, z::Vector{T}) where T <: CTFieldElem = - GeneralizedSrivastavaCode(F, a, w, z, 1) +SrivastavaCode( + F::CTFieldTypes, + a::Vector{T}, + w::Vector{T}, + z::Vector{T}, +) where {T<:CTFieldElem} = GeneralizedSrivastavaCode(F, a, w, z, 1) ############################# - # getter functions +# getter functions ############################# """ @@ -201,11 +297,11 @@ Return the evaluation points `γ` of the Generalized Reed-Solomon code `C`. evaluation_points(C::GeneralizedReedSolomonCode) = C.eval_pts ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# """ diff --git a/src/Classical/Gabidulin.jl b/src/Classical/Gabidulin.jl index 6e18c807..40577461 100644 --- a/src/Classical/Gabidulin.jl +++ b/src/Classical/Gabidulin.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# # TODO currently untested and have no unit tests @@ -19,30 +19,47 @@ evaluation points `eval_pts` with respect to the subfield `F` of the base ring o # Notes - Distances are reported with respect to the Hamming metric. """ -function GeneralizedGabidulinCode(F::CTFieldTypes, eval_pts::Vector{CTFieldElem}, k::Int, s::Int; parity::Bool = false) +function GeneralizedGabidulinCode( + F::CTFieldTypes, + eval_pts::Vector{CTFieldElem}, + k::Int, + s::Int; + parity::Bool = false, +) - is_empty(eval_pts) && throw(ArgumentError("The input vector `eval_pts` cannot be empty.")) + is_empty(eval_pts) && + throw(ArgumentError("The input vector `eval_pts` cannot be empty.")) is_positive(s) || throw(DomainError(s, "The parameter `s` must be positive.")) E = parent(eval_pts[1]) - all(parent(pt) == E for pt in eval_pts) || throw(ArgumentError("All evaluation points must be over the same base ring.")) + all(parent(pt) == E for pt in eval_pts) || + throw(ArgumentError("All evaluation points must be over the same base ring.")) flag, m = is_extension_field(E, F) - flag || throw(ArgumentError("The input field is not a subfield of the base ring of the evaluation points.")) + flag || throw( + ArgumentError( + "The input field is not a subfield of the base ring of the evaluation points.", + ), + ) n = length(eval_pts) - n ≤ m || throw(ArgumentError("The number of evaluation points must be less than or equal to the degree of the field extension.")) + n ≤ m || throw( + ArgumentError( + "The number of evaluation points must be less than or equal to the degree of the field extension.", + ), + ) 0 < k ≤ n || throw(DomainError(k, "The code dimenion must be `0 < k ≤ n`.")) q = Int(order(F)) B = zero_matrix(E, n, n) - for r in 1:n - for c in 1:n + for r = 1:n + for c = 1:n B[r, c] = eval_pts[c]^(q^(n - 1)) end end - iszero(det(B)) || throw(ArgumentError("The evaluation points must be linearly independent.")) + iszero(det(B)) || + throw(ArgumentError("The evaluation points must be linearly independent.")) G = zero_matrix(E, k, n) - for r in 1:k - for c in 1:n + for r = 1:k + for c = 1:n G[r, c] = eval_pts[c]^(q^(s * (r - 1))) end end @@ -60,8 +77,12 @@ Return the vector representation of the dimension `k` Gabidulin code given the e # Notes - Distances are reported with respect to the Hamming metric. """ -GabidulinCode(F::CTFieldTypes, eval_pts::Vector{CTFieldElem}, k::Int; parity::Bool = false) = - GeneralizedGabidulinCode(F, eval_pts, k, 1, parity = parity) +GabidulinCode( + F::CTFieldTypes, + eval_pts::Vector{CTFieldElem}, + k::Int; + parity::Bool = false, +) = GeneralizedGabidulinCode(F, eval_pts, k, 1, parity = parity) # TODO the dual is also a Gabidulin code, need to figure out those eval points based on these # but that would require making a type for this named code diff --git a/src/Classical/Goppa.jl b/src/Classical/Goppa.jl index 084a155c..a7c6c72c 100644 --- a/src/Classical/Goppa.jl +++ b/src/Classical/Goppa.jl @@ -5,23 +5,39 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# function GoppaCode(F::CTFieldTypes, L::Vector{FqFieldElem}, g::FqPolyRingElem) is_empty(L) && throw(ArgumentError("The input vector `L` cannot be empty.")) E = parent(L[1]) - all(parent(pt) == E for pt in L) || throw(ArgumentError("All elements of the input vector `L` must be over the same base ring.")) - E == base_ring(g) || throw(ArgumentError("Input vector must be over the same base ring as the Goppa polynomial.")) + all(parent(pt) == E for pt in L) || throw( + ArgumentError( + "All elements of the input vector `L` must be over the same base ring.", + ), + ) + E == base_ring(g) || throw( + ArgumentError( + "Input vector must be over the same base ring as the Goppa polynomial.", + ), + ) rts = roots(g) - isempty(L ∩ rts) || throw(ArgumentError("The input vector must not contain any roots of the Goppa polynomial.")) - is_subfield(F, E)[1] || throw(ArgumentError("The input field is not a subfield of the base ring of the polynomial.")) - + isempty(L ∩ rts) || throw( + ArgumentError( + "The input vector must not contain any roots of the Goppa polynomial.", + ), + ) + is_subfield(F, E)[1] || throw( + ArgumentError( + "The input field is not a subfield of the base ring of the polynomial.", + ), + ) + n = length(L) t = degree(g) H = zero_matrix(E, t, n) - for c in 1:n - for r in 1:t + for c = 1:n + for r = 1:t H[r, c] = L[c]^(r - 1) * g(L[c])^(-1) end end @@ -30,7 +46,10 @@ function GoppaCode(F::CTFieldTypes, L::Vector{FqFieldElem}, g::FqPolyRingElem) if typeof(E) === typeof(F) H_exp = transpose(expand_matrix(transpose(H), F, basis)) else - H_exp = change_base_ring(F, transpose(expand_matrix(transpose(H), GF(Int(order(F))), basis))) + H_exp = change_base_ring( + F, + transpose(expand_matrix(transpose(H), GF(Int(order(F))), basis)), + ) end # just call LinearCode constructor here? @@ -44,8 +63,8 @@ function GoppaCode(F::CTFieldTypes, L::Vector{FqFieldElem}, g::FqPolyRingElem) # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(G) G_tr = zero_matrix(base_ring(G), k, nr) - for r in 1:nr - for c in 1:rnk_G + for r = 1:nr + for c = 1:rnk_G !iszero(G[r, c]) && (G_tr[c, r] = G[r, c];) end end @@ -58,15 +77,19 @@ function GoppaCode(F::CTFieldTypes, L::Vector{FqFieldElem}, g::FqPolyRingElem) ub2, _ = _min_wt_row(G_stand) ub = min(ub1, ub2) - C = GoppaCode(F, E, n, k, missing, 1, ub, G, H_exp, G_stand, H_stand, P, - missing, L, g) + C = GoppaCode(F, E, n, k, missing, 1, ub, G, H_exp, G_stand, H_stand, P, missing, L, g) if BigInt(order(base_ring(G)))^min(k, n - k) <= 1.5e5 C.weight_enum = if 2k <= n _weight_enumerator_BF(C.G_stand) else MacWilliams_identity(dual(C), _weight_enumerator_BF(C.H_stand)) end - d = minimum(filter(is_positive, first.(exponent_vectors(CWE_to_HWE(C.weight_enum).polynomial)))) + d = minimum( + filter( + is_positive, + first.(exponent_vectors(CWE_to_HWE(C.weight_enum).polynomial)), + ), + ) set_minimum_distance!(C, d) else l_bound = t + 1 @@ -85,7 +108,7 @@ function GoppaCode(F::CTFieldTypes, L::Vector{FqFieldElem}, g::FqPolyRingElem) end ############################# - # getter functions +# getter functions ############################# """ @@ -103,11 +126,11 @@ Return the field over which the Goppa polynomial is defined. extension_field(C::AbstractGoppaCode) = C.E ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# """ diff --git a/src/Classical/MatrixProductCode.jl b/src/Classical/MatrixProductCode.jl index c8e0ed90..7de00717 100644 --- a/src/Classical/MatrixProductCode.jl +++ b/src/Classical/MatrixProductCode.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# # TODO: need to make sure codes are not overcomplete @@ -18,30 +18,33 @@ function MatrixProductCode(C::Vector{AbstractLinearCode}, A::CTMatrixTypes) isempty(C) && throw(ArgumentError("Vector of linear codes cannot be empty.")) iszero(A) && throw(ArgumentError("Matrix A cannot be zero.")) s, l = size(A) - s == length(C) || throw(ArgumentError("Number of rows of A must be equal to the number of codes.")) + s == length(C) || + throw(ArgumentError("Number of rows of A must be equal to the number of codes.")) F = C[1].F n = C[1].n - for i in 2:s + for i = 2:s F == C[i].F || throw(ArgumentError("All codes must have the same base ring.")) n == C[i].n || throw(ArgumentError("All codes must have the same length.")) end - F == base_ring(A) || throw(ArgumentError("Codes and matrix must have the same base ring.")) + F == base_ring(A) || + throw(ArgumentError("Codes and matrix must have the same base ring.")) # H formula holds in special case only - G = zero_matrix(F, sum([C[i].k for i in 1:s], l * n)) + G = zero_matrix(F, sum([C[i].k for i = 1:s], l * n)) # H = zero_matrix(F, sum([nrows(C[i].H) for i in 1:s], l * n)) curr = 1 # currH = 1 # need to do in this row/column order - for r in 1:s - for c in 1:l - G[curr:curr + C[r].k, 1 + (r - 1) * n:r * n] = A[r, c] * generator_matrix(C[r], true) + for r = 1:s + for c = 1:l + G[curr:(curr+C[r].k), (1+(r-1)*n):(r*n)] = + A[r, c] * generator_matrix(C[r], true) # H[currH:currH + nrows(C[r].H), 1 + (r - 1) * n:r * n] = A[r, c] * paritycheckmatrix(C[r]) end curr += C[r].k # currH += nrows(C[r].H) end - + G_stand, H_stand, P, k = _standard_form(G) if ismissing(P) _, H = right_kernel(G) @@ -54,20 +57,34 @@ function MatrixProductCode(C::Vector{AbstractLinearCode}, A::CTMatrixTypes) ub1, _ = _min_wt_row(G) ub2, _ = _min_wt_row(G_stand) ub = minimum([ub1, ub2]) - return MatrixProductCode(F, n, k, 1, ub, missing, G, H, G_stand, - H_stand, P, missing, C, A) + return MatrixProductCode( + F, + n, + k, + 1, + ub, + missing, + G, + H, + G_stand, + H_stand, + P, + missing, + C, + A, + ) end ############################# - # getter functions +# getter functions ############################# # TODO: why are there no getter functions for this? C, A inputs? ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# diff --git a/src/Classical/McEliece.jl b/src/Classical/McEliece.jl index 51dfaced..17ddf6d6 100644 --- a/src/Classical/McEliece.jl +++ b/src/Classical/McEliece.jl @@ -1,7 +1,13 @@ -function McEliece_attack(G::CTMatrix, w::CTMatrix, t::Int; max_iters::Int = 10000, verbose::Bool = false) +function McEliece_attack( + G::CTMatrix, + w::CTMatrix, + t::Int; + max_iters::Int = 10000, + verbose::Bool = false, +) # check 0 matrix, 0 dimensions @@ -18,12 +24,12 @@ function McEliece_attack(G::CTMatrix, w::CTMatrix, t::Int; max_iters::Int = 1000 thread_load = Int(floor(max_iters / num_thrds)) remaining = max_iters - thread_load * num_thrds flag = Threads.Atomic{Bool}(true) - answers = [zeros(Int, 1, n) for _ in 1:num_thrds] - which_ans = [false for _ in 1:num_thrds] - perms = [collect(1:n) for _ in 1:num_thrds] + answers = [zeros(Int, 1, n) for _ = 1:num_thrds] + which_ans = [false for _ = 1:num_thrds] + perms = [collect(1:n) for _ = 1:num_thrds] verbose && (prog_meter = Progress(max_iters);) - Threads.@threads for th in 1:num_thrds + Threads.@threads for th = 1:num_thrds G_loc = similar(G2) σ_loc = shuffle(1:n) _col_permutation!(G2, G_loc, σ_loc) @@ -37,15 +43,15 @@ function McEliece_attack(G::CTMatrix, w::CTMatrix, t::Int; max_iters::Int = 1000 w_loc = similar(w2) w_loc = _col_permutation!(w2, w_loc, σ_loc) - for _ in 1:(thread_load + (th <= remaining ? 1 : 0)) + for _ = 1:(thread_load+(th<=remaining ? 1 : 0)) if flag[] wt = 0 - @inbounds for j in k + 1:n + @inbounds for j = (k+1):n isodd(w_loc[i, j]) && (wt += 1;) end if wt == t which_ans[th] = true - answers[th][1, k + 1:n] .= w_loc[1, k + 1:n] + answers[th][1, (k+1):n] .= w_loc[1, (k+1):n] answers[th][1, invperm(σ_loc)] perms[th] .= σ_loc Threads.atomic_cas!(flag, true, false) @@ -64,13 +70,20 @@ function McEliece_attack(G::CTMatrix, w::CTMatrix, t::Int; max_iters::Int = 1000 end end verbose && finish!(prog_meter) - + i = findfirst(which_ans, true) # cheaper to not return the matrix here return matrix(base_ring(G), answers[i]), perms[i] end -function Lee_Brickell_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int; max_iters::Int = 10000, verbose::Bool = false) +function Lee_Brickell_attack( + G::CTMatrix, + w::CTMatrix, + t::Int, + p::Int; + max_iters::Int = 10000, + verbose::Bool = false, +) # check 0 matrix, 0 dimensions # G - gen matrix @@ -86,13 +99,13 @@ function Lee_Brickell_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int; max_iters thread_load = Int(floor(max_iters / num_thrds)) remaining = max_iters - thread_load * num_thrds flag = Threads.Atomic{Bool}(true) - answers = [zeros(Int, 1, n) for _ in 1:num_thrds] - which_ans = [false for _ in 1:num_thrds] - perms = [collect(1:n) for _ in 1:num_thrds] + answers = [zeros(Int, 1, n) for _ = 1:num_thrds] + which_ans = [false for _ = 1:num_thrds] + perms = [collect(1:n) for _ = 1:num_thrds] # update size for p and size of GrayCode verbose && (prog_meter = Progress(max_iters);) - Threads.@threads for th in 1:num_thrds + Threads.@threads for th = 1:num_thrds G_loc = similar(G2) σ_loc = shuffle(1:n) _col_permutation!(G2, G_loc, σ_loc) @@ -106,28 +119,28 @@ function Lee_Brickell_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int; max_iters w_loc = similar(w2) w_loc = _col_permutation!(w2, w_loc, σ_loc) q_A = zeros(Int, 1, n - k) - for _ in 1:(thread_load + (th <= remaining ? 1 : 0)) + for _ = 1:(thread_load+(th<=remaining ? 1 : 0)) if flag[] wt = 0 - @inbounds for j in k + 1:n + @inbounds for j = (k+1):n isodd(w_loc[i, j]) && (wt += 1;) end if wt ≤ t which_ans[th] = true - answers[th][1, k + 1:n] .= w_loc[1, k + 1:n] + answers[th][1, (k+1):n] .= w_loc[1, (k+1):n] answers[th][1, invperm(σ_loc)] perms[th] .= σ_loc Threads.atomic_cas!(flag, true, false) break end - for r in 1:p + for r = 1:p if flag[] for m in GrayCode(k, r) if flag[] - LinearAlgebra.mul!(q_A, m, view(G_loc, :, k + 1:n)) - q_A .+= w_loc[1, k + 1:n] + LinearAlgebra.mul!(q_A, m, view(G_loc, :, (k+1):n)) + q_A .+= w_loc[1, (k+1):n] wt = 0 @inbounds for j in axes(q_A, 2) isodd(q_A[1, j]) && (wt += 1;) @@ -136,7 +149,7 @@ function Lee_Brickell_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int; max_iters if wt ≤ t - r which_ans[th] = true answers[th][1, 1:k] .= m - answers[th][1, k + 1:n] .= q_A + answers[th][1, (k+1):n] .= q_A answers[th][1, invperm(σ_loc)] perms[th] .= σ_loc Threads.atomic_cas!(flag, true, false) @@ -167,13 +180,21 @@ function Lee_Brickell_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int; max_iters end end verbose && finish!(prog_meter) - + i = findfirst(which_ans, true) # cheaper to not return the matrix here return matrix(base_ring(G), answers[i]), perms[i] end -function Leon_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::Int; max_iters::Int = 10000, verbose::Bool = false) +function Leon_attack( + G::CTMatrix, + w::CTMatrix, + t::Int, + p::Int, + l::Int; + max_iters::Int = 10000, + verbose::Bool = false, +) # G - gen matrix # w - received vector @@ -188,13 +209,13 @@ function Leon_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::Int; max_iters thread_load = Int(floor(max_iters / num_thrds)) remaining = max_iters - thread_load * num_thrds flag = Threads.Atomic{Bool}(true) - answers = [zeros(Int, 1, n) for _ in 1:num_thrds] - which_ans = [false for _ in 1:num_thrds] - perms = [collect(1:n) for _ in 1:num_thrds] + answers = [zeros(Int, 1, n) for _ = 1:num_thrds] + which_ans = [false for _ = 1:num_thrds] + perms = [collect(1:n) for _ = 1:num_thrds] # update size for p and size of GrayCode verbose && (prog_meter = Progress(max_iters);) - Threads.@threads for th in 1:num_thrds + Threads.@threads for th = 1:num_thrds G_loc = similar(G2) σ_loc = shuffle(1:n) _col_permutation!(G2, G_loc, σ_loc) @@ -209,36 +230,36 @@ function Leon_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::Int; max_iters w_loc = _col_permutation!(w2, w_loc, σ_loc) q_P = zeros(Int, 1, l) q_B = zeros(Int, 1, n - k - l) - for _ in 1:(thread_load + (th <= remaining ? 1 : 0)) + for _ = 1:(thread_load+(th<=remaining ? 1 : 0)) if flag[] wt = 0 - @inbounds for j in k + 1:n + @inbounds for j = (k+1):n isodd(w_loc[i, j]) && (wt += 1;) end if wt ≤ t which_ans[th] = true - answers[th][1, k + 1:n] .= w_loc[1, k + 1:n] + answers[th][1, (k+1):n] .= w_loc[1, (k+1):n] answers[th][1, invperm(σ_loc)] perms[th] .= σ_loc Threads.atomic_cas!(flag, true, false) break end - for r in 1:p + for r = 1:p if flag[] for m in GrayCode(k, r) if flag[] - LinearAlgebra.mul!(q_P, m, view(G_loc, :, k + 1:k + l)) - q_P .+= w_loc[1, k + 1:k + l] + LinearAlgebra.mul!(q_P, m, view(G_loc, :, (k+1):(k+l))) + q_P .+= w_loc[1, (k+1):(k+l)] wt_P = 0 @inbounds for j in axes(q_P, 2) isodd(q_P[1, j]) && (wt_P += 1;) end if wt_P ≤ p - r - LinearAlgebra.mul!(q_B, m, view(G_loc, :, k + l + 1:n)) - q_B .+= w_loc[1, k + l + 1:n] + LinearAlgebra.mul!(q_B, m, view(G_loc, :, (k+l+1):n)) + q_B .+= w_loc[1, (k+l+1):n] wt_B = 0 @inbounds for j in axes(q_B, 2) isodd(q_B[1, j]) && (wt_B += 1;) @@ -247,8 +268,8 @@ function Leon_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::Int; max_iters if wt_B ≤ t - r - wt_p which_ans[th] = true answers[th][1, 1:k] .= m - answers[th][1, k + 1:k + l] .= q_P - answers[th][1, k + l + 1:n] .= q_B + answers[th][1, (k+1):(k+l)] .= q_P + answers[th][1, (k+l+1):n] .= q_B answers[th][1, invperm(σ_loc)] perms[th] .= σ_loc Threads.atomic_cas!(flag, true, false) @@ -280,7 +301,7 @@ function Leon_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::Int; max_iters end end verbose && finish!(prog_meter) - + i = findfirst(which_ans, true) # cheaper to not return the matrix here return matrix(base_ring(G), answers[i]), perms[i] @@ -288,8 +309,17 @@ end # my other is called Sterns_attack so won't mess it up and this file isn't imported yet -function generalized_Stern_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::Int, s::Int; max_iters::Int = 10000, verbose::Bool = false) - +function generalized_Stern_attack( + G::CTMatrix, + w::CTMatrix, + t::Int, + p::Int, + l::Int, + s::Int; + max_iters::Int = 10000, + verbose::Bool = false, +) + n = ncols(G) G2 = _Flint_matrix_to_Julia_T_matrix(G2, UInt8) w2 = _Flint_matrix_to_Julia_T_matrix(w, UInt8) @@ -299,13 +329,13 @@ function generalized_Stern_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::I thread_load = Int(floor(max_iters / num_thrds)) remaining = max_iters - thread_load * num_thrds flag = Threads.Atomic{Bool}(true) - answers = [zeros(Int, 1, n) for _ in 1:num_thrds] - which_ans = [false for _ in 1:num_thrds] - perms = [collect(1:n) for _ in 1:num_thrds] + answers = [zeros(Int, 1, n) for _ = 1:num_thrds] + which_ans = [false for _ = 1:num_thrds] + perms = [collect(1:n) for _ = 1:num_thrds] # update size for p and size of GrayCode verbose && (prog_meter = Progress(max_iters);) - Threads.@threads for th in 1:num_thrds + Threads.@threads for th = 1:num_thrds G_loc = similar(G2) σ_loc = shuffle(1:n) _col_permutation!(G2, G_loc, σ_loc) @@ -328,23 +358,23 @@ function generalized_Stern_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::I # first check none of these submatrices are 0 - Xis = [Dict{Matrix{UInt8}, Vector{Matrix{UInt8}}}() for _ in 1:s - 1] + Xis = [Dict{Matrix{UInt8},Vector{Matrix{UInt8}}}() for _ = 1:(s-1)] size_guess = binomial(BigInt(nr_Xi), p) - for i in 1:s - 1 + for i = 1:(s-1) sizehint!(Xis[i], size_guess) end - for _ in 1:(thread_load + (th <= remaining ? 1 : 0)) + for _ = 1:(thread_load+(th<=remaining ? 1 : 0)) if flag[] # does this check and if statement still hold here? wt = 0 - @inbounds for j in k + 1:n + @inbounds for j = (k+1):n isodd(w_loc[i, j]) && (wt += 1;) end if wt ≤ t which_ans[th] = true - answers[th][1, k + 1:n] .= w_loc[1, k + 1:n] + answers[th][1, (k+1):n] .= w_loc[1, (k+1):n] answers[th][1, invperm(σ_loc)] perms[th] .= σ_loc Threads.atomic_cas!(flag, true, false) @@ -352,9 +382,13 @@ function generalized_Stern_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::I end for m in GrayCode(nr_Xi, p) - for i in 1:s - 1 - LinearAlgebra.mul!(q_i, m, view(G_loc, (i - 1) * nr_Xi + 1:i * nr_Xi, k + 1:k + l)) - q_i .+= w_loc[1, k + 1:k + l] + for i = 1:(s-1) + LinearAlgebra.mul!( + q_i, + m, + view(G_loc, ((i-1)*nr_Xi+1):(i*nr_Xi), (k+1):(k+l)), + ) + q_i .+= w_loc[1, (k+1):(k+l)] if haskey(Xis[i], q_i) push(Xis[i][q_i], m) else @@ -364,29 +398,40 @@ function generalized_Stern_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::I end # allocates a pointer, don't ask for dynamically in a loop - keys_Xis = [keys(Xi_s) for _ in 1:length(Xis)] - vals_Xis = [values(Xi_s) for _ in 1:length(Xis)] + keys_Xis = [keys(Xi_s) for _ = 1:length(Xis)] + vals_Xis = [values(Xi_s) for _ = 1:length(Xis)] for m in GrayCode(nr_Y, p) if flag[] # q_i now representing q_Y - LinearAlgebra.mul!(q_i, m, view(G_loc, k - nr_Y + 1:k, k + 1:k - + l)) - q_i .+= w_loc[1, k + 1:k + l] - for iter_q in Nemo.AbstractAlgebra.ProductIterator([1:length(Xis) for _ in 1:s - 1], inplace = true) + LinearAlgebra.mul!(q_i, m, view(G_loc, (k-nr_Y+1):k, (k+1):(k+l))) + q_i .+= w_loc[1, (k+1):(k+l)] + for iter_q in Nemo.AbstractAlgebra.ProductIterator( + [1:length(Xis) for _ = 1:(s-1)], + inplace = true, + ) if flag[] q_sum .= keys_Xis[1][iter_q[1]] - for i in 2:length(iter_q) + for i = 2:length(iter_q) q_sum .+= keys_Xis[i][iter_q[i]] end if q_sum == q_i - for iter_m in Nemo.AbstractAlgebra.ProductIterator([1:length(vals_Xis[i][iter_q[i]] for i in 1:length(Xis))]) + for iter_m in Nemo.AbstractAlgebra.ProductIterator([ + 1:length( + vals_Xis[i][iter_q[i]] for i = 1:length(Xis) + ), + ]) # make m_B, q_B - for i in 1:s - 1 - m_B[1, (i - i) * nr_Xi + 1:i * nr_Xi] .= vals_Xis[i][iter[i]][iter_m[i]] + for i = 1:(s-1) + m_B[1, ((i-i)*nr_Xi+1):(i*nr_Xi)] .= + vals_Xis[i][iter[i]][iter_m[i]] end - LinearAlgebra.mul!(q_B, m_B, view(G_loc, :, k + l + 1:n)) - q_B .+= w_loc[1, k + l + 1:n] + LinearAlgebra.mul!( + q_B, + m_B, + view(G_loc, :, (k+l+1):n), + ) + q_B .+= w_loc[1, (k+l+1):n] wt_B = 0 @inbounds for j in axes(q_B, 2) isodd(q_B[1, j]) && (wt_B += 1;) @@ -395,7 +440,7 @@ function generalized_Stern_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::I if wt_B ≤ t - 2p which_ans[th] = true answers[th][1, 1:k] .= m_B - answers[th][1, k + l + 1:n] .= q_B + answers[th][1, (k+l+1):n] .= q_B answers[th][1, invperm(σ_loc)] perms[th] .= σ_loc Threads.atomic_cas!(flag, true, false) @@ -433,7 +478,16 @@ function generalized_Stern_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::I # cheaper to not return the matrix here return matrix(base_ring(G), answers[i]), perms[i] end -Stern_attack(G::CTMatrix, w::CTMatrix, t::Int, p::Int, l::Int, s::Int; max_iters::Int = 10000, verbose::Bool = false) = generalized_Stern_attack(G, w, t, p, l, 1, max_iters = max_iters, verbose = verbose) +Stern_attack( + G::CTMatrix, + w::CTMatrix, + t::Int, + p::Int, + l::Int, + s::Int; + max_iters::Int = 10000, + verbose::Bool = false, +) = generalized_Stern_attack(G, w, t, p, l, 1, max_iters = max_iters, verbose = verbose) function Canteaut_Chabaud_attack() diff --git a/src/Classical/ReedMuller.jl b/src/Classical/ReedMuller.jl index ef6321f4..abffa696 100644 --- a/src/Classical/ReedMuller.jl +++ b/src/Classical/ReedMuller.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# # """ @@ -17,8 +17,10 @@ # * If `alt` is `true`, the identity is used for the generator matrix for ``\\mathcal{RM}(1, 1)``, as in common in some sources. # Otherwise, `[1 1; 0 1]` is used, as is common in other sources. # """ -function _Reed_Muller_generator_matrix(r::Int, m::Int, alt::Bool=false) - (0 ≤ r ≤ m) || throw(DomainError("Reed-Muller codes require 0 ≤ r ≤ m, received r = $r and m = $m.")) +function _Reed_Muller_generator_matrix(r::Int, m::Int, alt::Bool = false) + (0 ≤ r ≤ m) || throw( + DomainError("Reed-Muller codes require 0 ≤ r ≤ m, received r = $r and m = $m."), + ) F = Oscar.Nemo.Native.GF(2) if r == 1 && m == 1 && !alt @@ -30,7 +32,10 @@ function _Reed_Muller_generator_matrix(r::Int, m::Int, alt::Bool=false) else Grm1 = _Reed_Muller_generator_matrix(r, m - 1, alt) Gr1m1 = _Reed_Muller_generator_matrix(r - 1, m - 1, alt) - return vcat(hcat(Grm1, Grm1), hcat(zero_matrix(F, nrows(Gr1m1), ncols(Gr1m1)), Gr1m1)) + return vcat( + hcat(Grm1, Grm1), + hcat(zero_matrix(F, nrows(Gr1m1), ncols(Gr1m1)), Gr1m1), + ) end end @@ -43,34 +48,75 @@ Return the ``\\mathcal{RM}(r, m)`` Reed-Muller code. * If `alt` is `true`, the identity is used for the generator matrix for ``\\mathcal{RM}(1, 1)``, as in common in some sources. Otherwise, `[1 1; 0 1]` is used, as is common in other sources. """ -function ReedMullerCode(r::Int, m::Int, alt::Bool=false) - (0 ≤ r < m) || throw(DomainError("Reed-Muller codes require 0 ≤ r < m, received r = $r and m = $m.")) - m < 64 || throw(DomainError("This Reed-Muller code requires the implmentation of BigInts. Change if necessary.")) +function ReedMullerCode(r::Int, m::Int, alt::Bool = false) + (0 ≤ r < m) || throw( + DomainError("Reed-Muller codes require 0 ≤ r < m, received r = $r and m = $m."), + ) + m < 64 || throw( + DomainError( + "This Reed-Muller code requires the implmentation of BigInts. Change if necessary.", + ), + ) G = _Reed_Muller_generator_matrix(r, m, alt) H = _Reed_Muller_generator_matrix(m - r - 1, m, alt) G_stand, H_stand, P, rnk = _standard_form(G) # verify - ncols(G) == 2^m || error("Generator matrix computed in ReedMuller has the wrong number of columns; received: $(ncols(G)), expected: $(BigInt(2)^m).") - k = sum([binomial(m, i) for i in 0:r]) - nrows(G) == k || error("Generator matrix computed in ReedMuller has the wrong number of rows; received: $(nrows(G)), expected: $k.") + ncols(G) == 2^m || error( + "Generator matrix computed in ReedMuller has the wrong number of columns; received: $(ncols(G)), expected: $(BigInt(2)^m).", + ) + k = sum([binomial(m, i) for i = 0:r]) + nrows(G) == k || error( + "Generator matrix computed in ReedMuller has the wrong number of rows; received: $(nrows(G)), expected: $k.", + ) size(H) == (2^m - k, k) && (H = transpose(H);) d = 2^(m - r) if r == 1 R, vars = polynomial_ring(Nemo.ZZ, 2) - poly = vars[1]^(2^m) + (2^(m + 1) - 2) * vars[1]^(2^m - 2^(m - 1))*vars[2]^(2^(m - 1)) + vars[2]^(2^m) - return ReedMullerCode(base_ring(G), ncols(G), nrows(G), d, d, d, r, m, G, - H, G_stand, H_stand, P, WeightEnumerator(poly, :complete)) + poly = + vars[1]^(2^m) + + (2^(m + 1) - 2) * vars[1]^(2^m - 2^(m - 1)) * vars[2]^(2^(m - 1)) + + vars[2]^(2^m) + return ReedMullerCode( + base_ring(G), + ncols(G), + nrows(G), + d, + d, + d, + r, + m, + G, + H, + G_stand, + H_stand, + P, + WeightEnumerator(poly, :complete), + ) end - return ReedMullerCode(base_ring(G), ncols(G), nrows(G), d, d, d, r, m, G, - H, G_stand, H_stand, P, missing) + return ReedMullerCode( + base_ring(G), + ncols(G), + nrows(G), + d, + d, + d, + r, + m, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end ############################# - # getter functions +# getter functions ############################# """ @@ -92,10 +138,9 @@ number_of_variables(C::ReedMullerCode) = C.m RM_m(C::ReedMullerCode) = C.m ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# - diff --git a/src/Classical/Tanner.jl b/src/Classical/Tanner.jl index 3776c6ef..ea3fdab4 100644 --- a/src/Classical/Tanner.jl +++ b/src/Classical/Tanner.jl @@ -22,14 +22,14 @@ Return the `SimpleGraph` object repesenting the Tanner graph of the parity-check matrix `H` along with the indices of the left and right vertices representing the bits and parity checks, respectively. """ -function Tanner_graph(H::Union{CTMatrixTypes, Matrix{Int}}) +function Tanner_graph(H::Union{CTMatrixTypes,Matrix{Int}}) typeof(H) <: CTMatrixTypes ? (I = _Flint_matrix_to_Julia_int_matrix(H);) : (I = H;) nr, nc = size(I) B = vcat(hcat(zeros(Int, nc, nc), transpose(I)), hcat(I, zeros(Int, nr, nr))) G = SimpleGraph(B) # lhs - bits # rhs - parity checks - return G, collect(1:nr), collect(nr + 1:nr + nc) + return G, collect(1:nr), collect((nr+1):(nr+nc)) end """ @@ -70,48 +70,61 @@ Tanner_graph(C::AbstractLinearCode) = Tanner_graph(parity_check_matrix(C)) Return the Tanner code obtained by applying the local code `C` to the edges of the graph with edge-vertex incidence matrix `EVI`. """ -function Tanner_code(EVI::SparseMatrixCSC{Int, Int}, C::AbstractLinearCode) +function Tanner_code(EVI::SparseMatrixCSC{Int,Int}, C::AbstractLinearCode) num_E = EVI.m # rows num_V = EVI.n # columns - num_E > num_V || throw(ArgumentError("The number of rows (edges) must be larger than the number of columns (vertices).")) - nnz(EVI) % num_E == 0 || throw(ArgumentError("The number of vertices does not divide the number of non-zero entries, cannot be regular.")) - nnz(EVI) % (C.n - C.k) == 0 || throw(ArgumentError("The dimension of the local code does not divide the number of non-zero entries.")) - + num_E > num_V || throw( + ArgumentError( + "The number of rows (edges) must be larger than the number of columns (vertices).", + ), + ) + nnz(EVI) % num_E == 0 || throw( + ArgumentError( + "The number of vertices does not divide the number of non-zero entries, cannot be regular.", + ), + ) + nnz(EVI) % (C.n - C.k) == 0 || throw( + ArgumentError( + "The dimension of the local code does not divide the number of non-zero entries.", + ), + ) + # pre-store all the information about H_loc # this could be a bit redundant if H_loc is sparse # H_loc = _Flint_matrix_to_Julia_int_matrix(parity_check_matrix(C)) H_loc = parity_check_matrix(C) nr_H_loc, nc_H_loc = size(H_loc) - H_loc_ind = Vector{Vector{Tuple{typeof(H_loc[1, 1]), Int}}}() - for r in 1:nr_H_loc - temp = Vector{Tuple{typeof(H_loc[1, 1]), Int}}() - for c in 1:nc_H_loc + H_loc_ind = Vector{Vector{Tuple{typeof(H_loc[1, 1]),Int}}}() + for r = 1:nr_H_loc + temp = Vector{Tuple{typeof(H_loc[1, 1]),Int}}() + for c = 1:nc_H_loc H_loc[r, c] != 0 && (push!(temp, (H_loc[r, c], c))) end push!(H_loc_ind, temp) end H_rows_I_tr_loc = ones(Int, 1, nr_H_loc) - H_loc_ind_lens = [length(H_loc_ind[i]) for i in 1:nr_H_loc] + H_loc_ind_lens = [length(H_loc_ind[i]) for i = 1:nr_H_loc] curr_row = 0 # H = zeros(Int, num_V * nr_H_loc, num_E) H = zero_matrix(C.F, num_V * nr_H_loc, num_E) # look at every edge attached to a vertex, so check every row for a fixed column - for c in 1:num_V + for c = 1:num_V count = 0 # since these graphs are regular this is always the same gap and could be exploited to save a few clock cycles - for r in EVI.colptr[c]:EVI.colptr[c + 1] - 1 + for r = EVI.colptr[c]:(EVI.colptr[c+1]-1) count += 1 # this is the count-th edge, is the count-th entry of any row of H_loc # this loop handles all rows of H_loc in a single pass # doesn't actually do anything here because there's the if statement I think - @simd for i in 1:nr_H_loc + @simd for i = 1:nr_H_loc # instead of looping through a col of H_loc every time # H_loc_ind stores the next column index and since this is sorted # if the 2nd element of H_loc_ind at this index is count then # there is a 1 there, otherwise a zero since it wasn't stored - if H_loc_ind_lens[i] >= H_rows_I_tr_loc[i] && H_loc_ind[i][H_rows_I_tr_loc[i]][2] == count - H[curr_row + i, EVI.rowval[r]] = H_loc_ind[i][H_rows_I_tr_loc[i]][1] + if H_loc_ind_lens[i] >= H_rows_I_tr_loc[i] && + H_loc_ind[i][H_rows_I_tr_loc[i]][2] == count + H[curr_row+i, EVI.rowval[r]] = H_loc_ind[i][H_rows_I_tr_loc[i]][1] H_rows_I_tr_loc[i] += 1 end end @@ -120,7 +133,7 @@ function Tanner_code(EVI::SparseMatrixCSC{Int, Int}, C::AbstractLinearCode) H_rows_I_tr_loc[:] .= 1 end return LinearCode(H, true) -end +end """ Tanner_code(G::SimpleGraph{Int}, C::AbstractLinearCode) @@ -129,7 +142,11 @@ Return the Tanner code obtained by applying the local code `C` to the edges of ` """ function Tanner_code(G::SimpleGraph{Int}, C::AbstractLinearCode) isregular(G) || throw(ArgumentError("Graph must be regular.")) - length(G.fadjlist[1]) == C.n || throw(ArgumentError("The degree of the verties must be equal to the length of the local code.")) + length(G.fadjlist[1]) == C.n || throw( + ArgumentError( + "The degree of the verties must be equal to the length of the local code.", + ), + ) # can use G.fadjlist directly? # would need to make sure we don't use the same edge twice return Tanner_code(sparse(transpose(incidence_matrix(G))), C) @@ -141,19 +158,25 @@ end Return the Tanner code obtained by applying the local code `C` to the vertices `right` in the bipartition of `G` and treating the vertices of `left` as bits. """ -function Tanner_code(G::SimpleGraph{Int}, left::Vector{Int}, right::Vector{Int}, C::AbstractLinearCode) +function Tanner_code( + G::SimpleGraph{Int}, + left::Vector{Int}, + right::Vector{Int}, + C::AbstractLinearCode, +) # remove this to allow for overcomplete matrices like quasi-cyclic codes? # length(left) > length(right) || throw(ArgumentError("The size of `left` (bits) must be greater than the size of `right` (parity checks).")) - is_valid_bipartition(G, left, right) || throw(ArgumentError("The input vectors are not a valid partition for the graph.")) - + is_valid_bipartition(G, left, right) || + throw(ArgumentError("The input vectors are not a valid partition for the graph.")) + # pre-store all the information about H_loc # this could be a bit redundant if H_loc is sparse H_loc = parity_check_matrix(C) nr_H_loc, nc_H_loc = size(H_loc) - H_loc_ind = Vector{Vector{Tuple{typeof(H_loc[1, 1]), Int}}}() - for r in 1:nr_H_loc - temp = Vector{Tuple{typeof(H_loc[1, 1]), Int}}() - for c in 1:nc_H_loc + H_loc_ind = Vector{Vector{Tuple{typeof(H_loc[1, 1]),Int}}}() + for r = 1:nr_H_loc + temp = Vector{Tuple{typeof(H_loc[1, 1]),Int}}() + for c = 1:nc_H_loc H_loc[r, c] != 0 && (push!(temp, (H_loc[r, c], c))) end push!(H_loc_ind, temp) @@ -165,9 +188,9 @@ function Tanner_code(G::SimpleGraph{Int}, left::Vector{Int}, right::Vector{Int}, curr_row = 0 H = zero_matrix(C.F, length(right) * nr_H_loc, length(left)) for rv in right - for r in 1:nr_H_loc + for r = 1:nr_H_loc @simd for c in H_loc_ind[r] - H[curr_row + r, edge_map[G.fadjlist[rv][c[2]]]] = c[1] + H[curr_row+r, edge_map[G.fadjlist[rv][c[2]]]] = c[1] end end curr_row += nr_H_loc @@ -182,19 +205,27 @@ end Return the Tanner code obtained by applying the local code `C1` to the vertices `right1` and the local code `C2` to the vertices `right2` in the bipartition of `G` and treating the vertices of `left` as bits. """ -function Tanner_code(G::SimpleGraph{Int}, left::Vector{Int}, right1::Vector{Int}, right2::Vector{Int}, C1::AbstractLinearCode, C2::AbstractLinearCode) +function Tanner_code( + G::SimpleGraph{Int}, + left::Vector{Int}, + right1::Vector{Int}, + right2::Vector{Int}, + C1::AbstractLinearCode, + C2::AbstractLinearCode, +) # remove this to allow for overcomplete matrices like quasi-cyclic codes? # length(left) > length(right) || throw(ArgumentError("The size of `left` (bits) must be greater than the size of `right` (parity checks).")) - is_valid_bipartition(G, left, right1 ∪ right2) || throw(ArgumentError("The input vectors are not a valid partition for the graph.")) - + is_valid_bipartition(G, left, right1 ∪ right2) || + throw(ArgumentError("The input vectors are not a valid partition for the graph.")) + # pre-store all the information about H_loc # this could be a bit redundant if H_loc is sparse H_loc = parity_check_matrix(C1) nr_H_loc, nc_H_loc = size(H_loc) - H_loc_ind = Vector{Vector{Tuple{typeof(H_loc[1, 1]), Int}}}() - for r in 1:nr_H_loc - temp = Vector{Tuple{typeof(H_loc[1, 1]), Int}}() - for c in 1:nc_H_loc + H_loc_ind = Vector{Vector{Tuple{typeof(H_loc[1, 1]),Int}}}() + for r = 1:nr_H_loc + temp = Vector{Tuple{typeof(H_loc[1, 1]),Int}}() + for c = 1:nc_H_loc H_loc[r, c] != 0 && (push!(temp, (H_loc[r, c], c))) end push!(H_loc_ind, temp) @@ -206,9 +237,9 @@ function Tanner_code(G::SimpleGraph{Int}, left::Vector{Int}, right1::Vector{Int} curr_row = 0 H = zero_matrix(C.F, (length(right1) + length(right2)) * nr_H_loc, length(left)) for rv in right1 - for r in 1:nr_H_loc + for r = 1:nr_H_loc @simd for c in H_loc_ind[r] - H[curr_row + r, edge_map[G.fadjlist[rv][c[2]]]] = c[1] + H[curr_row+r, edge_map[G.fadjlist[rv][c[2]]]] = c[1] end end curr_row += nr_H_loc @@ -217,19 +248,19 @@ function Tanner_code(G::SimpleGraph{Int}, left::Vector{Int}, right1::Vector{Int} # do second code H_loc = parity_check_matrix(C2) nr_H_loc, nc_H_loc = size(H_loc) - H_loc_ind = Vector{Vector{Tuple{typeof(H_loc[1, 1]), Int}}}() - for r in 1:nr_H_loc - temp = Vector{Tuple{typeof(H_loc[1, 1]), Int}}() - for c in 1:nc_H_loc + H_loc_ind = Vector{Vector{Tuple{typeof(H_loc[1, 1]),Int}}}() + for r = 1:nr_H_loc + temp = Vector{Tuple{typeof(H_loc[1, 1]),Int}}() + for c = 1:nc_H_loc H_loc[r, c] != 0 && (push!(temp, (H_loc[r, c], c))) end push!(H_loc_ind, temp) end for rv in right2 - for r in 1:nr_H_loc + for r = 1:nr_H_loc @simd for c in H_loc_ind[r] - H[curr_row + r, edge_map[G.fadjlist[rv][c[2]]]] = c[1] + H[curr_row+r, edge_map[G.fadjlist[rv][c[2]]]] = c[1] end end curr_row += nr_H_loc diff --git a/src/Classical/TwistedReedSolomon.jl b/src/Classical/TwistedReedSolomon.jl index 57fdf369..a7e2a325 100644 --- a/src/Classical/TwistedReedSolomon.jl +++ b/src/Classical/TwistedReedSolomon.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -13,31 +13,49 @@ Return the twisted Reed-Solomon code defined in `https://arxiv.org/abs/2107.06945`. """ -function TwistedReedSolomonCode(k::Int, α::Vector{T}, t::Vector{Int}, h::Vector{Int}, η::Vector{T}) where T <: CTFieldElem - +function TwistedReedSolomonCode( + k::Int, + α::Vector{T}, + t::Vector{Int}, + h::Vector{Int}, + η::Vector{T}, +) where {T<:CTFieldElem} + l = length(t) - l == length(h) || throw(ArgumentError("Input vectors `t`, `h`, and `η` must have the same length")) - l == length(η) || throw(ArgumentError("Input vectors `t`, `h`, and `η` must have the same length")) - length(unique(collect(zip(h, t)))) == l || throw(ArgumentError("The tuples `(h[i], t[i])` must be distinct")) + l == length(h) || + throw(ArgumentError("Input vectors `t`, `h`, and `η` must have the same length")) + l == length(η) || + throw(ArgumentError("Input vectors `t`, `h`, and `η` must have the same length")) + length(unique(collect(zip(h, t)))) == l || + throw(ArgumentError("The tuples `(h[i], t[i])` must be distinct")) n = length(α) length(unique(α)) == n || throw(ArgumentError("The elements of `α` must be distinct")) - 1 ≤ k ≤ n || throw(DomainError(k, "The dimension of the code must satisfy `1 ≤ k ≤ length(α)`")) - all(1 ≤ x ≤ n - k for x in t) || throw(DomainError(t, "Elements of `t` must satsify `1 ≤ t[i] ≤ n - k`")) - all(0 ≤ x ≤ k - 1 for x in h) || throw(DomainError(h, "Elements of `h` must satsify `0 ≤ h[i] ≤ k - 1`")) + 1 ≤ k ≤ n || + throw(DomainError(k, "The dimension of the code must satisfy `1 ≤ k ≤ length(α)`")) + all(1 ≤ x ≤ n - k for x in t) || + throw(DomainError(t, "Elements of `t` must satsify `1 ≤ t[i] ≤ n - k`")) + all(0 ≤ x ≤ k - 1 for x in h) || + throw(DomainError(h, "Elements of `h` must satsify `0 ≤ h[i] ≤ k - 1`")) F = parent(α[1]) - all(parent(x) == F for x in α) || throw(DomainError(α, "All elements of `α` must be over the same base ring")) - all(parent(x) == F for x in η) || throw(DomainError(η, "All elements of `η` must be over the same base ring as the elements of `α`")) + all(parent(x) == F for x in α) || + throw(DomainError(α, "All elements of `α` must be over the same base ring")) + all(parent(x) == F for x in η) || throw( + DomainError( + η, + "All elements of `η` must be over the same base ring as the elements of `α`", + ), + ) _, x = polynomial_ring(F, :x) G = zero_matrix(F, k, n) - for i in 0:k - 1 + for i = 0:(k-1) g_i = x^i - for j in 1:l + for j = 1:l h[j] == i && (g_i += η[j] * x^(k - 1 + t[j]);) end - - for c in 1:n - G[i + 1, c] = g_i(α[c]) + + for c = 1:n + G[i+1, c] = g_i(α[c]) end end # display(G) @@ -45,14 +63,14 @@ function TwistedReedSolomonCode(k::Int, α::Vector{T}, t::Vector{Int}, h::Vector t_dual = k .- h h_dual = (n - k) .- t H = zero_matrix(F, n - k, n) - for i in 0:n - k - 1 + for i = 0:(n-k-1) g_i = x^i - for j in 1:l + for j = 1:l h_dual[j] == i && (g_i += -η[j] * x^(n - k - 1 + t_dual[j]);) end - - for c in 1:n - H[i + 1, c] = g_i(α[c]) + + for c = 1:n + H[i+1, c] = g_i(α[c]) end end # println(" ") @@ -62,11 +80,29 @@ function TwistedReedSolomonCode(k::Int, α::Vector{T}, t::Vector{Int}, h::Vector # display(G * transpose(H)) C = LinearCode(G, H, false) - return TwistedReedSolomonCode(C.F, C.n, C.k, C.d, C.l_bound, C.u_bound, C.G, C.H, C.G_stand, C.H_stand, C.P_stand, C.weight_enum, α, t, h, η, l) + return TwistedReedSolomonCode( + C.F, + C.n, + C.k, + C.d, + C.l_bound, + C.u_bound, + C.G, + C.H, + C.G_stand, + C.H_stand, + C.P_stand, + C.weight_enum, + α, + t, + h, + η, + l, + ) end ############################# - # getter functions +# getter functions ############################# """ @@ -98,15 +134,33 @@ Return the number of twists of `C`. number_of_twists(C::AbstractTwistedReedSolomonCode) = C.l ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# # TODO check if all of these are in linear_code and branches on type # TODO can do better wrt d, bounds, and weight enumerator function dual(C::AbstractTwistedReedSolomonCode) - return TwistedReedSolomonCode(C.F, C.n, C.n - C.k, missing, 1, C.n, C.H, C.G, C.H_stand, C.G_stand, C.P_stand, missing, C.α, C.k .- C.h, (C.n - C.k) .- C.t, -C.η, C.l) + return TwistedReedSolomonCode( + C.F, + C.n, + C.n - C.k, + missing, + 1, + C.n, + C.H, + C.G, + C.H_stand, + C.G_stand, + C.P_stand, + missing, + C.α, + C.k .- C.h, + (C.n - C.k) .- C.t, + -C.η, + C.l, + ) end diff --git a/src/Classical/concatenation.jl b/src/Classical/concatenation.jl index b42e24b3..e97f296a 100644 --- a/src/Classical/concatenation.jl +++ b/src/Classical/concatenation.jl @@ -5,11 +5,11 @@ # LICENSE file in the root directory of this source tree. ############################# - # Classical +# Classical ############################# ############################# - # constructors +# constructors ############################# # TODO: give control over expansion basis @@ -25,25 +25,35 @@ function concatenate(C_out::AbstractLinearCode, C_in::AbstractLinearCode) β, λ = missing, missing if Int(order(F_out)) != Int(order(F_in)) flag, deg = is_extension(F_out, F_in) - flag || throw(ArgumentError("Galois concatenation requires the outer code to be over an extension field of the inner code")) - deg % C_in.k == 0 || C_out.n % C_in.k == 0 || - throw(ArgumentError("Inner dimension must divide outer length or extension degree")) + flag || throw( + ArgumentError( + "Galois concatenation requires the outer code to be over an extension field of the inner code", + ), + ) + deg % C_in.k == 0 || + C_out.n % C_in.k == 0 || + throw( + ArgumentError( + "Inner dimension must divide outer length or extension degree", + ), + ) G_out = generator_matrix(C_out, true) ismissing(C_out.P_stand) || (G_out = G_out * C_out.P_stand) - + β, λ = primitive_basis(F_out, F_in) D = _expansion_dict(F_out, F_in, λ) G_out = _expand_matrix(G_out, D, deg) type = :expanded else - C_out.n % C_in.k == 0 || throw(ArgumentError("Inner dimension must divide outer length")) + C_out.n % C_in.k == 0 || + throw(ArgumentError("Inner dimension must divide outer length")) F_out == F_in || (C_out = change_field(C_out, F_in);) G_out = generator_matrix(C_out, true) ismissing(C_out.P_stand) || (G_out = G_out * C_out.P_stand) type = :same end - + Gin = generator_matrix(C_in, true) ismissing(C_in.P_stand) || (Gin = Gin * C_in.P_stand) G = _concatenated_generator_matrix(G_out, Gin) @@ -53,7 +63,25 @@ function concatenate(C_out::AbstractLinearCode, C_in::AbstractLinearCode) ub2, _ = _min_wt_row(G_stand) ub = min(ub1, ub2) - C = ConcatenatedCode(C_out, C_in, type, β, λ, F_in, ncols(G), k, missing, 1, ub, G, H, G_stand, H_stand, P, missing) + C = ConcatenatedCode( + C_out, + C_in, + type, + β, + λ, + F_in, + ncols(G), + k, + missing, + 1, + ub, + G, + H, + G_stand, + H_stand, + P, + missing, + ) # TODO: distance check here # for a lower bound on the distance, count the number of pieces of G_out in _concatenated_generator_matrix # with full rank and multiply by the distance of the inner code @@ -62,18 +90,24 @@ function concatenate(C_out::AbstractLinearCode, C_in::AbstractLinearCode) end ∘(C_out::AbstractLinearCode, C_in::AbstractLinearCode) = concatenate(C_out, C_in) -function concatenate(outers_unexpanded::Vector{T}, inners::Vector{T}) where T <: AbstractLinearCode +function concatenate( + outers_unexpanded::Vector{T}, + inners::Vector{T}, +) where {T<:AbstractLinearCode} isempty(outers_unexpanded) && throw(ArgumentError("List of codes cannot be empty")) - length(outers_unexpanded) == length(inners) || throw(ArgumentError("Must have the same number of inner and outer codes")) - for i in 2:length(inners) - inners[i - 1] ⊆ inners[i] || throw(ArgumentError("The inner subcodes must be in a decreasing nested sequence")) + length(outers_unexpanded) == length(inners) || + throw(ArgumentError("Must have the same number of inner and outer codes")) + for i = 2:length(inners) + inners[i-1] ⊆ inners[i] || throw( + ArgumentError("The inner subcodes must be in a decreasing nested sequence"), + ) end F = first(inners).F n_in = first(inners).n outers = copy(outers_unexpanded) - β = Union{Vector{<:CTFieldElem}, Missing}[missing for _ in eachindex(outers)] - λ = Union{Vector{<:CTFieldElem}, Missing}[missing for _ in eachindex(outers)] + β = Union{Vector{<:CTFieldElem},Missing}[missing for _ in eachindex(outers)] + λ = Union{Vector{<:CTFieldElem},Missing}[missing for _ in eachindex(outers)] type = [:same for i in eachindex(outers)] ord_F = Int(order(F)) for (i, C_out) in enumerate(outers) @@ -84,7 +118,7 @@ function concatenate(outers_unexpanded::Vector{T}, inners::Vector{T}) where T <: # if it could have been "expanded" without changing # anything, list as expanded so that the distance # calculation at the end knows - if (i == 1 && inners[i].k == 1) || (i > 1 && inners[i].k - inners[i - 1].k == 1) + if (i == 1 && inners[i].k == 1) || (i > 1 && inners[i].k - inners[i-1].k == 1) type[i] = :expanded end elseif is_subfield(F, C_out.F)[1] @@ -98,14 +132,15 @@ function concatenate(outers_unexpanded::Vector{T}, inners::Vector{T}) where T <: # Are the outer matrices the right size? n_out = divexact(outers[1].n, inners[1].k) - for i in 2:length(outers) - n_out == divexact(outers[i].n, inners[i].k - inners[i - 1].k) || throw(ArgumentError("The outer matrices are not of the correct size")) + for i = 2:length(outers) + n_out == divexact(outers[i].n, inners[i].k - inners[i-1].k) || + throw(ArgumentError("The outer matrices are not of the correct size")) end B = [generator_matrix(inners[1])] - for i in 2:length(inners) + for i = 2:length(inners) Gi = generator_matrix(inners[i]) - Gim1 = generator_matrix(inners[i - 1]) + Gim1 = generator_matrix(inners[i-1]) push!(B, _quotient_space(Gi, Gim1, :VS)) end @@ -113,7 +148,7 @@ function concatenate(outers_unexpanded::Vector{T}, inners::Vector{T}) where T <: G2 = zero_matrix(F, ncols(G1), n_in * n_out) z = 1 for i in eachindex(inners) - for j in 0:n_out - 1 + for j = 0:(n_out-1) rows = range(z, z + size(B[i], 1) - 1) cols = range(j * n_in + 1, (j + 1) * n_in) G2[rows, cols] = B[i] @@ -136,9 +171,30 @@ function concatenate(outers_unexpanded::Vector{T}, inners::Vector{T}) where T <: ub2, _ = _min_wt_row(G_stand) ub = ismissing(d) ? min(ub1, ub2) : d - return ConcatenatedCode(outers_unexpanded, inners, type, β, λ, F, ncols(G), k, d, lb, ub, G, H, G_stand, H_stand, P, missing) + return ConcatenatedCode( + outers_unexpanded, + inners, + type, + β, + λ, + F, + ncols(G), + k, + d, + lb, + ub, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end -multilevel_concatenation(outers::Vector{T}, inners::Vector{T}) where T <: AbstractLinearCode = concatenate(outers, inners) +multilevel_concatenation( + outers::Vector{T}, + inners::Vector{T}, +) where {T<:AbstractLinearCode} = concatenate(outers, inners) # cascade? # Eric had written this so it's in the way explained by the book but technically it's equivalent to the above @@ -199,7 +255,7 @@ multilevel_concatenation(outers::Vector{T}, inners::Vector{T}) where T <: Abstra # Blokh_Zyablov_concatenation(outers::Vector{T}, inners::Vector{T}) where T <: AbstractLinearCode = generalized_concatenation(outers, inners) ############################# - # getter functions +# getter functions ############################# """ @@ -238,20 +294,20 @@ Return `:expanded`, `:same`, or `:generalized` depending on the type of concaten concatenation_type(C::AbstractConcatenatedCode) = C.type ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# -function _concatenated_generator_matrix(A::T, B::T) where T <: CTMatrixTypes +function _concatenated_generator_matrix(A::T, B::T) where {T<:CTMatrixTypes} nr_A, nc_A = size(A) nr_B, nc_B = size(B) t = div(nc_A, nr_B) M = zero_matrix(base_ring(A), nr_A, t * nc_B) - for i in 1:t - M[:, nc_B * (i - 1) + 1: nc_B * i] = view(A, :, nr_B * (i - 1) + 1:nr_B * i) * B + for i = 1:t + M[:, (nc_B*(i-1)+1):(nc_B*i)] = view(A, :, (nr_B*(i-1)+1):(nr_B*i)) * B end return M end @@ -262,7 +318,7 @@ end Return the encoding of `v` into `C`, where `v` is either a valid input for the outer code or the full code. """ -function encode(C::AbstractConcatenatedCode, v::Union{CTMatrixTypes, Vector{Int}}) +function encode(C::AbstractConcatenatedCode, v::Union{CTMatrixTypes,Vector{Int}}) if typeof(v) <: CTMatrixTypes nr_v, nc_v = size(v) nr_v == 1 || nc_v == 1 || throw(ArgumentError("Vector has incorrect dimension")) @@ -270,7 +326,9 @@ function encode(C::AbstractConcatenatedCode, v::Union{CTMatrixTypes, Vector{Int} nc_w = ncols(w) if nc_w == C.C_out.k # TODO: should check order and then convert if they are the same but different pointers - base_ring(w) == C.C_out.F || throw(ArgumentError("Vector must have the same base ring as the outer code.")) + base_ring(w) == C.C_out.F || throw( + ArgumentError("Vector must have the same base ring as the outer code."), + ) G_out = generator_matrix(C.C_out, true) ismissing(C.C_out.P_stand) || (G_out = G_out * C.C_out.P_stand) temp = w * G_out @@ -285,7 +343,8 @@ function encode(C::AbstractConcatenatedCode, v::Union{CTMatrixTypes, Vector{Int} ismissing(C.C_in.P_stand) || (Gin = Gin * C.C_in.P_stand) return temp * Gin elseif nc_w == C.k - base_ring(w) == C.F || throw(ArgumentError("Vector must have the same base ring as the code.")) + base_ring(w) == C.F || + throw(ArgumentError("Vector must have the same base ring as the code.")) return w * C.G else throw(ArgumentError("Vector has incorrect dimension")) @@ -318,7 +377,7 @@ end # permute? ############################# - # Quantum +# Quantum ############################# # something like this diff --git a/src/Classical/cyclic_code.jl b/src/Classical/cyclic_code.jl index 7c931987..236db4fa 100644 --- a/src/Classical/cyclic_code.jl +++ b/src/Classical/cyclic_code.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# # TODO: these consctructors reuse a lot of the same code, extract @@ -26,7 +26,9 @@ julia> C = CyclicCode(q, n, cosets) ``` """ function CyclicCode(q::Int, n::Int, cosets::Vector{Vector{Int}}) - (q <= 1 || n <= 1) && throw(DomainError("Invalid parameters passed to CyclicCode constructor: q = $q, n = $n.")) + (q <= 1 || n <= 1) && throw( + DomainError("Invalid parameters passed to CyclicCode constructor: q = $q, n = $n."), + ) factors = Nemo.factor(q) length(factors) == 1 || throw(DomainError("There is no finite field of order $q.")) (p, t), = factors @@ -61,10 +63,13 @@ function CyclicCode(q::Int, n::Int, cosets::Vector{Vector{Int}}) tr_H = transpose(H) flag, h_test = divides(x^n - 1, g) flag || error("Incorrect generator polynomial, does not divide x^$n - 1.") - h_test == h || error("Division of x^$n - 1 by the generator polynomial does not yield the constructed parity check polynomial.") + h_test == h || error( + "Division of x^$n - 1 by the generator polynomial does not yield the constructed parity check polynomial.", + ) # e * e == e || error("Idempotent polynomial is not an idempotent.") size(H) == (n - k, k) && (temp = H; H = tr_H; tr_H = temp;) - iszero(G * tr_H) || error("Generator and parity check matrices are not transpose orthogonal.") + iszero(G * tr_H) || + error("Generator and parity check matrices are not transpose orthogonal.") if t == 1 F = GF(p) @@ -75,23 +80,92 @@ function CyclicCode(q::Int, n::Int, cosets::Vector{Vector{Int}}) ismissing(P) || (P = change_base_ring(F, P);) end - if δ >= 2 && def_set == defining_set([i for i in b:(b + δ - 2)], q, n, true) + if δ >= 2 && def_set == defining_set([i for i = b:(b+δ-2)], q, n, true) if deg == 1 && n == q - 1 # known distance, should probably not do δ, HT here d = n - k + 1 - return ReedSolomonCode(F, E, R, β, n, k, d, b, d, d, d, d, cosets, - sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, - H, G_stand, H_stand, P, missing) + return ReedSolomonCode( + F, + E, + R, + β, + n, + k, + d, + b, + d, + d, + d, + d, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end - return BCHCode(F, E, R, β, n, k, missing, b, δ, HT, HT, ub, - cosets, sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, - H, G_stand, H_stand, P, missing) + return BCHCode( + F, + E, + R, + β, + n, + k, + missing, + b, + δ, + HT, + HT, + ub, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end - return CyclicCode(F, E, R, β, n, k, missing, b, δ, HT, HT, ub, - cosets, sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, - H, G_stand, H_stand, P, missing) + return CyclicCode( + F, + E, + R, + β, + n, + k, + missing, + b, + δ, + HT, + HT, + ub, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end # TODO should define this instead over a residue ring such that n is already defined? @@ -100,8 +174,9 @@ end Return the length `n` cyclic code generated by the polynomial `g`. """ -function CyclicCode(n::Int, g::Union{fpPolyRingElem, FqPolyRingElem}) - is_positive(n) || throw(DomainError("Invalid parameters passed to CyclicCode constructor: n = $n.")) +function CyclicCode(n::Int, g::Union{fpPolyRingElem,FqPolyRingElem}) + is_positive(n) || + throw(DomainError("Invalid parameters passed to CyclicCode constructor: n = $n.")) R = parent(g) flag, h = divides(gen(R)^n - 1, g) flag || throw(ArgumentError("Given polynomial does not divide x^$n - 1.")) @@ -128,11 +203,11 @@ function CyclicCode(n::Int, g::Union{fpPolyRingElem, FqPolyRingElem}) # _, h = divides(gen(R_E)^n - 1, g_E) # TODO doesn't work for large fields - dic = Dict{FqFieldElem, Int}() - for i in 0:ord_E - 1 + dic = Dict{FqFieldElem,Int}() + for i = 0:(ord_E-1) dic[β^i] = i end - + cosets = defining_set(sort!([dic[rt] for rt in roots(g_E)]), q, n, false) def_set = sort!(reduce(vcat, cosets)) k = n - length(def_set) @@ -149,7 +224,8 @@ function CyclicCode(n::Int, g::Union{fpPolyRingElem, FqPolyRingElem}) tr_H = transpose(H) # e * e == e || error("Idempotent polynomial is not an idempotent.") size(H) == (n - k, k) && (temp = H; H = tr_H; tr_H = temp;) - iszero(G * tr_H) || error("Generator and parity check matrices are not transpose orthogonal.") + iszero(G * tr_H) || + error("Generator and parity check matrices are not transpose orthogonal.") if t == 1 F = Oscar.Nemo.Native.GF(p) @@ -160,22 +236,91 @@ function CyclicCode(n::Int, g::Union{fpPolyRingElem, FqPolyRingElem}) ismissing(P) || (P = change_base_ring(F, P);) end - if δ >= 2 && def_set == defining_set([i for i in b:(b + δ - 2)], q, n, true) + if δ >= 2 && def_set == defining_set([i for i = b:(b+δ-2)], q, n, true) if deg == 1 && n == q - 1 d = n - k + 1 - return ReedSolomonCode(F, E, R, β, n, k, d, b, d, d, d, d, cosets, - sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, - H, G_stand, H_stand, P, missing) + return ReedSolomonCode( + F, + E, + R, + β, + n, + k, + d, + b, + d, + d, + d, + d, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end - return BCHCode(F, E, R, β, n, k, missing, b, δ, HT, HT, upper, - cosets, sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, - H, G_stand, H_stand, P, missing) + return BCHCode( + F, + E, + R, + β, + n, + k, + missing, + b, + δ, + HT, + HT, + upper, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end - return CyclicCode(F, E, R, β, n, k, missing, b, δ, HT, HT, upper, - cosets, sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, - H, G_stand, H_stand, P, missing) + return CyclicCode( + F, + E, + R, + β, + n, + k, + missing, + b, + δ, + HT, + HT, + upper, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end # self orthogonal cyclic codes are even-like @@ -210,8 +355,11 @@ Generator matrix: 5 × 15 ``` """ function BCHCode(q::Int, n::Int, δ::Int, b::Int = 0) - δ >= 2 || throw(DomainError("BCH codes require δ ≥ 2 but the constructor was given δ = $δ.")) - (q <= 1 || n <= 1) && throw(DomainError("Invalid parameters passed to BCHCode constructor: q = $q, n = $n.")) + δ >= 2 || + throw(DomainError("BCH codes require δ ≥ 2 but the constructor was given δ = $δ.")) + (q <= 1 || n <= 1) && throw( + DomainError("Invalid parameters passed to BCHCode constructor: q = $q, n = $n."), + ) factors = Nemo.factor(q) length(factors) == 1 || throw(DomainError("There is no finite field of order $q.")) (p, t), = factors @@ -228,7 +376,7 @@ function BCHCode(q::Int, n::Int, δ::Int, b::Int = 0) R, x = polynomial_ring(E, :x) β = α^(div(q^deg - 1, n)) - cosets = defining_set([i for i in b:(b + δ - 2)], q, n, false) + cosets = defining_set([i for i = b:(b+δ-2)], q, n, false) def_set = sort!(reduce(vcat, cosets)) k = n - length(def_set) com_cosets = complement_qcosets(q, n, cosets) @@ -247,10 +395,13 @@ function BCHCode(q::Int, n::Int, δ::Int, b::Int = 0) tr_H = transpose(H) flag, h_test = divides(x^n - 1, g) flag || error("Incorrect generator polynomial, does not divide x^$n - 1.") - h_test == h || error("Division of x^$n - 1 by the generator polynomial does not yield the constructed parity check polynomial.") + h_test == h || error( + "Division of x^$n - 1 by the generator polynomial does not yield the constructed parity check polynomial.", + ) # e * e == e || error("Idempotent polynomial is not an idempotent.") size(H) == (n - k, k) && (temp = H; H = tr_H; tr_H = temp;) - iszero(G * tr_H) || error("Generator and parity check matrices are not transpose orthogonal.") + iszero(G * tr_H) || + error("Generator and parity check matrices are not transpose orthogonal.") if t == 1 F = GF(p) @@ -263,14 +414,60 @@ function BCHCode(q::Int, n::Int, δ::Int, b::Int = 0) if deg == 1 && n == q - 1 d = n - k + 1 - return ReedSolomonCode(F, E, R, β, n, k, d, b, d, d, d, d, cosets, - sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, - H, G_stand, H_stand, P, missing) + return ReedSolomonCode( + F, + E, + R, + β, + n, + k, + d, + b, + d, + d, + d, + d, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end - return BCHCode(F, E, R, β, n, k, missing, b, δ, HT, HT, upper, - cosets, sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, - H, G_stand, H_stand, P, missing) + return BCHCode( + F, + E, + R, + β, + n, + k, + missing, + b, + δ, + HT, + HT, + upper, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end """ @@ -311,8 +508,16 @@ Generator matrix: 8 × 12 ``` """ function ReedSolomonCode(q::Int, d::Int, b::Int = 0) - d >= 2 || throw(DomainError("Reed Solomon codes require δ ≥ 2 but the constructor was given d = $d.")) - q > 4 || throw(DomainError("Invalid or too small parameters passed to ReedSolomonCode constructor: q = $q.")) + d >= 2 || throw( + DomainError( + "Reed Solomon codes require δ ≥ 2 but the constructor was given d = $d.", + ), + ) + q > 4 || throw( + DomainError( + "Invalid or too small parameters passed to ReedSolomonCode constructor: q = $q.", + ), + ) # n = q - 1 # if ord(n, q) != 1 @@ -332,7 +537,7 @@ function ReedSolomonCode(q::Int, d::Int, b::Int = 0) R, x = polynomial_ring(F, :x) n = q - 1 - cosets = defining_set([i for i in b:(b + d - 2)], q, n, false) + cosets = defining_set([i for i = b:(b+d-2)], q, n, false) def_set = sort!(reduce(vcat, cosets)) k = n - length(def_set) com_cosets = complement_qcosets(q, n, cosets) @@ -350,16 +555,42 @@ function ReedSolomonCode(q::Int, d::Int, b::Int = 0) tr_H = transpose(H) flag, h_test = divides(x^n - 1, g) flag || error("Incorrect generator polynomial, does not divide x^$n - 1.") - h_test == h || error("Division of x^$n - 1 by the generator polynomial does not yield the constructed parity check polynomial.") + h_test == h || error( + "Division of x^$n - 1 by the generator polynomial does not yield the constructed parity check polynomial.", + ) # e * e == e || error("Idempotent polynomial is not an idempotent.") size(H) == (n - k, k) && (temp = H; H = tr_H; tr_H = temp;) - iszero(G * tr_H) || error("Generator and parity check matrices are not transpose orthogonal.") + iszero(G * tr_H) || + error("Generator and parity check matrices are not transpose orthogonal.") iszero(G_stand * tr_H) || error("Column swap appeared in _standard_form.") # TODO: known weight enumerator - return ReedSolomonCode(F, F, R, α, n, k, d, b, d, d, d, d, cosets, - sort!([arr[1] for arr in cosets]), def_set, g, h, e, G, H, - G_stand, H_stand, P, missing) + return ReedSolomonCode( + F, + F, + R, + α, + n, + k, + d, + b, + d, + d, + d, + d, + cosets, + sort!([arr[1] for arr in cosets]), + def_set, + g, + h, + e, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end # TODO: think further about how I use δ here @@ -390,28 +621,31 @@ QuadraticResidueCode(q::Int, n::Int) = CyclicCode(q, n, [quadratic_residues(q, n Return the fire code with generator polynomial `(x^(2l - 1) + 1) * p`. """ -function FireCode(p::Union{fpPolyRingElem, FqPolyRingElem}, l::Int) +function FireCode(p::Union{fpPolyRingElem,FqPolyRingElem}, l::Int) # F = base_ring(p) # Int(order(F)) == 2 || throw(ArgumentError("Fire codes are only defined over `GF(2)`.")) - Oscar.is_irreducible(p) || throw(ArgumentError("The polynomial `p` must be irreducible over `GF(2)`.")) + Oscar.is_irreducible(p) || + throw(ArgumentError("The polynomial `p` must be irreducible over `GF(2)`.")) m = degree(p) x = gen(parent(p)) 1 ≤ l ≤ m || throw(DomainError(l, "This construction requires 1 ≤ l ≤ degree(p).")) - isone(gcd(p, x^(2l - 1) + 1)) || throw(ArgumentError("This construction requires `gcd(p, x^(2l - 1) + 1) = 1`.")) + isone(gcd(p, x^(2l - 1) + 1)) || + throw(ArgumentError("This construction requires `gcd(p, x^(2l - 1) + 1) = 1`.")) g = (x^(2l - 1) + 1) * p n = -1 - for i in 1:3000 + for i = 1:3000 flag, _ = divides(x^i - 1, g) flag && (n = i; break) end - n == -1 && error("Unable to find the period of the generator polynomial in 3000 iterations.") + n == -1 && + error("Unable to find the period of the generator polynomial in 3000 iterations.") return CyclicCode(n, g) end #TODO: cyclic code constructors from zeros and nonzeros ############################# - # getter functions +# getter functions ############################# """ @@ -478,7 +712,7 @@ zeros(C::AbstractCyclicCode) = [C.β^i for i in C.def_set] Return the nonzeros of `C`. """ -nonzeros(C::AbstractCyclicCode) = [C.β^i for i in setdiff(0:C.n - 1, C.def_set)] +nonzeros(C::AbstractCyclicCode) = [C.β^i for i in setdiff(0:(C.n-1), C.def_set)] """ generator_polynomial(C::AbstractCyclicCode) @@ -518,11 +752,11 @@ BCH_bound(C::AbstractCyclicCode) = C.δ # HT_bound(C::AbstractCyclicCode) = C.HT ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# function _generator_polynomial(R::FqPolyRing, β::FqFieldElem, Z::Vector{Int}) @@ -534,7 +768,8 @@ function _generator_polynomial(R::FqPolyRing, β::FqFieldElem, Z::Vector{Int}) end return g end -_generator_polynomial(R::FqPolyRing, β::FqFieldElem, qcosets::Vector{Vector{Int}}) = _generator_polynomial(R, β, reduce(vcat, qcosets)) +_generator_polynomial(R::FqPolyRing, β::FqFieldElem, qcosets::Vector{Vector{Int}}) = + _generator_polynomial(R, β, reduce(vcat, qcosets)) function _generator_matrix(F::FqField, n::Int, k::Int, g::FqPolyRingElem) # if g = x^10 + α^2*x^9 + x^8 + α*x^7 + x^3 + α^2*x^2 + x + α @@ -544,14 +779,14 @@ function _generator_matrix(F::FqField, n::Int, k::Int, g::FqPolyRingElem) k + len - 1 <= n || error("Too many coefficients for $k shifts in _generator_matrix.") G = zero_matrix(F, k, n) - for i in 1:k - G[i:i, i:i + len - 1] = coeffs + for i = 1:k + G[i:i, i:(i+len-1)] = coeffs end return G end # TODO: make flat optional throughout - """ +""" defining_set(nums::Vector{Int}, q::Int, n::Int, flat::Bool = true) Returns the set of `q`-cyclotomic cosets of the numbers in `nums` modulo `n`. @@ -603,7 +838,7 @@ function find_delta(n::Int, cosets::Vector{Vector{Int}}) used_def_set = Vector{Int}() reps = Vector{Int}() coset_num = 0 - for i in 1:length(cosets) + for i = 1:length(cosets) if x ∈ cosets[i] coset_num = i append!(used_def_set, cosets[i]) @@ -618,7 +853,7 @@ function find_delta(n::Int, cosets::Vector{Vector{Int}}) append!(reps, y) else coset_num = 0 - for i in 1:length(cosets) + for i = 1:length(cosets) if y ∈ cosets[i] coset_num = i append!(used_def_set, cosets[i]) @@ -670,7 +905,8 @@ end Return the defining set of the dual code of length `n` and defining set `def_set`. """ -dual_defining_set(def_set::Vector{Int}, n::Int) = sort!([mod(n - i, n) for i in setdiff(0:n - 1, def_set)]) +dual_defining_set(def_set::Vector{Int}, n::Int) = + sort!([mod(n - i, n) for i in setdiff(0:(n-1), def_set)]) """ is_cyclic(C::AbstractLinearCode) @@ -680,7 +916,7 @@ return `false, missing`. """ function is_cyclic(C::AbstractLinearCode) typeof(C) <: AbstractCyclicCode && (return true, C;) - + ord_F = Int(order(C.F)) gcd(C.n, ord_F) == 1 || return false (p, t), = Nemo.factor(ord_F) @@ -692,9 +928,9 @@ function is_cyclic(C::AbstractLinearCode) G = generator_matrix(C) nc = ncols(G) - g = R([E(G[1, i]) for i in 1:nc]) - for r in 2:nrows(G) - g = gcd(g, R([E(G[r, i]) for i in 1:nc])) + g = R([E(G[1, i]) for i = 1:nc]) + for r = 2:nrows(G) + g = gcd(g, R([E(G[r, i]) for i = 1:nc])) end isone(g) && return false degree(g) == C.n - C.k || return false @@ -702,7 +938,7 @@ function is_cyclic(C::AbstractLinearCode) flag, h = divides(x^C.n - 1, g) flag || return false G_cyc = _generator_matrix(C.F, C.n, C.k, g) - for r in 1:nrows(G_cyc) + for r = 1:nrows(G_cyc) (G_cyc[r:r, :] ∈ C) || (return false;) end @@ -717,7 +953,8 @@ Return the cyclic code whose cyclotomic cosets are the completement of `C`'s. function complement(C::AbstractCyclicCode) ord_C = Int(order(C.F)) D = CyclicCode(ord_C, C.n, complement_qcosets(ord_C, C.n, C.qcosets)) - (C.h != D.g || D.e != (1 - C.e)) && error("Error constructing the complement cyclic code.") + (C.h != D.g || D.e != (1 - C.e)) && + error("Error constructing the complement cyclic code.") return D end @@ -739,7 +976,8 @@ is_subcode(C1::AbstractCyclicCode, C2::AbstractCyclicCode) = C1 ⊆ C2 Return whether or not `C1` and `C2` have the same fields, lengths, and defining sets. """ -==(C1::AbstractCyclicCode, C2::AbstractCyclicCode) = C1.F == C2.F && C1.n == C2.n && C1.def_set == C2.def_set && C1.β == C2.β +==(C1::AbstractCyclicCode, C2::AbstractCyclicCode) = + C1.F == C2.F && C1.n == C2.n && C1.def_set == C2.def_set && C1.β == C2.β # this checks def set, need to rewrite == for linear first """ @@ -770,10 +1008,17 @@ function ∩(C1::AbstractCyclicCode, C2::AbstractCyclicCode) # has generator idempotent e_1(x) e_2(x) if C1.F == C2.F && C1.n == C2.n ord_C1 = Int(order(C1.F)) - return CyclicCode(ord_C1, C1.n, defining_set(C1.def_set ∪ C2.def_set, ord_C1, - C1.n, false)) + return CyclicCode( + ord_C1, + C1.n, + defining_set(C1.def_set ∪ C2.def_set, ord_C1, C1.n, false), + ) else - throw(ArgumentError("Cannot intersect two codes over different base fields or lengths.")) + throw( + ArgumentError( + "Cannot intersect two codes over different base fields or lengths.", + ), + ) end end @@ -823,7 +1068,7 @@ some `r` less than the length of the code. """ function is_degenerate(C::AbstractCyclicCode) x = gen(C.R) - for r in 1:C.n - 1 + for r = 1:(C.n-1) flag, _ = divides(x^r - 1, C.h) flag && return true end diff --git a/src/Classical/cyclotomic.jl b/src/Classical/cyclotomic.jl index 79c9a092..8868f426 100644 --- a/src/Classical/cyclotomic.jl +++ b/src/Classical/cyclotomic.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # general functions +# general functions ############################# """ @@ -14,11 +14,11 @@ Return the order of `n` mod `q`. """ function ord(n::Int, q::Int) - (q <= 0 || n <= 0) && + (q <= 0 || n <= 0) && throw(DomainError("q and n both need to be positive. Passed: q = $q, n = $n")) # finite stop instead of while - for i in 1:200 + for i = 1:200 if mod(BigInt(q)^i, n) == 1 return i end @@ -36,11 +36,16 @@ Return the `q`-cyclotomic coset of `x` modulo `n`. sorted. If the optional parameter `verbose` is set to `true`, the result will pretty print. """ -function cyclotomic_coset(x::Int, q::Int, n::Int; to_sort::Bool = true, - verbose::Bool = false) +function cyclotomic_coset( + x::Int, + q::Int, + n::Int; + to_sort::Bool = true, + verbose::Bool = false, +) temp = [mod(x, n)] - for i in 0:(n - 1) + for i = 0:(n-1) y = mod(temp[end] * q, n) if y ∉ temp append!(temp, y) @@ -76,13 +81,12 @@ Return all `q`-cyclotomic cosets modulo `n`. sorted. If the optional parameter `verbose` is set to `true`, the result will pretty print. """ -function all_cyclotomic_cosets(q::Int, n::Int; to_sort::Bool = true, - verbose::Bool = false) +function all_cyclotomic_cosets(q::Int, n::Int; to_sort::Bool = true, verbose::Bool = false) n % q == 0 && throw(DomainError("Cyclotomic coset requires gcd(n, q) = 1")) arr = [[0]] - for x in 1:(n - 1) + for x = 1:(n-1) found = false for a in arr if x ∈ a @@ -113,7 +117,7 @@ function all_cyclotomic_cosets(q::Int, n::Int; to_sort::Bool = true, end end - if sort!(reduce(vcat, arr)) != [i for i in 0:(n - 1)] + if sort!(reduce(vcat, arr)) != [i for i = 0:(n-1)] error("Missed some") end return arr @@ -129,14 +133,14 @@ function complement_qcosets(q::Int, n::Int, qcosets::Vector{Vector{Int64}}) comp_cosets = Vector{Vector{Int64}}() for a in all # if a != [0] - found = false - for b in qcosets - if a[1] == b[1] - found = true - break - end + found = false + for b in qcosets + if a[1] == b[1] + found = true + break end - found || (push!(comp_cosets, a);) + end + found || (push!(comp_cosets, a);) # end end return comp_cosets @@ -148,8 +152,8 @@ end Return the `q`-cyclotomic cosets modulo `n` collected into complementary pairs. """ function qcoset_pairings(arr::Vector{Vector{Int64}}, n::Int) - coset_rep_list = Vector{Tuple{Int64, Int64}}() - coset_pair_list = Vector{Tuple{Vector{Int64}, Vector{Int64}}}() + coset_rep_list = Vector{Tuple{Int64,Int64}}() + coset_pair_list = Vector{Tuple{Vector{Int64},Vector{Int64}}}() for a in arr found = false for pair in coset_rep_list @@ -176,7 +180,8 @@ function qcoset_pairings(arr::Vector{Vector{Int64}}, n::Int) end return coset_pair_list, coset_rep_list end -qcoset_pairings(q::Int, n::Int) = qcoset_pairings(all_cyclotomic_cosets(q, n, to_sort = false), n) +qcoset_pairings(q::Int, n::Int) = + qcoset_pairings(all_cyclotomic_cosets(q, n, to_sort = false), n) # TODO: redo this with an abstract range """ @@ -185,7 +190,7 @@ qcoset_pairings(q::Int, n::Int) = qcoset_pairings(all_cyclotomic_cosets(q, n, to Print all `q`-cyclotomic cosets modulo `n` for `n` between `a` and `b`. """ function qcoset_table(a::Int, b::Int, q::Int) - for n in a:b + for n = a:b if n % q != 0 println("n = $n") all_cyclotomic_cosets(q, n, to_sort = true, verbose = true) diff --git a/src/Classical/linear_code.jl b/src/Classical/linear_code.jl index 0f02922b..ad59bb40 100644 --- a/src/Classical/linear_code.jl +++ b/src/Classical/linear_code.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -17,7 +17,8 @@ set to `true`, a linear code is built with `G` as the parity-check matrix. If th there are fewer than 1.5e5 codewords. """ function LinearCode(G::CTMatrixTypes, parity::Bool = false, brute_force_WE::Bool = true) - iszero(G) && return parity ? IdentityCode(base_ring(G), ncols(G)) : ZeroCode(base_ring(G), ncols(G)) + iszero(G) && return parity ? IdentityCode(base_ring(G), ncols(G)) : + ZeroCode(base_ring(G), ncols(G)) G_new = deepcopy(G) G_new = _remove_empty(G_new, :rows) @@ -33,8 +34,8 @@ function LinearCode(G::CTMatrixTypes, parity::Bool = false, brute_force_WE::Bool # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(H) H_tr = zero_matrix(base_ring(H), rnk_H, nr) - for r in 1:nr - for c in 1:rnk_H + for r = 1:nr + for c = 1:rnk_H !iszero(H[r, c]) && (H_tr[c, r] = H[r, c];) end end @@ -46,7 +47,20 @@ function LinearCode(G::CTMatrixTypes, parity::Bool = false, brute_force_WE::Bool ub2, _ = _min_wt_row(H_stand) ub = min(ub1, ub2) # treat G as the parity-check matrix H - LinearCode(base_ring(G_new), ncols(H), nrows(H_stand), missing, 1, ub, H, G_new, H_stand, G_stand, P, missing) + LinearCode( + base_ring(G_new), + ncols(H), + nrows(H_stand), + missing, + 1, + ub, + H, + G_new, + H_stand, + G_stand, + P, + missing, + ) else G_stand, H_stand, P, k = _standard_form(G_new) if k == ncols(G) @@ -58,7 +72,20 @@ function LinearCode(G::CTMatrixTypes, parity::Bool = false, brute_force_WE::Bool ub1, _ = _min_wt_row(G_new) ub2, _ = _min_wt_row(G_stand) ub = min(ub1, ub2) - LinearCode(base_ring(G_new), ncols(G_new), k, missing, 1, ub, G_new, H, G_stand, H_stand, P, missing) + LinearCode( + base_ring(G_new), + ncols(G_new), + k, + missing, + 1, + ub, + G_new, + H, + G_stand, + H_stand, + P, + missing, + ) end if k == 0 @@ -75,7 +102,12 @@ function LinearCode(G::CTMatrixTypes, parity::Bool = false, brute_force_WE::Bool MacWilliams_identity(dual(C), _weight_enumerator_BF(C.H_stand)) end end - d = minimum(filter(is_positive, first.(exponent_vectors(CWE_to_HWE(C.weight_enum).polynomial)))) + d = minimum( + filter( + is_positive, + first.(exponent_vectors(CWE_to_HWE(C.weight_enum).polynomial)), + ), + ) set_minimum_distance!(C, d) end end @@ -84,20 +116,38 @@ function LinearCode(G::CTMatrixTypes, parity::Bool = false, brute_force_WE::Bool end # TODO: add doc strings -function LinearCode(G::T, H::T, brute_force_WE::Bool = true) where T <: CTMatrixTypes - ncols(G) == ncols(H) || - throw(ArgumentError("The number of columns of G and H should be the same (received ncols(G) = $(ncols(G)), ncols(H) = $(ncols(H)))")) - base_ring(G) == base_ring(H) || throw(ArgumentError("G and H are not over the same field")) +function LinearCode(G::T, H::T, brute_force_WE::Bool = true) where {T<:CTMatrixTypes} + ncols(G) == ncols(H) || throw( + ArgumentError( + "The number of columns of G and H should be the same (received ncols(G) = $(ncols(G)), ncols(H) = $(ncols(H)))", + ), + ) + base_ring(G) == base_ring(H) || + throw(ArgumentError("G and H are not over the same field")) G_new = _remove_empty(G, :rows) H_new = _remove_empty(H, :rows) iszero(G_new * transpose(H_new)) || throw(ArgumentError("H isn't orthogonal to G")) G_stand, H_stand, P, k = _standard_form(G_new) - rank(H) == ncols(G) - k || throw(ArgumentError("The given matrix H is not a parity check matrix for G")) + rank(H) == ncols(G) - k || + throw(ArgumentError("The given matrix H is not a parity check matrix for G")) ub1, _ = _min_wt_row(G_new) ub2, _ = _min_wt_row(G_stand) ub = min(ub1, ub2) - C = LinearCode(base_ring(G_new), ncols(G_new), k, missing, 1, ub, G_new, H_new, G_stand, H_stand, P, missing) + C = LinearCode( + base_ring(G_new), + ncols(G_new), + k, + missing, + 1, + ub, + G_new, + H_new, + G_stand, + H_stand, + P, + missing, + ) if brute_force_WE && BigInt(order(base_ring(G)))^min(k, ncols(G) - k) <= 1.5e5 C.weight_enum = if 2k <= ncols(G) @@ -105,7 +155,12 @@ function LinearCode(G::T, H::T, brute_force_WE::Bool = true) where T <: CTMatrix else MacWilliams_identity(dual(C), _weight_enumerator_BF(C.H_stand)) end - d = minimum(filter(is_positive, first.(exponent_vectors(CWE_to_HWE(C.weight_enum).polynomial)))) + d = minimum( + filter( + is_positive, + first.(exponent_vectors(CWE_to_HWE(C.weight_enum).polynomial)), + ), + ) set_minimum_distance!(C, d) end @@ -114,7 +169,8 @@ end function LinearCode(G::Matrix{Int}, q::Int, parity::Bool = false) factors = Nemo.factor(q) - (length(factors) == 1 && q > 1) || throw(ArgumentError("There is no finite field of order $q.")) + (length(factors) == 1 && q > 1) || + throw(ArgumentError("There is no finite field of order $q.")) p, m = first(factors) F = m == 1 ? GF(p) : GF(p, m, :ω) @@ -125,7 +181,8 @@ end function LinearCode(Gs::Vector{<:CTMatrixTypes}) s = size(Gs[1]) - all(s == size(Gs[i]) for i in 2:length(Gs)) || throw(ArgumentError("Not all vectors in `Gs` were the same size.")) + all(s == size(Gs[i]) for i = 2:length(Gs)) || + throw(ArgumentError("Not all vectors in `Gs` were the same size.")) G = reduce(vcat, Gs) rref!(G) @@ -134,7 +191,8 @@ end function LinearCode(Gs::Vector{Vector{Int}}, q::Int, parity::Bool = false) s = size(Gs[1]) - all(s == size(Gs[i]) for i in 2:length(Gs)) || throw(ArgumentError("Not all vectors in `Gs` were the same size.")) + all(s == size(Gs[i]) for i = 2:length(Gs)) || + throw(ArgumentError("Not all vectors in `Gs` were the same size.")) return LinearCode(reduce(vcat, Gs), q, parity) end @@ -149,16 +207,21 @@ end Return a random `[n, k]` linear code over `F`. """ -function random_linear_code(F::CTFieldTypes, n::Int, k::Int; rng::AbstractRNG = Random.seed!()) +function random_linear_code( + F::CTFieldTypes, + n::Int, + k::Int; + rng::AbstractRNG = Random.seed!(), +) rand_mat = zero_matrix(F, k, n - k) - for r in 1:nrows(rand_mat) - for c in 1:ncols(rand_mat) - rand_mat[r, c] = rand(rng, F) + for r = 1:nrows(rand_mat) + for c = 1:ncols(rand_mat) + rand_mat[r, c] = rand(rng, F) end end full_mat = hcat(identity_matrix(F, k), rand_mat) return LinearCode(full_mat) -end +end # # Arguments # - `q` - a prime power @@ -172,7 +235,7 @@ Return a random `[n, k]` linear code over `GF(q)`. """ function random_linear_code(q::Int, n::Int, k::Int; rng::AbstractRNG = Random.seed!()) _, e, p = is_prime_power_with_data(q) - if e == 1 + if e == 1 field = Oscar.Nemo.Native.GF(p) elseif e > 1 field = GF(p, e, :x) @@ -183,7 +246,7 @@ function random_linear_code(q::Int, n::Int, k::Int; rng::AbstractRNG = Random.se end ############################# - # getter functions +# getter functions ############################# """ @@ -240,8 +303,8 @@ function generator_matrix(C::AbstractLinearCode, stand_form::Bool = false) # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(G) G_tr = zero_matrix(base_ring(G), rnk_G, nr) - for r in 1:nr - for c in 1:rnk_G + for r = 1:nr + for c = 1:rnk_G !iszero(G[r, c]) && (G_tr[c, r] = G[r, c];) end end @@ -279,8 +342,8 @@ function parity_check_matrix(C::AbstractLinearCode, stand_form::Bool = false) # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(G) G_tr = zero_matrix(base_ring(G), rnk_G, nr) - for r in 1:nr - for c in 1:rnk_G + for r = 1:nr + for c = 1:rnk_G !iszero(G[r, c]) && (G_tr[c, r] = G[r, c];) end end @@ -356,7 +419,8 @@ Return the number of correctable errors for the code. # Notes * The number of correctable errors is ``t = \\floor{(d - 1) / 2}``. """ -number_correctable_errors(C::AbstractLinearCode) = ismissing(C.d) ? missing : Int(fld(C.d - 1, 2)) +number_correctable_errors(C::AbstractLinearCode) = + ismissing(C.d) ? missing : Int(fld(C.d - 1, 2)) """ is_overcomplete(C::AbstractLinearCode, which::Symbol=:G) @@ -364,7 +428,7 @@ number_correctable_errors(C::AbstractLinearCode) = ismissing(C.d) ? missing : In Return `true` if the generator matrix is over complete, or if the optional parameter is set to :H and the parity-check matrix is over complete. """ -function is_overcomplete(C::AbstractLinearCode, which::Symbol=:G) +function is_overcomplete(C::AbstractLinearCode, which::Symbol = :G) if which == :G return nrows(C.G) > C.k elseif which == :H @@ -374,7 +438,7 @@ function is_overcomplete(C::AbstractLinearCode, which::Symbol=:G) end ############################# - # setter functions +# setter functions ############################# """ @@ -383,7 +447,8 @@ end Set the lower bound on the minimum distance of `C`, if `l` is better than the current bound. """ function set_distance_lower_bound!(C::AbstractLinearCode, l::Int) - 1 <= l <= C.u_bound || throw(DomainError(l, "The lower bound must be between 1 and the upper bound.")) + 1 <= l <= C.u_bound || + throw(DomainError(l, "The lower bound must be between 1 and the upper bound.")) C.l_bound < l && (C.l_bound = l;) if C.l_bound == C.u_bound @info "The new lower bound is equal to the upper bound; setting the minimum distance." @@ -397,7 +462,12 @@ end Set the upper bound on the minimum distance of `C`, if `u` is better than the current bound. """ function set_distance_upper_bound!!(C::AbstractLinearCode, u::Int) - C.l_bound <= u <= C.n || throw(DomainError(u, "The upper bound must be between the lower bound and the code length.")) + C.l_bound <= u <= C.n || throw( + DomainError( + u, + "The upper bound must be between the lower bound and the code length.", + ), + ) u < C.u_bound && (C.u_bound = u;) if C.l_bound == C.u_bound @info "The new upper bound is equal to the lower bound; setting the minimum distance." @@ -414,13 +484,14 @@ Set the minimum distance of the code to `d`. * The only check done on the value of `d` is that ``1 \\leq d \\leq n``. """ function set_minimum_distance!(C::AbstractLinearCode, d::Int) - 0 < d <= C.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + 0 < d <= C.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) C.d = d C.l_bound = d C.u_bound = d end -function change_field!(C::T, F::CTFieldTypes) where T <: AbstractLinearCode +function change_field!(C::T, F::CTFieldTypes) where {T<:AbstractLinearCode} # TODO: this is doesn't work for cyclic codes yet T <: AbstractCyclicCode && @error "Not implemented for cyclic codes yet" C.G = change_base_ring(F, C.G) @@ -435,7 +506,7 @@ function change_field!(C::T, F::CTFieldTypes) where T <: AbstractLinearCode end C.F = F - + return nothing end @@ -446,7 +517,7 @@ function change_field(C::AbstractLinearCode, F::CTFieldTypes) end ############################# - # general functions +# general functions ############################# # # Arguments @@ -458,7 +529,7 @@ Return a set of column indices corresponding to an information set of `C`. """ function information_set(C::AbstractLinearCode) _, _, perm = _rref_col_swap_perm(C.G) - return on_sets(collect(1 : C.k), inv(perm)) + return on_sets(collect(1:C.k), inv(perm)) end # # Arguments @@ -470,23 +541,26 @@ end Return a set of column indices corresponding to a random information set of `C`. """ function random_information_set(C::AbstractLinearCode; rng::AbstractRNG = Random.seed!()) - shuffle_perm_julia = shuffle(rng, collect(1 : C.n)) + shuffle_perm_julia = shuffle(rng, collect(1:C.n)) shuffle_perm = perm(shuffle_perm_julia) # apply shuffle permutation - permuted_mat = C.G[: , invperm(shuffle_perm_julia)] + permuted_mat = C.G[:, invperm(shuffle_perm_julia)] # transform to rref. The first k columns of the rref matrix are pivot columns _, _, rref_perm = CodingTheory._rref_col_swap_perm(permuted_mat) inv_perm = inv(shuffle_perm * rref_perm) # apply the inverse permutation to the pivots - return on_sets(collect(1 : C.k), inv_perm) + return on_sets(collect(1:C.k), inv_perm) end function _standard_form(G::CTMatrixTypes) rnk, G_stand, P = _rref_col_swap(G, 1:nrows(G), 1:ncols(G)) F = base_ring(G_stand) nrows(G_stand) > rnk && (G_stand = _remove_empty(G_stand, :rows);) - A_tr = transpose(view(G_stand, :, (nrows(G_stand) + 1):ncols(G_stand))) - H_stand = hcat(order(F) == 2 ? A_tr : -A_tr, identity_matrix(F, ncols(G_stand) - nrows(G_stand))) + A_tr = transpose(view(G_stand, :, (nrows(G_stand)+1):ncols(G_stand))) + H_stand = hcat( + order(F) == 2 ? A_tr : -A_tr, + identity_matrix(F, ncols(G_stand) - nrows(G_stand)), + ) return G_stand, H_stand, P, rnk end @@ -543,7 +617,7 @@ function show(io::IO, C::AbstractLinearCode) if len ≤ 20 println(io, "Evaluated at:") print(io, "\t[") - for i in 1:len + for i = 1:len if i ≠ len print(C.L[i], ", ") else @@ -558,7 +632,7 @@ function show(io::IO, C::AbstractLinearCode) if C.l ≤ 20 println(io, "Twist vector:") print(io, "\t[") - for i in 1:C.l + for i = 1:C.l if i ≠ C.l print(C.t[i], ", ") else @@ -567,7 +641,7 @@ function show(io::IO, C::AbstractLinearCode) end println(io, "Hook vector:") print(io, "\t[") - for i in 1:C.l + for i = 1:C.l if i ≠ C.l print(C.h[i], ", ") else @@ -576,7 +650,7 @@ function show(io::IO, C::AbstractLinearCode) end println(io, "Coefficient vector:") print(io, "\t[") - for i in 1:C.l + for i = 1:C.l if i ≠ C.l print(C.η[i], ", ") else @@ -587,7 +661,7 @@ function show(io::IO, C::AbstractLinearCode) if C.n ≤ 20 println(io, "Evaluated at:") print(io, "\t[") - for i in 1:C.n + for i = 1:C.n if i ≠ C.n print(C.α[i], ", ") else @@ -608,9 +682,9 @@ function show(io::IO, C::AbstractLinearCode) nr, nc = size(M) println(io, "Parity-check matrix: $(nr) × $(nc)") end - for i in 1:nr + for i = 1:nr print(io, "\t") - for j in 1:nc + for j = 1:nc if j != nc print(io, "$(M[i, j]) ") elseif j == nc && i != nr @@ -624,8 +698,16 @@ function show(io::IO, C::AbstractLinearCode) G = generator_matrix(C) nr, nc = size(G) println(io, "Generator matrix: $nr × $nc") - println(io, "\t" * replace(replace(replace(repr(MIME("text/plain"), G), - r"\n" => "\n\t"), r"\[" => ""), r"\]" => "")) + println( + io, + "\t" * replace( + replace( + replace(repr(MIME("text/plain"), G), r"\n" => "\n\t"), + r"\[" => "", + ), + r"\]" => "", + ), + ) end end # if !ismissing(C.weight_enum) @@ -640,7 +722,8 @@ end Return the Singleton bound ``d \\leq n - k + 1`` or ``k \\leq n - d + 1`` depending on the interpretation of `a`. """ -Singleton_bound(n::Int, a::Int) = 0 <= a <= n ? (return n - a + 1) : +Singleton_bound(n::Int, a::Int) = + 0 <= a <= n ? (return n - a + 1) : error("Invalid parameters for the Singleton bound. Received n = $n, k/d = $a") """ @@ -655,13 +738,17 @@ Singleton_bound(C::AbstractLinearCode) = Singleton_bound(C.n, C.k) Return the encoding of `v` into `C`. """ -function encode(C::AbstractLinearCode, v::Union{CTMatrixTypes, Vector{Int}}) +function encode(C::AbstractLinearCode, v::Union{CTMatrixTypes,Vector{Int}}) w = isa(v, Vector{Int}) ? matrix(C.F, 1, length(v), v) : v G = generator_matrix(C) nr = nrows(G) - (size(w) != (1, nr) && size(w) != (nr, 1)) && - throw(ArgumentError("Vector has incorrect dimension; expected length $nr, received: $(size(v)).")) - base_ring(w) == C.F || throw(ArgumentError("Vector must have the same base ring as the generator matrix.")) + (size(w) != (1, nr) && size(w) != (nr, 1)) && throw( + ArgumentError( + "Vector has incorrect dimension; expected length $nr, received: $(size(v)).", + ), + ) + base_ring(w) == C.F || + throw(ArgumentError("Vector must have the same base ring as the generator matrix.")) nrows(w) != 1 || return w * G return transpose(w) * G end @@ -671,17 +758,29 @@ end Return the syndrome of `v` with respect to `C`. """ -function syndrome(C::AbstractLinearCode, v::Union{CTMatrixTypes, Vector{Int}, Vector{fpFieldElem}, Vector{FpFieldElem}}) - w = isa(v, Union{Vector{Int}, Vector{fpFieldElem}, Vector{FpFieldElem}}) ? matrix(C.F, length(v), 1, v) : v +function syndrome( + C::AbstractLinearCode, + v::Union{CTMatrixTypes,Vector{Int},Vector{fpFieldElem},Vector{FpFieldElem}}, +) + w = + isa(v, Union{Vector{Int},Vector{fpFieldElem},Vector{FpFieldElem}}) ? + matrix(C.F, length(v), 1, v) : v H = parity_check_matrix(C) nc = ncols(H) - (size(w) != (nc, 1) && size(w) != (1, nc)) && - throw(ArgumentError("Vector has incorrect dimension; expected length $nc, received: $(size(v)).")) + (size(w) != (nc, 1) && size(w) != (1, nc)) && throw( + ArgumentError( + "Vector has incorrect dimension; expected length $nc, received: $(size(v)).", + ), + ) if base_ring(w) != C.F if order(base_ring(w)) == order(C.F) @warn "Fields are of different types, but have the same order." else - throw(ArgumentError("Vector must have the same base ring as the parity-check matrix.")) + throw( + ArgumentError( + "Vector must have the same base ring as the parity-check matrix.", + ), + ) end end return nrows(w) == 1 ? H * transpose(w) : H * w @@ -693,7 +792,10 @@ end Return whether or not `v` is a codeword of `C`. """ -in(v::Union{CTMatrixTypes, Vector{Int}, Vector{fpFieldElem}, Vector{FpFieldElem}}, C::AbstractLinearCode) = iszero(syndrome(C, v)) +in( + v::Union{CTMatrixTypes,Vector{Int},Vector{fpFieldElem},Vector{FpFieldElem}}, + C::AbstractLinearCode, +) = iszero(syndrome(C, v)) """ ⊆(C1::AbstractLinearCode, C2::AbstractLinearCode) @@ -703,7 +805,11 @@ in(v::Union{CTMatrixTypes, Vector{Int}, Vector{fpFieldElem}, Vector{FpFieldElem} Return whether or not `C1` is a subcode of `C2`. """ function ⊆(C1::AbstractLinearCode, C2::AbstractLinearCode) - C1.F == C2.F || (order(C1.F) == order(C2.F) ? (@warn "Fields are of different types, but have the same order.") : (return false;)) + C1.F == C2.F || ( + order(C1.F) == order(C2.F) ? + (@warn "Fields are of different types, but have the same order.") : + (return false;) + ) (C1.n == C2.n && C1.k <= C2.k) || return false G1 = generator_matrix(C1) @@ -720,22 +826,39 @@ Return the (Euclidean) dual of the code `C`. """ function dual(C::AbstractLinearCode) if typeof(C) <: AbstractCyclicCode - return CyclicCode(Int(order(C.F)), C.n, dual_qcosets(Int(order(C.F)), C.n, C.qcosets)) + return CyclicCode( + Int(order(C.F)), + C.n, + dual_qcosets(Int(order(C.F)), C.n, C.qcosets), + ) elseif isa(C, GeneralizedReedSolomonCode) d = C.k + 1 - return GeneralizedReedSolomonCode(C.F, C.n, C.n - C.k, d, d, d, - deepcopy(C.dual_scalars), deepcopy(C.scalars), deepcopy(C.eval_pts), - deepcopy(C.H), deepcopy(C.G), deepcopy(C.H_stand), - deepcopy(C.G_stand), deepcopy(C.P_stand), missing) + return GeneralizedReedSolomonCode( + C.F, + C.n, + C.n - C.k, + d, + d, + d, + deepcopy(C.dual_scalars), + deepcopy(C.scalars), + deepcopy(C.eval_pts), + deepcopy(C.H), + deepcopy(C.G), + deepcopy(C.H_stand), + deepcopy(C.G_stand), + deepcopy(C.P_stand), + missing, + ) elseif isa(C, MatrixProductCode) nr, nc = size(C.A) # probably not going to work nr == nc || return LinearCode.dual(C) D = Vector{LinearCode}() - for i in 1:length(C.C) + for i = 1:length(C.C) push!(D, dual(C.C[i])) end - + try A_inv = inv(C.A) catch @@ -744,8 +867,22 @@ function dual(C::AbstractLinearCode) return MatrixProductCode(D, transpose(A_inv)) elseif isa(C, ReedMullerCode) d = 2^(C.r + 1) - return ReedMullerCode(C.F, C.n, C.n - C.k, d, d, d, C.m - C.r - 1, C.m, C.H, C.G, - C.H_stand, C.G_stand, C.P_stand, missing) + return ReedMullerCode( + C.F, + C.n, + C.n - C.k, + d, + d, + d, + C.m - C.r - 1, + C.m, + C.H, + C.G, + C.H_stand, + C.G_stand, + C.P_stand, + missing, + ) else G = deepcopy(generator_matrix(C)) H = deepcopy(parity_check_matrix(C)) @@ -766,14 +903,38 @@ function dual(C::AbstractLinearCode) dual_wt_enum = MacWilliams_identity(C, C.weight_enum) dual_HWE_poly = CWE_to_HWE(dual_wt_enum).polynomial d = minimum(filter(>(0), first.(exponent_vectors(dual_HWE_poly)))) - return LinearCode(C.F, C.n, C.n - C.k, d, d, d, H, G, - H_stand, G_stand, P_stand, dual_wt_enum) + return LinearCode( + C.F, + C.n, + C.n - C.k, + d, + d, + d, + H, + G, + H_stand, + G_stand, + P_stand, + dual_wt_enum, + ) else ub1, _ = _min_wt_row(H) ub2, _ = _min_wt_row(H_stand) ub = min(ub1, ub2) - return LinearCode(C.F, C.n, C.n - C.k, missing, 1, ub, H, - G, H_stand, G_stand, P_stand, missing) + return LinearCode( + C.F, + C.n, + C.n - C.k, + missing, + 1, + ub, + H, + G, + H_stand, + G_stand, + P_stand, + missing, + ) end end end @@ -791,7 +952,7 @@ function Hermitian_dual(C::AbstractLinearCode) # probably not going to work nr == nc || return LinearCode.Hermitian_dual(C) D = Vector{LinearCode}() - for i in 1:length(C.C) + for i = 1:length(C.C) push!(D, Hermitian_dual(C.C[i])) end @@ -842,17 +1003,20 @@ end """ Checks permutation equivalence by brute force for the purpose of doing small tests. """ -function _are_perm_equivalent_exhaustive_search(C1::AbstractLinearCode, C2::AbstractLinearCode) - G1 = C1.G - G2 = C2.G - if G1 == G2 - return are_permutation_equivalent(C1, C2) - end +function _are_perm_equivalent_exhaustive_search( + C1::AbstractLinearCode, + C2::AbstractLinearCode, +) + G1 = C1.G + G2 = C2.G + if G1 == G2 + return are_permutation_equivalent(C1, C2) + end nc = ncols(G1) sym = symmetric_group(nc) - for e in collect(sym) + for e in collect(sym) P = permutation_matrix(C1.F, e) - if G1 * P == G2 + if G1 * P == G2 return (true, P) end end @@ -937,7 +1101,7 @@ Return the code `C` as a vector space object. function vector_space(C::AbstractLinearCode) V = vector_space(C.F, C.n) G = generator_matrix(C) - return sub(V, [V(view(G, i:i, :)) for i in 1:nrows(G)]) + return sub(V, [V(view(G, i:i, :)) for i = 1:nrows(G)]) end # vector_space(C::AbstractLinearCode) = vector_space(C) @@ -947,12 +1111,13 @@ end Return `true` if `C` is even. """ function is_even(C::AbstractLinearCode) - Int(order(C.F)) == 2 || throw(ArgumentError("Even-ness is only defined for binary codes.")) - + Int(order(C.F)) == 2 || + throw(ArgumentError("Even-ness is only defined for binary codes.")) + # A binary code generated by G is even if and only if each row of G has # even weight. G = generator_matrix(C) - return all(wt(view(G, r:r, :)) % 2 == 0 for r in 1:nrows(G)) + return all(wt(view(G, r:r, :)) % 2 == 0 for r = 1:nrows(G)) end """ @@ -961,16 +1126,17 @@ end Return `true` if `C` is doubly-even. """ function is_doubly_even(C::AbstractLinearCode) - Int(order(C.F)) == 2 || throw(ArgumentError("Even-ness is only defined for binary codes.")) + Int(order(C.F)) == 2 || + throw(ArgumentError("Even-ness is only defined for binary codes.")) # A binary code generated by G is doubly-even if and only if each row of G # has weight divisible by 4 and the sum of any two rows of G has weight # divisible by 4. G = generator_matrix(C) nr = nrows(G) - all(wt(view(G, r:r, :)) % 4 == 0 for r in 1:nr) || (return false;) - all(wt(view(G, r1:r1, :) + view(G, r2:r2, :)) % 4 == 0 - for r1 in 1:nr, r2 in 1:nr) || (return false;) + all(wt(view(G, r:r, :)) % 4 == 0 for r = 1:nr) || (return false;) + all(wt(view(G, r1:r1, :) + view(G, r2:r2, :)) % 4 == 0 for r1 = 1:nr, r2 = 1:nr) || + (return false;) return true end @@ -980,17 +1146,19 @@ end Return `true` if `C` is triply-even. """ function is_triply_even(C::AbstractLinearCode) - Int(order(C.F)) == 2 || throw(ArgumentError("Even-ness is only defined for binary codes.")) + Int(order(C.F)) == 2 || + throw(ArgumentError("Even-ness is only defined for binary codes.")) # following Ward's divisibility theorem G = _Flint_matrix_to_Julia_int_matrix(generator_matrix(C)) nr, _ = size(G) - all(wt(view(G, r:r, :)) % 8 == 0 - for r in 1:nr) || (return false;) - all(wt(view(G, r1:r1, :) .* view(G, r2:r2, :)) % 4 == 0 - for r1 in 1:nr, r2 in 1:nr) || (return false;) - all(wt(view(G, r1:r1, :) .* view(G, r2:r2, :) .* view(G, r3:r3, :)) % 2 == 0 - for r1 in 1:nr, r2 in 1:nr, r3 in 1:nr) || (return false;) + all(wt(view(G, r:r, :)) % 8 == 0 for r = 1:nr) || (return false;) + all(wt(view(G, r1:r1, :) .* view(G, r2:r2, :)) % 4 == 0 for r1 = 1:nr, r2 = 1:nr) || + (return false;) + all( + wt(view(G, r1:r1, :) .* view(G, r2:r2, :) .* view(G, r3:r3, :)) % 2 == 0 for + r1 = 1:nr, r2 = 1:nr, r3 = 1:nr + ) || (return false;) return true end @@ -1007,7 +1175,9 @@ Return the elements of `C`. """ function words(C::AbstractLinearCode, only_print::Bool = false) words = only_print ? nothing : Vector{typeof(C.G)}() - G = ismissing(C.P_stand) ? generator_matrix(C, true) : generator_matrix(C, true) * C.P_stand + G = + ismissing(C.P_stand) ? generator_matrix(C, true) : + generator_matrix(C, true) * C.P_stand E = base_ring(G) if iszero(G) @@ -1019,9 +1189,9 @@ function words(C::AbstractLinearCode, only_print::Bool = false) # TODO new bug? # for iter in Iterators.product(Iterators.repeated(E, nrows(G))...) - for iter in Nemo.AbstractAlgebra.ProductIterator([E for _ in 1:nrows(G)], inplace = true) + for iter in Nemo.AbstractAlgebra.ProductIterator([E for _ = 1:nrows(G)], inplace = true) row = iter[1] * view(G, 1:1, :) - for r in 2:nrows(G) + for r = 2:nrows(G) if !iszero(iter[r]) row += iter[r] * view(G, r:r, :) end @@ -1047,13 +1217,13 @@ function hull(C::AbstractLinearCode) H = parity_check_matrix(C) F = field(C) VS = vector_space(F, C.n) - U, U_to_VS = sub(VS, [VS(G[i, :]) for i in 1:nrows(G)]) - W, _ = sub(VS, [VS(H[i, :]) for i in 1:nrows(H)]) + U, U_to_VS = sub(VS, [VS(G[i, :]) for i = 1:nrows(G)]) + W, _ = sub(VS, [VS(H[i, :]) for i = 1:nrows(H)]) I, I_to_W = intersect(U, W) if !iszero(AbstractAlgebra.dim(I)) I_basis = [U_to_VS(I_to_W(g)) for g in gens(I)] G_I = reduce(vcat, I_basis) - F_basis = [[F(G_I[j][i]) for i in 1:C.n] for j in 1:AbstractAlgebra.dim(I)] + F_basis = [[F(G_I[j][i]) for i = 1:C.n] for j = 1:AbstractAlgebra.dim(I)] G_hull = matrix(F, length(F_basis), length(F_basis[1]), reduce(vcat, F_basis)) return LinearCode(G_hull), AbstractAlgebra.dim(I) else @@ -1076,13 +1246,13 @@ function Hermitian_hull(C::AbstractLinearCode) H = parity_check_matrix(D) F = field(C) VS = vector_space(F, C.n) - U, U_to_VS = sub(VS, [VS(G[i, :]) for i in 1:nrows(G)]) - W, _ = sub(VS, [VS(H[i, :]) for i in 1:nrows(H)]) + U, U_to_VS = sub(VS, [VS(G[i, :]) for i = 1:nrows(G)]) + W, _ = sub(VS, [VS(H[i, :]) for i = 1:nrows(H)]) I, I_to_W = intersect(U, W) if !iszero(AbstractAlgebra.dim(I)) I_basis = [U_to_VS(I_to_W(g)) for g in gens(I)] G_I = reduce(vcat, I_basis) - F_basis = [[F(G_I[j][i]) for i in 1:C.n] for j in 1:AbstractAlgebra.dim(I)] + F_basis = [[F(G_I[j][i]) for i = 1:C.n] for j = 1:AbstractAlgebra.dim(I)] G_hull = matrix(F, length(F_basis), length(F_basis[1]), reduce(vcat, F_basis)) return LinearCode(G_hull), AbstractAlgebra.dim(I) else diff --git a/src/Classical/misc_known_codes.jl b/src/Classical/misc_known_codes.jl index 5c16f261..ee49a645 100644 --- a/src/Classical/misc_known_codes.jl +++ b/src/Classical/misc_known_codes.jl @@ -5,20 +5,35 @@ # LICENSE file in the root directory of this source tree. ############################# - # Misc +# Misc ############################# function ZeroCode(F::CTFieldTypes, n::Integer) n > 0 || throw(ArgumentError("Code length must be positive (received n = $n)")) _, vars = polynomial_ring(Nemo.ZZ, Int(order(F))) - return LinearCode(F, n, 0, 0, 0, 0, zero_matrix(F, 1, n), identity_matrix(F, n), zero_matrix(F, 0, n), identity_matrix(F, n), missing, WeightEnumerator(vars[1]^n, :complete)) + return LinearCode( + F, + n, + 0, + 0, + 0, + 0, + zero_matrix(F, 1, n), + identity_matrix(F, n), + zero_matrix(F, 0, n), + identity_matrix(F, n), + missing, + WeightEnumerator(vars[1]^n, :complete), + ) end function ZeroCode(q::Integer, n::Integer) - F = if is_prime(q) Oscar.Nemo.Native.GF(q) + F = if is_prime(q) + Oscar.Nemo.Native.GF(q) else factors = Nemo.factor(q) - length(factors) == 1 || throw(DomainError("There is no finite field of order $q")) + length(factors) == 1 || + throw(DomainError("There is no finite field of order $q")) p, t = first(factors) GF(p, t, :α) end @@ -40,7 +55,8 @@ function RepetitionCode(q::Int, n::Int) Oscar.Nemo.Native.GF(q) else factors = Nemo.factor(q) - length(factors) == 1 || throw(DomainError("There is no finite field of order $q")) + length(factors) == 1 || + throw(DomainError("There is no finite field of order $q")) (p, t), = factors GF(p, t, :α) end @@ -63,7 +79,8 @@ function SingleParityCheckCode(q::Int, n::Int) Oscar.Nemo.Native.GF(q) else factors = Nemo.factor(q) - length(factors) == 1 || throw(DomainError("There is no finite field of order $q")) + length(factors) == 1 || + throw(DomainError("There is no finite field of order $q")) (p, t), = factors GF(p, t, :α) end @@ -84,11 +101,24 @@ function Hexacode() G = matrix(F, [1 0 0 1 ω ω; 0 1 0 ω 1 ω; 0 0 1 ω ω 1]) H = matrix(F, [1 ω ω 1 0 0; ω 1 ω 0 1 0; ω ω 1 0 0 1]) G_stand, H_stand, P, rnk = _standard_form(G) - return LinearCode(F, 6, 3, 4, 4, 4, G, H, G_stand, H_stand, P, _weight_enumerator_BF(G_stand)) + return LinearCode( + F, + 6, + 3, + 4, + 4, + 4, + G, + H, + G_stand, + H_stand, + P, + _weight_enumerator_BF(G_stand), + ) end ############################# - # Hamming +# Hamming ############################# # unclear if this should be promoted to its own type so r can be extracted @@ -102,7 +132,11 @@ Return the `[(q^r - 1)/(q - 1), (q^r - 1)/(q - 1) - r, 3]` Hamming code over `GF """ function HammingCode(q::Int, r::Int) 2 ≤ r || throw(DomainError("Hamming codes require r ≥ 2; received r = $r.")) - r < 64 || throw(DomainError("This Hamming code requires the implmentation of BigInts. Change if necessary.")) + r < 64 || throw( + DomainError( + "This Hamming code requires the implmentation of BigInts. Change if necessary.", + ), + ) q == 2 || throw(DomainError("Nonbinary Hamming codes have not yet been implemented.")) factors = Nemo.factor(q) length(factors) == 1 || throw(ArgumentError("There is no finite field of order $q.")) @@ -111,13 +145,23 @@ function HammingCode(q::Int, r::Int) F = Oscar.Nemo.Native.GF(2) # there are faster ways to do this using trees, but the complexity and # overhead is not worth it for the sizes required here - H = matrix(F, reduce(hcat, [reverse(digits(i, base=2, pad=r)) for i in 1:2^r - 1])) + H = matrix( + F, + reduce(hcat, [reverse(digits(i, base = 2, pad = r)) for i = 1:(2^r-1)]), + ) C = LinearCode(H, true, false) set_minimum_distance!(C, 3) R, vars = polynomial_ring(Nemo.ZZ, 2) - C.weight_enum = WeightEnumerator(divexact((vars[2] + vars[1])^C.n + C.n * - (vars[2] + vars[1])^div(C.n - 1, 2)*(vars[1] - vars[2])^div(C.n + 1, - 2), C.n + 1), :complete) + C.weight_enum = WeightEnumerator( + divexact( + (vars[2] + vars[1])^C.n + + C.n * + (vars[2] + vars[1])^div(C.n - 1, 2) * + (vars[1] - vars[2])^div(C.n + 1, 2), + C.n + 1, + ), + :complete, + ) return C end @@ -145,13 +189,19 @@ function TetraCode() H = matrix(F, [-1 -1 1 0; -1 1 0 1]) G_stand, H_stand, P, rnk = _standard_form(G) R, vars = polynomial_ring(Nemo.ZZ, 3) - CWE = WeightEnumerator(vars[1]^4 + vars[1]*vars[2]^3 + 3*vars[1]*vars[2]^2*vars[3] + - 3*vars[1]*vars[2]*vars[3]^2 + vars[1]*vars[3]^3, :complete) + CWE = WeightEnumerator( + vars[1]^4 + + vars[1]*vars[2]^3 + + 3*vars[1]*vars[2]^2*vars[3] + + 3*vars[1]*vars[2]*vars[3]^2 + + vars[1]*vars[3]^3, + :complete, + ) return LinearCode(F, 4, 2, 3, 3, 3, G, H, G_stand, H_stand, P, CWE) end ############################# - # Simplex +# Simplex ############################# # if kept as separate type, then can detect this and return simplexcode constrcutor @@ -168,7 +218,11 @@ Return the `[(q^r - 1)/(q - 1), r]` simplex code over `GF(q)`. """ function SimplexCode(q::Int, r::Int) 2 ≤ r || throw(DomainError("Simplex codes require 2 ≤ r; received r = $r.")) - r < 64 || throw(DomainError("The weight enumerator for the simplex codes for r > 64 require BigInts. Implement if necessary.")) + r < 64 || throw( + DomainError( + "The weight enumerator for the simplex codes for r > 64 require BigInts. Implement if necessary.", + ), + ) q == 2 || throw(DomainError("Nonbinary simplex codes have not yet been implemented.")) # actually really need to check here that q^r is not over sizeof(Int) @@ -185,7 +239,7 @@ function SimplexCode(q::Int, r::Int) C = LinearCode(G2, false, false) else Grm1 = G2 - for i in 3:r + for i = 3:r zs = matrix(F, nrows(Grm1), 1, zeros(Int, nrows(Grm1), 1)) bot = hcat(Grm1, zs, Grm1) zs = matrix(F, 1, ncols(Grm1), zeros(Int, 1, ncols(Grm1))) @@ -198,14 +252,16 @@ function SimplexCode(q::Int, r::Int) # all nonzero codewords have weights q^{r - 1} # should have q^r - 1 nonzero codewords R, vars = polynomial_ring(Nemo.ZZ, 2) - C.weight_enum = WeightEnumerator(vars[1]^(2^r - 1) + (2^r - 1)* - vars[1]^(2^r - 2^(r - 1) - 1)*vars[2]^(2^(r - 1)), :complete) + C.weight_enum = WeightEnumerator( + vars[1]^(2^r - 1) + (2^r - 1) * vars[1]^(2^r - 2^(r - 1) - 1) * vars[2]^(2^(r - 1)), + :complete, + ) set_minimum_distance!(C, 2^(r - 1)) return C end ############################# - # Golay +# Golay ############################# """ @@ -217,32 +273,48 @@ extended ternary Golay code if `p == 3`. function ExtendedGolayCode(p::Int) if p == 2 F = Oscar.Nemo.Native.GF(2) - A = matrix(F, [0 1 1 1 1 1 1 1 1 1 1 1; - 1 1 1 0 1 1 1 0 0 0 1 0; - 1 1 0 1 1 1 0 0 0 1 0 1; - 1 0 1 1 1 0 0 0 1 0 1 1; - 1 1 1 1 0 0 0 1 0 1 1 0; - 1 1 1 0 0 0 1 0 1 1 0 1; - 1 1 0 0 0 1 0 1 1 0 1 1; - 1 0 0 0 1 0 1 1 0 1 1 1; - 1 0 0 1 0 1 1 0 1 1 1 0; - 1 0 1 0 1 1 0 1 1 1 0 0; - 1 1 0 1 1 0 1 1 1 0 0 0; - 1 0 1 1 0 1 1 1 0 0 0 1]) + A = matrix( + F, + [ + 0 1 1 1 1 1 1 1 1 1 1 1; + 1 1 1 0 1 1 1 0 0 0 1 0; + 1 1 0 1 1 1 0 0 0 1 0 1; + 1 0 1 1 1 0 0 0 1 0 1 1; + 1 1 1 1 0 0 0 1 0 1 1 0; + 1 1 1 0 0 0 1 0 1 1 0 1; + 1 1 0 0 0 1 0 1 1 0 1 1; + 1 0 0 0 1 0 1 1 0 1 1 1; + 1 0 0 1 0 1 1 0 1 1 1 0; + 1 0 1 0 1 1 0 1 1 1 0 0; + 1 1 0 1 1 0 1 1 1 0 0 0; + 1 0 1 1 0 1 1 1 0 0 0 1 + ], + ) G = hcat(identity_matrix(F, 12), A) H = hcat(-transpose(A), identity_matrix(F, 12)) R, vars = polynomial_ring(Nemo.ZZ, 2) - wt_enum = WeightEnumerator(vars[1]^24 + 759*vars[2]^8*vars[1]^16 + 2576* - vars[2]^12*vars[1]^12 + 759*vars[1]^8*vars[2]^16 + vars[2]^24, :complete) + wt_enum = WeightEnumerator( + vars[1]^24 + + 759*vars[2]^8*vars[1]^16 + + 2576 * vars[2]^12 * vars[1]^12 + + 759*vars[1]^8*vars[2]^16 + + vars[2]^24, + :complete, + ) return LinearCode(F, 24, 12, 8, 8, 8, G, H, G, H, missing, wt_enum) elseif p == 3 F = Oscar.Nemo.Native.GF(3) - A = matrix(F, [0 1 1 1 1 1; - 1 0 1 -1 -1 1; - 1 1 0 1 -1 -1; - 1 -1 1 0 1 -1; - 1 -1 -1 1 0 1; - 1 1 -1 -1 1 0]) + A = matrix( + F, + [ + 0 1 1 1 1 1; + 1 0 1 -1 -1 1; + 1 1 0 1 -1 -1; + 1 -1 1 0 1 -1; + 1 -1 -1 1 0 1; + 1 1 -1 -1 1 0 + ], + ) G = hcat(identity_matrix(F, 6), A) H = hcat(-transpose(A), identity_matrix(F, 6)) R, vars = polynomial_ring(Nemo.ZZ, 2) @@ -272,7 +344,7 @@ function GolayCode(p::Int) end ############################# - # Hadamard +# Hadamard ############################# # """ @@ -308,16 +380,16 @@ end # WalshCode(m) = HadamardCode(m) ############################# - # Best Known Linear Codes +# Best Known Linear Codes ############################# function best_known_linear_code(n::Int, k::Int) C_GAP = GAP.Globals.BestKnownLinearCode(n, k, GAP.Globals.GF(2)) G = GAP.Globals.GeneratorMat(C_GAP) dims = GAP.Globals.DimensionsMat(G) - g = matrix(GF(2), [GAP.Globals.Int(G[i, j]) for i in 1:dims[1], j in 1:dims[2]]) + g = matrix(GF(2), [GAP.Globals.Int(G[i, j]) for i = 1:dims[1], j = 1:dims[2]]) H = GAP.Globals.CheckMat(C_GAP) dims = GAP.Globals.DimensionsMat(H) - h = matrix(GF(2), [GAP.Globals.Int(H[i, j]) for i in 1:dims[1], j in 1:dims[2]]) + h = matrix(GF(2), [GAP.Globals.Int(H[i, j]) for i = 1:dims[1], j = 1:dims[2]]) return LinearCode(g, h) end diff --git a/src/Classical/new_codes_from_old.jl b/src/Classical/new_codes_from_old.jl index 5e387c6a..836ce8be 100644 --- a/src/Classical/new_codes_from_old.jl +++ b/src/Classical/new_codes_from_old.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -15,9 +15,16 @@ Return the Plotkin (u | u + v)-construction with `u ∈ C1` and `v ∈ C2`. """ function u_u_plus_v(C1::AbstractLinearCode, C2::AbstractLinearCode) - C1.F == C2.F || throw(ArgumentError("Base field must be the same in the Plotkin (u|u + v)-construction.")) - C1.n == C2.n || throw(ArgumentError("Both codes must have the same length in the Plotkin (u|u + v)-construction.")) - (iszero(C1.G) || iszero(C2.G)) && throw(ArgumentError("`u_u_plus_v` not supported for zero codes.")) + C1.F == C2.F || throw( + ArgumentError("Base field must be the same in the Plotkin (u|u + v)-construction."), + ) + C1.n == C2.n || throw( + ArgumentError( + "Both codes must have the same length in the Plotkin (u|u + v)-construction.", + ), + ) + (iszero(C1.G) || iszero(C2.G)) && + throw(ArgumentError("`u_u_plus_v` not supported for zero codes.")) G1 = generator_matrix(C1) G2 = generator_matrix(C2) @@ -34,7 +41,20 @@ function u_u_plus_v(C1::AbstractLinearCode, C2::AbstractLinearCode) ub1, _ = _min_wt_row(G) ub2, _ = _min_wt_row(G_stand) ub = min(ub1, ub2, 2 * C1.u_bound, C2.u_bound) - return LinearCode(C1.F, 2 * C1.n, k, missing, lb, ub, G, H, G_stand, H_stand, P, missing) + return LinearCode( + C1.F, + 2 * C1.n, + k, + missing, + lb, + ub, + G, + H, + G_stand, + H_stand, + P, + missing, + ) else d = min(2 * C1.d, C2.d) return LinearCode(C1.F, 2 * C1.n, k, d, d, d, G, H, G_stand, H_stand, P, missing) @@ -48,16 +68,22 @@ Plotkin_construction(C1::AbstractLinearCode, C2::AbstractLinearCode) = u_u_plus_ Return the code generated by the (u + w | v + w | u + v + w)-construction. """ function u_plus_w_v_plus_w_u_plus_v_plus_w(C1::AbstractLinearCode, C2::AbstractLinearCode) - C1.F == C2.F || throw(ArgumentError("All codes must be over the same base ring in the (u + w | v + w | u + v + w)-construction.")) - C1.n == C2.n || throw(ArgumentError("All codes must be the same length in the (u + w | v + w | u + v + w)-construction.")) + C1.F == C2.F || throw( + ArgumentError( + "All codes must be over the same base ring in the (u + w | v + w | u + v + w)-construction.", + ), + ) + C1.n == C2.n || throw( + ArgumentError( + "All codes must be the same length in the (u + w | v + w | u + v + w)-construction.", + ), + ) G1 = generator_matrix(C1) G2 = generator_matrix(C2) Z = zero_matrix(C1.F, C1.k, C1.n) # could do some verification steps on parameters - return LinearCode(vcat(hcat(G1, Z, G1), - hcat(G2, G2, G2), - hcat(Z, G1, G1))) + return LinearCode(vcat(hcat(G1, Z, G1), hcat(G2, G2, G2), hcat(Z, G1, G1))) end # TODO: add construction A, B, Y, B2 @@ -67,16 +93,34 @@ end Return the code generated by the construction X procedure. """ -function construction_X(C1::AbstractLinearCode, C2::AbstractLinearCode, C3::AbstractLinearCode) - C1 ⊆ C2 || throw(ArgumentError("The first code must be a subcode of the second in construction X.")) - are_equivalent(C1, C2) && throw(ArgumentError("The first code must be a proper subcode of the second in construction X.")) - C1.F == C2.F == C3.F || throw(ArgumentError("All codes must be over the same base ring in construction X.")) - C2.k == C1.k + dimension(C3) || - throw(ArgumentError("The dimension of the second code must be the sum of the dimensions of the first and third codes.")) +function construction_X( + C1::AbstractLinearCode, + C2::AbstractLinearCode, + C3::AbstractLinearCode, +) + C1 ⊆ C2 || throw( + ArgumentError("The first code must be a subcode of the second in construction X."), + ) + are_equivalent(C1, C2) && throw( + ArgumentError( + "The first code must be a proper subcode of the second in construction X.", + ), + ) + C1.F == C2.F == C3.F || + throw(ArgumentError("All codes must be over the same base ring in construction X.")) + C2.k == C1.k + dimension(C3) || throw( + ArgumentError( + "The dimension of the second code must be the sum of the dimensions of the first and third codes.", + ), + ) # could do some verification steps on parameters - C = LinearCode(vcat(hcat(generator_matrix(C1 / C2), generator_matrix(C3)), - hcat(C1.G, zero_matrix(C1.F, C1.k, length(C3))))) + C = LinearCode( + vcat( + hcat(generator_matrix(C1 / C2), generator_matrix(C3)), + hcat(C1.G, zero_matrix(C1.F, C1.k, length(C3))), + ), + ) C.n == C1.n + C3.n || error("Something went wrong in construction X. Expected length $(C1.n + C3.n) but obtained length $(C.n)") @@ -95,30 +139,62 @@ end Return the code generated by the construction X3 procedure. """ -function construction_X3(C1::AbstractLinearCode, C2::AbstractLinearCode, C3::AbstractLinearCode, - C4::AbstractLinearCode, C5::AbstractLinearCode) - - C1 ⊆ C2 || throw(ArgumentError("The first code must be a subcode of the second in construction X3.")) - are_equivalent(C1, C2) && throw(ArgumentError("The first code must be a proper subcode of the second in construction X3.")) - C2 ⊆ C3 || throw(ArgumentError("The second code must be a subcode of the third in construction X3.")) - are_equivalent(C2, C3) && throw(ArgumentError("The second code must be a proper subcode of the third in construction X3.")) +function construction_X3( + C1::AbstractLinearCode, + C2::AbstractLinearCode, + C3::AbstractLinearCode, + C4::AbstractLinearCode, + C5::AbstractLinearCode, +) + + C1 ⊆ C2 || throw( + ArgumentError("The first code must be a subcode of the second in construction X3."), + ) + are_equivalent(C1, C2) && throw( + ArgumentError( + "The first code must be a proper subcode of the second in construction X3.", + ), + ) + C2 ⊆ C3 || throw( + ArgumentError("The second code must be a subcode of the third in construction X3."), + ) + are_equivalent(C2, C3) && throw( + ArgumentError( + "The second code must be a proper subcode of the third in construction X3.", + ), + ) # the above lines check C1.F == C2.F == field(C3) - C1.F == C4.F == C5.F || throw(ArgumentError("All codes must be over the same base ring in construction X3.")) - C3.k == C2.k + C4.k || - throw(ArgumentError("The dimension of the third code must be the sum of the dimensions of the second and fourth codes in construction X3.")) - C2.k == C1.k + C5.k || - throw(ArgumentError("The dimension of the second code must be the sum of the dimensions of the first and fifth codes in construction X3.")) + C1.F == C4.F == C5.F || throw( + ArgumentError("All codes must be over the same base ring in construction X3."), + ) + C3.k == C2.k + C4.k || throw( + ArgumentError( + "The dimension of the third code must be the sum of the dimensions of the second and fourth codes in construction X3.", + ), + ) + C2.k == C1.k + C5.k || throw( + ArgumentError( + "The dimension of the second code must be the sum of the dimensions of the first and fifth codes in construction X3.", + ), + ) C2_mod_C1 = C2 / C1 C3_mod_C2 = C3 / C2 F = C1.F # could do some verification steps on parameters - G = vcat(hcat(generator_matrix(C1), zero_matrix(F, C1.k, C4.n), zero_matrix(F, C1.k, C5.n)), - hcat(C2_mod_C1.G, C4.G, zero_matrix(F, C4.k, C5.n)), - hcat(C3_mod_C2.G, zero_matrix(F, C5.k, C4.n), generator_matrix(C5))) + G = vcat( + hcat(generator_matrix(C1), zero_matrix(F, C1.k, C4.n), zero_matrix(F, C1.k, C5.n)), + hcat(C2_mod_C1.G, C4.G, zero_matrix(F, C4.k, C5.n)), + hcat(C3_mod_C2.G, zero_matrix(F, C5.k, C4.n), generator_matrix(C5)), + ) C = LinearCode(G) - if !ismissing(C1.d) && !ismissing(C2.d) && !ismissing(C3.d) && !ismissing(C4.d) && !ismissing(C5.d) && ismissing(C.d) + if !ismissing(C1.d) && + !ismissing(C2.d) && + !ismissing(C3.d) && + !ismissing(C4.d) && + !ismissing(C5.d) && + ismissing(C.d) setlowerdistancebound!(C, minimum([C1.d, C2.d + C4.d, C3.d + C5.d])) end return C @@ -149,7 +225,20 @@ function ⊕(C1::AbstractLinearCode, C2::AbstractLinearCode) else lb = minimum([C1.l_bound, C2.l_bound]) ub = minimum([C1.u_bound, C2.u_bound]) - return LinearCode(C1.F, C1.n, k, missing, lb, ub, G, H, G_stand, H_stand, P, missing) + return LinearCode( + C1.F, + C1.n, + k, + missing, + lb, + ub, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end end direct_sum(C1::AbstractLinearCode, C2::AbstractLinearCode) = C1 ⊕ C2 @@ -173,8 +262,20 @@ function ×(C1::AbstractLinearCode, C2::AbstractLinearCode) d = C1.d * C2.d return LinearCode(C1.F, C1.n * C2.n, k, d, d, d, G, H, G_stand, H_stand, P, missing) else - return LinearCode(C1.F, C1.n * C2.n, k, missing, C1.l_bound * C2.l_bound, - C1.u_bound * C2.u_bound, G, H, G_stand, H_stand, P, missing) + return LinearCode( + C1.F, + C1.n * C2.n, + k, + missing, + C1.l_bound * C2.l_bound, + C1.u_bound * C2.u_bound, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end end @@ -188,7 +289,8 @@ product_code(C1::AbstractLinearCode, C2::AbstractLinearCode) = C1 × C2 Return the tensor product code of `C1` and `C2`. """ -⊗(C1::AbstractLinearCode, C2::AbstractLinearCode) = LinearCode(parity_check_matrix(C1) ⊗ parity_check_matrix(C2), true) +⊗(C1::AbstractLinearCode, C2::AbstractLinearCode) = + LinearCode(parity_check_matrix(C1) ⊗ parity_check_matrix(C2), true) kron(C1::AbstractLinearCode, C2::AbstractLinearCode) = C1 ⊗ C2 tensor_product(C1::AbstractLinearCode, C2::AbstractLinearCode) = C1 ⊗ C2 @@ -209,8 +311,10 @@ tensor_product(C1::AbstractLinearCode, C2::AbstractLinearCode) = C1 ⊗ C2 Return the entrywise product of `C` and `D`. """ function entrywise_product_code(C::AbstractLinearCode, D::AbstractLinearCode) - C.F == D.F || throw(ArgumentError("Codes must be over the same field in the Schur product.")) - C.n == D.n || throw(ArgumentError("Codes must have the same length in the Schur product.")) + C.F == D.F || + throw(ArgumentError("Codes must be over the same field in the Schur product.")) + C.n == D.n || + throw(ArgumentError("Codes must have the same length in the Schur product.")) if isa(C, ReedMullerCode) r = C.r + D.r @@ -227,20 +331,25 @@ function entrywise_product_code(C::AbstractLinearCode, D::AbstractLinearCode) # TODO: Oscar doesn't work well with dot operators # TODO: I think this choice of indices only works for C == D - indices = Vector{Tuple{Int, Int}}() - for i in 1:nr_C - for j in 1:nr_D + indices = Vector{Tuple{Int,Int}}() + for i = 1:nr_C + for j = 1:nr_D i <= j && push!(indices, (i, j)) end end - return LinearCode(matrix(C.F, reduce(vcat, G_C[i, :] .* G_D[j, :] for (i, j) in indices))) + return LinearCode( + matrix(C.F, reduce(vcat, G_C[i, :] .* G_D[j, :] for (i, j) in indices)), + ) end # TODO: verify C ⊂ it? end *(C::AbstractLinearCode, D::AbstractLinearCode) = entrywise_product_code(C, D) -Schur_product_code(C::AbstractLinearCode, D::AbstractLinearCode) = entrywise_product_code(C, D) -Hadamard_product_code(C::AbstractLinearCode, D::AbstractLinearCode) = entrywise_product_code(C, D) -componentwise_product_code(C::AbstractLinearCode, D::AbstractLinearCode) = entrywise_product_code(C, D) +Schur_product_code(C::AbstractLinearCode, D::AbstractLinearCode) = + entrywise_product_code(C, D) +Hadamard_product_code(C::AbstractLinearCode, D::AbstractLinearCode) = + entrywise_product_code(C, D) +componentwise_product_code(C::AbstractLinearCode, D::AbstractLinearCode) = + entrywise_product_code(C, D) """ /(C1::AbstractLinearCode, C2::AbstractLinearCode) @@ -256,15 +365,18 @@ function /(C2::AbstractLinearCode, C1::AbstractLinearCode) G1 = generator_matrix(C1) G2 = generator_matrix(C2) V = vector_space(F, C1.n) - U, U_to_V = sub(V, [V(G1[i, :]) for i in 1:nrows(G1)]) - W, W_to_V = sub(V, [V(G2[i, :]) for i in 1:nrows(G2)]) + U, U_to_V = sub(V, [V(G1[i, :]) for i = 1:nrows(G1)]) + W, W_to_V = sub(V, [V(G2[i, :]) for i = 1:nrows(G2)]) gens_of_U_in_W = [preimage(W_to_V, U_to_V(g)) for g in gens(U)] U_in_W, _ = sub(W, gens_of_U_in_W) Q, W_to_Q = quo(W, U_in_W) C2_mod_C1_basis = [W_to_V(x) for x in [preimage(W_to_Q, g) for g in gens(Q)]] - F_basis = [[F(C2_mod_C1_basis[j][i]) for i in 1:dim(parent(C2_mod_C1_basis[1]))] for j in 1:length(C2_mod_C1_basis)] + F_basis = [ + [F(C2_mod_C1_basis[j][i]) for i = 1:dim(parent(C2_mod_C1_basis[1]))] for + j = 1:length(C2_mod_C1_basis) + ] G = matrix(F, length(F_basis), length(F_basis[1]), reduce(vcat, F_basis)) - for r in 1:length(F_basis) + for r = 1:length(F_basis) v = G[r, :] (v ∈ C2 && v ∉ C1) || error("Error in creation of basis for C2 / C1.") end @@ -281,24 +393,29 @@ Return the code generated by the horizontal concatenation of the generator matrices of `C1` then `C2`. """ function juxtaposition(C1::AbstractLinearCode, C2::AbstractLinearCode) - C1.F == C2.F || throw(ArgumentError("Cannot juxtapose two codes over different fields.")) + C1.F == C2.F || + throw(ArgumentError("Cannot juxtapose two codes over different fields.")) G1 = generator_matrix(C1) G2 = generator_matrix(C2) - nrows(G1) == nrows(G2) || throw(ArgumentError("Cannot juxtapose codes with generator matrices with a different number of rows.")) + nrows(G1) == nrows(G2) || throw( + ArgumentError( + "Cannot juxtapose codes with generator matrices with a different number of rows.", + ), + ) return LinearCode(hcat(G1, G2)) end ############################# - # getter functions +# getter functions ############################# ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# # keep not as a one-linear for a moment to add new properties later @@ -313,10 +430,11 @@ transpose(C::AbstractLinearCode) = LinearCode(transpose(parity_check_matrix(C)), Return the code whose generator matrix is `C`'s with the columns permuted by `σ`. """ -function permute_code(C::AbstractLinearCode, σ::Union{PermGroupElem, Perm{Int}, Vector{Int}}) +function permute_code(C::AbstractLinearCode, σ::Union{PermGroupElem,Perm{Int},Vector{Int}}) if isa(C, QuasiCyclicCode) P = transpose(permutation_matrix(C.F, typeof(σ) <: Perm ? σ.d : σ)) - size(P, 1) == C.n || throw(ArgumentError("Incorrect number of digits in permutation.")) + size(P, 1) == C.n || + throw(ArgumentError("Incorrect number of digits in permutation.")) G = generator_matrix(C) * P H = parity_check_matrix(C) * P C2 = LinearCode(G, H) @@ -325,7 +443,8 @@ function permute_code(C::AbstractLinearCode, σ::Union{PermGroupElem, Perm{Int}, else C2 = copy(C) P = transpose(permutation_matrix(C.F, typeof(σ) <: Perm ? σ.d : σ)) - size(P, 1) == C.n || throw(ArgumentError("Incorrect number of digits in permutation.")) + size(P, 1) == C.n || + throw(ArgumentError("Incorrect number of digits in permutation.")) C2.G = C2.G * P C2.H = C2.H * P C2.P_stand = ismissing(C2.P_stand) ? P : C2.P_stand * P @@ -346,7 +465,11 @@ the `c`th position. If `c` isn't given, it is appended. If `a` isn't given, then the all 1's vector is used giving an even extension. """ function extend(C::AbstractLinearCode, a::CTMatrixTypes, c::Integer) - 1 <= c <= C.n + 1 || throw(ArgumentError("The code has length $(C.n), so `c` must be between 1 and $(C.n + 1).")) + 1 <= c <= C.n + 1 || throw( + ArgumentError( + "The code has length $(C.n), so `c` must be between 1 and $(C.n + 1).", + ), + ) length(a) == C.n || throw(ArgumentError("The vector `a` should have length $(C.n).")) b = ncols(a) == 1 ? transpose(a) : a nrows(b) == 1 || throw(ArgumentError("The argument `a` should be a vector.")) @@ -358,9 +481,12 @@ function extend(C::AbstractLinearCode, a::CTMatrixTypes, c::Integer) new_col[i, 1] = dot(b, view(C.G, i:i, :)) is_binary || (new_col[i, 1] *= F(-1);) end - G_new = hcat(view(C.G, :, 1:c - 1), new_col, view(C.G, :, c:C.n)) - new_row = hcat(view(b, 1:1, 1:c - 1), matrix(F, 1, 1, [1]), view(b, 1:1, c:C.n)) - H_new = vcat(new_row, hcat(view(C.H, :, 1:c - 1), zero_matrix(F, nrows(C.H), 1), view(C.H, :, c:C.n))) + G_new = hcat(view(C.G, :, 1:(c-1)), new_col, view(C.G, :, c:C.n)) + new_row = hcat(view(b, 1:1, 1:(c-1)), matrix(F, 1, 1, [1]), view(b, 1:1, c:C.n)) + H_new = vcat( + new_row, + hcat(view(C.H, :, 1:(c-1)), zero_matrix(F, nrows(C.H), 1), view(C.H, :, c:C.n)), + ) C_new = LinearCode(G_new, H_new) if !ismissing(C.d) && ismissing(C_new.d) if is_binary && all(isone(x) for x in a) @@ -374,9 +500,11 @@ function extend(C::AbstractLinearCode, a::CTMatrixTypes, c::Integer) return C_new end -extend(C::AbstractLinearCode, c::Integer) = extend(C, matrix(base_ring(C.G), 1, C.n, ones(Int, C.n)), c) +extend(C::AbstractLinearCode, c::Integer) = + extend(C, matrix(base_ring(C.G), 1, C.n, ones(Int, C.n)), c) extend(C::AbstractLinearCode, a::CTMatrixTypes) = extend(C, a, C.n + 1) -extend(C::AbstractLinearCode) = extend(C, matrix(base_ring(C.G), 1, C.n, ones(Int, C.n)), C.n + 1) +extend(C::AbstractLinearCode) = + extend(C, matrix(base_ring(C.G), 1, C.n, ones(Int, C.n)), C.n + 1) even_extension(C::AbstractLinearCode) = extend(C) """ @@ -388,8 +516,10 @@ Return the code of `C` punctured at the columns in `cols`. function puncture(C::AbstractLinearCode, cols::Vector{<:Integer}) isempty(cols) && return C allunique(cols) || throw(ArgumentError("Columns to puncture are not unique.")) - cols ⊆ 1:C.n || throw(ArgumentError("Columns to puncture are not a subset of the index set.")) - length(cols) == C.n && throw(ArgumentError("Cannot puncture all columns of a generator matrix.")) + cols ⊆ 1:C.n || + throw(ArgumentError("Columns to puncture are not a subset of the index set.")) + length(cols) == C.n && + throw(ArgumentError("Cannot puncture all columns of a generator matrix.")) G = generator_matrix(C)[:, setdiff(1:C.n, cols)] G = _remove_empty(G, :rows) @@ -415,8 +545,10 @@ function expurgate(C::AbstractLinearCode, rows::Vector{<:Integer}) allunique(rows) || throw(ArgumentError("Rows to expurgate are not unique.")) G = generator_matrix(C) nr = nrows(G) - rows ⊆ 1:nr || throw(ArgumentError("Rows to expurgate are not a subset of the index set.")) - length(rows) == nr && throw(ArgumentError("Cannot expurgate all rows of a generator matrix.")) + rows ⊆ 1:nr || + throw(ArgumentError("Rows to expurgate are not a subset of the index set.")) + length(rows) == nr && + throw(ArgumentError("Cannot expurgate all rows of a generator matrix.")) G = G[setdiff(1:nr, rows), :] G_stand, H_stand, P, k = _standard_form(G) @@ -425,7 +557,20 @@ function expurgate(C::AbstractLinearCode, rows::Vector{<:Integer}) ub1, _ = _min_wt_row(G) ub2, _ = _min_wt_row(G_stand) ub = min(ub1, ub2) - return LinearCode(C.F, C.n, k, missing, C.l_bound, ub, G, H, G_stand, H_stand, P, missing) + return LinearCode( + C.F, + C.n, + k, + missing, + C.l_bound, + ub, + G, + H, + G_stand, + H_stand, + P, + missing, + ) end expurgate(C::AbstractLinearCode, rows::Integer) = expurgate(C, [rows]) @@ -435,7 +580,8 @@ expurgate(C::AbstractLinearCode, rows::Integer) = expurgate(C, [rows]) Return the code of `C` shortened on the indices `L`. """ -shorten(C::AbstractLinearCode, L::Vector{<:Integer}) = isempty(L) ? (return C;) : (return dual(puncture(dual(C), L));) +shorten(C::AbstractLinearCode, L::Vector{<:Integer}) = + isempty(L) ? (return C;) : (return dual(puncture(dual(C), L));) shorten(C::AbstractLinearCode, L::Integer) = shorten(C, [L]) """ @@ -445,8 +591,13 @@ Return the code of `C` whose generator matrix is augmented with `M`. """ function augment(C::AbstractLinearCode, M::CTMatrixTypes) iszero(M) && throw(ArgumentError("Zero matrix passed to augment.")) - C.n == ncols(M) || throw(ArgumentError("Rows to augment must have the same number of columns as the generator matrix.")) - C.F == base_ring(M) || throw(ArgumentError("Rows to augment must have the same base field as the code.")) + C.n == ncols(M) || throw( + ArgumentError( + "Rows to augment must have the same number of columns as the generator matrix.", + ), + ) + C.F == base_ring(M) || + throw(ArgumentError("Rows to augment must have the same base field as the code.")) M = _remove_empty(M, :rows) G = vcat(generator_matrix(C), M) @@ -473,7 +624,11 @@ lengthen(C::AbstractLinearCode) = extend(augment(C, matrix(C.F, ones(Int, 1, C.n Return a `k`-dimensional subcode of `C`. """ function subcode(C::AbstractLinearCode, k::Int) - k >= 1 && k < C.k || throw(ArgumentError("Cannot construct a $k-dimensional subcode of an $(C.k)-dimensional code.")) + k >= 1 && k < C.k || throw( + ArgumentError( + "Cannot construct a $k-dimensional subcode of an $(C.k)-dimensional code.", + ), + ) k != C.k || return C return if ismissing(C.P_stand) @@ -503,17 +658,22 @@ end Return a subcode of dimenion `k` between `C1` and `C2`. """ -function subcode_of_dimension_between_codes(C1::AbstractLinearCode, C2::AbstractLinearCode, k::Int) +function subcode_of_dimension_between_codes( + C1::AbstractLinearCode, + C2::AbstractLinearCode, + k::Int, +) C2 ⊆ C1 || throw(ArgumentError("C2 must be a subcode of C1")) - C2.k <= k <= C1.k || throw(ArgumentError("The dimension must be between that of C1 and C2.")) - + C2.k <= k <= C1.k || + throw(ArgumentError("The dimension must be between that of C1 and C2.")) + k == C2.k && return C2 k == C1.k && return C1 C = C1 / C2 return if ismissing(C.P_stand) - augment(C2, generator_matrix(C, true)[1:k - C2.k, :]) + augment(C2, generator_matrix(C, true)[1:(k-C2.k), :]) else - augment(C2, generator_matrix(C, true)[1:k - C2.k, :] * C.P_stand) + augment(C2, generator_matrix(C, true)[1:(k-C2.k), :] * C.P_stand) end end @@ -533,7 +693,7 @@ function expanded_code(C::AbstractLinearCode, K::CTFieldTypes, β::Vector{FqFiel G = generator_matrix(C) G_new = zero_matrix(C.F, nrows(G) * length(β), ncols(G)) curr_row = 1 - for r in 1:nrows(G) + for r = 1:nrows(G) for βi in β G_new[curr_row, :] = βi * view(G, r:r, :) curr_row += 1 @@ -545,7 +705,7 @@ function expanded_code(C::AbstractLinearCode, K::CTFieldTypes, β::Vector{FqFiel H = parity_check_matrix(C) H_new = zero_matrix(C.F, nrows(H) * length(β), ncols(H)) curr_row = 1 - for r in 1:nrows(H) + for r = 1:nrows(H) for βi in β H_new[curr_row, :] = βi * view(H, r:r, :) curr_row += 1 @@ -585,8 +745,15 @@ end Return the subfield subcode code of `C` over `K` using the provided dual `basis` for the field of `C` over `K`. """ -function subfield_subcode(C::AbstractLinearCode, K::CTFieldTypes, basis::Vector{<:CTFieldElem}) - C_new = LinearCode(transpose(expand_matrix(transpose(parity_check_matrix(C)), K, basis)), true) +function subfield_subcode( + C::AbstractLinearCode, + K::CTFieldTypes, + basis::Vector{<:CTFieldElem}, +) + C_new = LinearCode( + transpose(expand_matrix(transpose(parity_check_matrix(C)), K, basis)), + true, + ) C_new.G = change_base_ring(K, C_new.G) C_new.H = change_base_ring(K, C_new.H) C_new.G_stand = change_base_ring(K, C_new.G_stand) @@ -602,7 +769,8 @@ end Return the trace code of `C` over `K` using the provided dual `basis` for the field of `C` over `K` using Delsarte's theorem. """ -trace_code(C::AbstractLinearCode, K::CTFieldTypes, basis::Vector{<:CTFieldElem}) = dual(subfield_subcode(dual(C), K, basis)) +trace_code(C::AbstractLinearCode, K::CTFieldTypes, basis::Vector{<:CTFieldElem}) = + dual(subfield_subcode(dual(C), K, basis)) # needs significant testing, works so far """ @@ -612,14 +780,19 @@ Return the even subcode of `C`. """ function even_subcode(C::AbstractLinearCode) F = C.F - Int(order(F)) == 2 || throw(ArgumentError("Even-ness is only defined for binary codes.")) + Int(order(F)) == 2 || + throw(ArgumentError("Even-ness is only defined for binary codes.")) V_C, ψ = vector_space(C) G_F_VS = vector_space(F, 1) - homo1_quad = ModuleHomomorphism(V_C, G_F_VS, matrix(F, dim(V_C), 1, - reduce(vcat, [F(weight(ψ(g).v) % 2) for g in gens(V_C)]))) + homo1_quad = ModuleHomomorphism( + V_C, + G_F_VS, + matrix(F, dim(V_C), 1, reduce(vcat, [F(weight(ψ(g).v) % 2) for g in gens(V_C)])), + ) even_sub, ϕ1 = kernel(homo1_quad) - iszero(dim(even_sub)) ? (return missing;) : (return LinearCode(reduce(vcat, [ψ(ϕ1(g)).v for g in gens(even_sub)]));) + iszero(dim(even_sub)) ? (return missing;) : + (return LinearCode(reduce(vcat, [ψ(ϕ1(g)).v for g in gens(even_sub)]));) end # needs significant testing, works so far @@ -630,34 +803,73 @@ Return the doubly-even subcode of `C`. """ function doubly_even_subcode(C::AbstractLinearCode) F = C.F - Int(order(C.F)) == 2 || throw(ArgumentError("Even-ness is only defined for binary codes.")) + Int(order(C.F)) == 2 || + throw(ArgumentError("Even-ness is only defined for binary codes.")) V_C, ψ = vector_space(C) G_F_VS = vector_space(F, 1) # first get the even subspace - homo1_quad = ModuleHomomorphism(V_C, G_F_VS, matrix(F, dim(V_C), 1, - reduce(vcat, [F(weight(ψ(g).v) % 2) for g in gens(V_C)]))) + homo1_quad = ModuleHomomorphism( + V_C, + G_F_VS, + matrix(F, dim(V_C), 1, reduce(vcat, [F(weight(ψ(g).v) % 2) for g in gens(V_C)])), + ) even_sub, ϕ1 = kernel(homo1_quad) if !iszero(dim(even_sub)) # now control the overlap (Ward's divisibility theorem) - homo2_bi = ModuleHomomorphism(even_sub, even_sub, matrix(F, dim(even_sub), - dim(even_sub), - reduce(vcat, [F(weight(matrix(F, 1, C.n, ψ(ϕ1(gens(even_sub)[i])).v .* - ψ(ϕ1(gens(even_sub)[j])).v)) % 2) - for i in 1:dim(even_sub), j in 1:dim(even_sub)]))) + homo2_bi = ModuleHomomorphism( + even_sub, + even_sub, + matrix( + F, + dim(even_sub), + dim(even_sub), + reduce( + vcat, + [ + F( + weight( + matrix( + F, + 1, + C.n, + ψ(ϕ1(gens(even_sub)[i])).v .* + ψ(ϕ1(gens(even_sub)[j])).v, + ), + ) % 2, + ) for i = 1:dim(even_sub), j = 1:dim(even_sub) + ], + ), + ), + ) even_sub_w_overlap, μ1 = kernel(homo2_bi) if !iszero(dim(even_sub_w_overlap)) # now apply the weight four condition - homo2_quad = ModuleHomomorphism(even_sub_w_overlap, G_F_VS, matrix(F, - dim(even_sub_w_overlap), 1, reduce(vcat, [F(div(weight(ψ(ϕ1(μ1(g))).v), - 2) % 2) for g in gens(even_sub_w_overlap)]))) + homo2_quad = ModuleHomomorphism( + even_sub_w_overlap, + G_F_VS, + matrix( + F, + dim(even_sub_w_overlap), + 1, + reduce( + vcat, + [ + F(div(weight(ψ(ϕ1(μ1(g))).v), 2) % 2) for + g in gens(even_sub_w_overlap) + ], + ), + ), + ) four_sub, ϕ2 = kernel(homo2_quad) if !iszero(dim(four_sub)) - return LinearCode(reduce(vcat, [ψ(ϕ1(μ1(ϕ2(g)))).v for g in gens(four_sub)])) + return LinearCode( + reduce(vcat, [ψ(ϕ1(μ1(ϕ2(g)))).v for g in gens(four_sub)]), + ) end end end diff --git a/src/Classical/quasi-cyclic_code.jl b/src/Classical/quasi-cyclic_code.jl index 0c585318..a8fee848 100644 --- a/src/Classical/quasi-cyclic_code.jl +++ b/src/Classical/quasi-cyclic_code.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -14,7 +14,7 @@ Return the quasi-cycle code specified by the matrix `A` of polynomial circulant generators. If the optional paramater `parity` is set to `true`, the input is used to construct the parity-check matrix. """ -function QuasiCyclicCode(A::MatElem{T}, parity::Bool=false) where T <: ResElem +function QuasiCyclicCode(A::MatElem{T}, parity::Bool = false) where {T<:ResElem} R = parent(A[1, 1]) S = base_ring(R) F = base_ring(S) @@ -28,15 +28,53 @@ function QuasiCyclicCode(A::MatElem{T}, parity::Bool=false) where T <: ResElem # k, _ = kernel(H, side = :right) k = rank(H) W = weight_matrix(A) - return QuasiCyclicCode(F, R, ncols(H), k, missing, 1, ncols(H), missing, missing, - missing, missing, missing, missing, l, m, A, A_type, W, maximum(W)) + return QuasiCyclicCode( + F, + R, + ncols(H), + k, + missing, + 1, + ncols(H), + missing, + missing, + missing, + missing, + missing, + missing, + l, + m, + A, + A_type, + W, + maximum(W), + ) else A_type = :G G = lift(A) k = rank(G) W = weight_matrix(A) - return QuasiCyclicCode(F, R, ncols(G), k, missing, 1, ncols(G), missing, missing, - missing, missing, missing, missing, l, m, A, A_type, W, maximum(W)) + return QuasiCyclicCode( + F, + R, + ncols(G), + k, + missing, + 1, + ncols(G), + missing, + missing, + missing, + missing, + missing, + missing, + l, + m, + A, + A_type, + W, + maximum(W), + ) end end @@ -53,30 +91,39 @@ for the circulant matrices instead of generator vectors for the code. If the opt * If `circ_gens` is `true`, then the length of the code is `ncols(v[1]) * l`. Circulant matrices are stacked in rows of length `l`, so `l` must divide `length(v)`. """ -function QuasiCyclicCode(v::Vector{T}, l::Int, circ_gens::Bool, parity::Bool=false) where T <: CTMatrixTypes +function QuasiCyclicCode( + v::Vector{T}, + l::Int, + circ_gens::Bool, + parity::Bool = false, +) where {T<:CTMatrixTypes} F = base_ring(v[1]) len_v = length(v) if circ_gens len_v >= 2 || throw(ArgumentError("Length of input vector must be at least two.")) - len_v % l == 0 || throw(ArgumentError("The length of the input vector must be divisible by l.")) + len_v % l == 0 || + throw(ArgumentError("The length of the input vector must be divisible by l.")) nr = div(len_v, l) r, m = size(v[1]) (r != 1 && m != 1) && throw(ArgumentError("The input matrices must be vectors.")) m == 1 && (v[1] = transpose(v[1]); (r, m = size(v[1]));) - for i in 2:len_v - F == base_ring(v[i]) || throw(ArgumentError("All inputs must be over the same base ring.")) + for i = 2:len_v + F == base_ring(v[i]) || + throw(ArgumentError("All inputs must be over the same base ring.")) r2, m2 = size(v[i]) - (r2 != 1 && m2 != 1) && throw(ArgumentError("The input matrices must be vectors.")) + (r2 != 1 && m2 != 1) && + throw(ArgumentError("The input matrices must be vectors.")) m2 == 1 && (v[i] = transpose(v[i]); (r2, m2 = size(v[i]));) - m == m2 || throw(ArgumentError("The input vectors must all be the same length.")) + m == m2 || + throw(ArgumentError("The input vectors must all be the same length.")) end S, x = polynomial_ring(F, :x) R, _ = residue_ring(S, x^m - 1) A = zero_matrix(R, nr, l) - for r in 1:nr - for c in 1:l - temp = [v[(r - 1) * l + c][i] for i in 1:m] + for r = 1:nr + for c = 1:l + temp = [v[(r-1)*l+c][i] for i = 1:m] A[r, c] = R(S(temp)) end end @@ -85,29 +132,33 @@ function QuasiCyclicCode(v::Vector{T}, l::Int, circ_gens::Bool, parity::Bool=fal r, n = size(v[1]) (r != 1 && n != 1) && throw(ArgumentError("The input matrices must be vectors.")) n == 1 && (v[1] = transpose(v[1]); (r, n = size(v[1]));) - n % l == 0 || throw(ArgumentError("Parameter l must divide the length of the vector.")) + n % l == 0 || + throw(ArgumentError("Parameter l must divide the length of the vector.")) m = div(n, l) - for i in 2:len_v - F == base_ring(v[i]) || throw(ArgumentError("All vectors must be over the same base ring.")) + for i = 2:len_v + F == base_ring(v[i]) || + throw(ArgumentError("All vectors must be over the same base ring.")) r2, n2 = size(v[i]) - (r2 != 1 && n2 != 1) && throw(ArgumentError("The input matrices must be vectors.")) + (r2 != 1 && n2 != 1) && + throw(ArgumentError("The input matrices must be vectors.")) n2 == 1 && (v[i] = transpose(v[i]); (r2, n2 = size(v[i]));) - n == n2 || throw(ArgumentError("The input vectors must all be the same length.")) + n == n2 || + throw(ArgumentError("The input vectors must all be the same length.")) end - + S, x = polynomial_ring(F, :x) R, _ = residue_ring(S, x^m - 1) A = zero_matrix(R, len_v, l) - for k in 1:len_v - for i in 1:l + for k = 1:len_v + for i = 1:l row = v[k] top_circ_row = zero_matrix(F, m, 1) - for j in 1:m - top_circ_row[j, 1] = row[i + (j - 1) * l] + for j = 1:m + top_circ_row[j, 1] = row[i+(j-1)*l] end # transpose to get first circulant column top_circ_row[2:end, :] = top_circ_row[end:-1:2, :] - A[k, i] = R(S([top_circ_row[i, 1] for i in 1:m])) + A[k, i] = R(S([top_circ_row[i, 1] for i = 1:m])) end end return QuasiCyclicCode(A, parity) @@ -121,7 +172,8 @@ Return the quasi-cyclic code of index `l` generated by right-bit shifts of size generator vector `v`. If the optional paramater `parity` is set to `true`, the input is used to construct the parity check matrix. """ -QuasiCyclicCode(v::CTMatrixTypes, l::Int, parity::Bool=false) = QuasiCyclicCode([v], l, false, parity) +QuasiCyclicCode(v::CTMatrixTypes, l::Int, parity::Bool = false) = + QuasiCyclicCode([v], l, false, parity) """ QuasiCyclicCode(v::Vector{fqPolyRepPolyRingElem}, n::Int, l::Int, parity::Bool=false) @@ -130,7 +182,12 @@ Return the quasi-cyclic code of index `l` whose circulants are defined by the ge polynomials `v`. If the optional paramater `parity` is set to `true`, the input is used to construct the parity check matrix. """ -function QuasiCyclicCode(v::Vector{T}, n::Int, l::Int, parity::Bool=false) where T <: CTMatrixTypes +function QuasiCyclicCode( + v::Vector{T}, + n::Int, + l::Int, + parity::Bool = false, +) where {T<:CTMatrixTypes} # if g = x^10 + α^2*x^9 + x^8 + α*x^7 + x^3 + α^2*x^2 + x + α # g.coeffs = [α 1 α^2 1 0 0 0 α 1 α^2 1] gen_vecs = Vector{T}() @@ -151,7 +208,7 @@ Return the quasi-cyclic code of index `l` whose circulants are determined by the codes in `v`. If the optional paramater `parity` is set to `true`, the input is used to construct the parity check matrix. """ -function QuasiCyclicCode(v::Vector{AbstractCyclicCode}, l::Int, parity::Bool=false) +function QuasiCyclicCode(v::Vector{AbstractCyclicCode}, l::Int, parity::Bool = false) gen_vecs = Vector{fqPolyRepMatrix}() for C in v push!(gen_vecs, C.G[1, :]) @@ -160,7 +217,7 @@ function QuasiCyclicCode(v::Vector{AbstractCyclicCode}, l::Int, parity::Bool=fal end ############################# - # getter functions +# getter functions ############################# """ @@ -208,11 +265,11 @@ Return `true` if `C` is a single-generator quasi-cyclic code. is_single_generator(C::AbstractQuasiCyclicCode) = (nrows(C.A) == 1;) ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# """ @@ -222,18 +279,18 @@ is_single_generator(C::AbstractQuasiCyclicCode) = (nrows(C.A) == 1;) Return the base/protograph/weight matrix of `A`. """ -function weight_matrix(A::MatElem{T}) where T <: ResElem +function weight_matrix(A::MatElem{T}) where {T<:ResElem} nr, nc = size(A) W = zeros(Int, nr, nc) - for c in 1:nc - for r in 1:nr + for c = 1:nc + for r = 1:nr W[r, c] = wt(Nemo.lift(A[r, c])) end end return W end -base_matrix(A::MatElem{T}) where T <: ResElem = weight_matrix(A) -protograph_matrix(A::MatElem{T}) where T <: ResElem = weight_matrix(A) +base_matrix(A::MatElem{T}) where {T<:ResElem} = weight_matrix(A) +protograph_matrix(A::MatElem{T}) where {T<:ResElem} = weight_matrix(A) """ noncirculant_generator_matrix(C::AbstractQuasiCyclicCode) @@ -244,15 +301,15 @@ polynomial matrix specifies the generator matrix; otherwise, return `missing`. function noncirculant_generator_matrix(C::AbstractQuasiCyclicCode) if C.A_type == :G flag = true - for r in 1:C.m + for r = 1:C.m G_inner = zero_matrix(C.F, C.l, C.l * C.n) - for col in 1:C.l + for col = 1:C.l C = lift(C.A[r, col]) G_inner = zero(C) - for i in 1:m + for i = 1:m c = k % l c == 0 && (c = l;) - G_inner[:, (i - 1) * l + c] = C[:, i] + G_inner[:, (i-1)*l+c] = C[:, i] end end flag ? (G = G_inner;) : (G = vcat(G, G_inner);) @@ -272,15 +329,15 @@ if the polynomial matrix specifies the parity-check matrix; otherwise, return `m function noncirculant_parity_check_matrix(C::AbstractQuasiCyclicCode) if C.A_type == :H flag = true - for r in 1:C.m + for r = 1:C.m H_inner = zero_matrix(C.F, C.l, C.l * C.n) - for col in 1:C.l + for col = 1:C.l C = lift(C.A[r, col]) H_inner = zero(C) - for i in 1:m + for i = 1:m c = k % l c == 0 && (c = l;) - H_inner[:, (i - 1) * l + c] = C[:, i] + H_inner[:, (i-1)*l+c] = C[:, i] end end flag ? (H = H_inner;) : (H = vcat(H, H_inner);) @@ -300,7 +357,7 @@ function generators(C::AbstractQuasiCyclicCode) G = noncirculant_generator_matrix(C) gen_vecs = Vector{fqPolyRepMatrix}() nr = nrows(G) - for i in 1:nr + for i = 1:nr if i % l == 1 push!(gen_vecs, G[i, :]) end @@ -317,8 +374,8 @@ function circulants(C::AbstractQuasiCyclicCode) circulants = Vector{fqPolyRepMatrix}() nr, nc = size(C.A) # want stored in row order - for r in 1:nr - for c in 1:nc + for r = 1:nr + for c = 1:nc push!(circulants, lift(C.A[r, c])) end end diff --git a/src/Classical/types.jl b/src/Classical/types.jl index d04e52ff..5aecf658 100644 --- a/src/Classical/types.jl +++ b/src/Classical/types.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # abstract types +# abstract types ############################# abstract type AbstractCode end @@ -28,63 +28,63 @@ abstract type AbstractGeneralizedSrivastavaCode <: AbstractAlternateCode end abstract type AbstractTwistedReedSolomonCode <: AbstractLinearCode end ############################# - # concrete types +# concrete types ############################# ############################# - # linearcode.jl +# linearcode.jl ############################# struct WeightEnumerator - polynomial::Union{ZZMPolyRingElem, Nemo.AbsSimpleNumFieldElem} - type::Symbol + polynomial::Union{ZZMPolyRingElem,Nemo.AbsSimpleNumFieldElem} + type::Symbol end - + mutable struct LinearCode <: AbstractLinearCode F::CTFieldTypes # base field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d G::CTMatrixTypes H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} end ############################# - # MatrixProductCode.jl +# MatrixProductCode.jl ############################# mutable struct MatrixProductCode <: AbstractMatrixProductCode F::CTFieldTypes # base field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d G::CTMatrixTypes H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} Cvec::Vector{AbstractLinearCode} A::fqPolyRepMatrix end ############################# - # ReedMuller.jl +# ReedMuller.jl ############################# mutable struct ReedMullerCode <: AbstractReedMullerCode F::CTFieldTypes n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d r::Integer # order @@ -93,12 +93,12 @@ mutable struct ReedMullerCode <: AbstractReedMullerCode H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} end - + ############################# - # cycliccode.jl +# cycliccode.jl ############################# mutable struct CyclicCode <: AbstractCyclicCode @@ -108,7 +108,7 @@ mutable struct CyclicCode <: AbstractCyclicCode β::CTFieldElem # n-th root of primitive element of splitting field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance b::Int # offset δ::Int # BCH bound HT::Int # Hartmann-Tzeng refinement @@ -124,8 +124,8 @@ mutable struct CyclicCode <: AbstractCyclicCode H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} end mutable struct BCHCode <: AbstractBCHCode @@ -135,7 +135,7 @@ mutable struct BCHCode <: AbstractBCHCode β::CTFieldElem # n-th root of primitive element of splitting field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance b::Int # offset δ::Int # BCH bound HT::Int # Hartmann-Tzeng refinement @@ -151,8 +151,8 @@ mutable struct BCHCode <: AbstractBCHCode H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} end mutable struct ReedSolomonCode <: AbstractReedSolomonCode @@ -162,7 +162,7 @@ mutable struct ReedSolomonCode <: AbstractReedSolomonCode β::CTFieldElem # n-th root of primitive element of splitting field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance b::Int # offset δ::Int # BCH bound HT::Int # Hartmann-Tzeng refinement @@ -178,12 +178,12 @@ mutable struct ReedSolomonCode <: AbstractReedSolomonCode H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} end ############################# - # quasicycliccode.jl +# quasicycliccode.jl ############################# mutable struct QuasiCyclicCode <: AbstractQuasiCyclicCode @@ -191,15 +191,15 @@ mutable struct QuasiCyclicCode <: AbstractQuasiCyclicCode R::EuclideanRingResidueRing n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d - G::Union{CTMatrixTypes, Missing} - H::Union{CTMatrixTypes, Missing} - G_stand::Union{CTMatrixTypes, Missing} - H_stand::Union{CTMatrixTypes, Missing} - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + G::Union{CTMatrixTypes,Missing} + H::Union{CTMatrixTypes,Missing} + G_stand::Union{CTMatrixTypes,Missing} + H_stand::Union{CTMatrixTypes,Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} l::Int m::Int A::MatElem{<:ResElem} @@ -209,14 +209,14 @@ mutable struct QuasiCyclicCode <: AbstractQuasiCyclicCode end ############################# - # GRS_alternate.jl +# GRS_alternate.jl ############################# mutable struct GeneralizedReedSolomonCode <: AbstractGeneralizedReedSolomonCode F::CTFieldTypes # base field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d scalars::Vector{<:CTFieldElem} @@ -226,8 +226,8 @@ mutable struct GeneralizedReedSolomonCode <: AbstractGeneralizedReedSolomonCode H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} # TODO: should never be missing? is completely known for MDS? + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} # TODO: should never be missing? is completely known for MDS? end mutable struct AlternateCode <: AbstractAlternateCode @@ -235,7 +235,7 @@ mutable struct AlternateCode <: AbstractAlternateCode E::CTFieldTypes # extension field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d scalars::Vector{<:CTFieldElem} @@ -244,8 +244,8 @@ mutable struct AlternateCode <: AbstractAlternateCode H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} end mutable struct GeneralizedSrivastavaCode <: AbstractGeneralizedSrivastavaCode @@ -253,7 +253,7 @@ mutable struct GeneralizedSrivastavaCode <: AbstractGeneralizedSrivastavaCode E::CTFieldTypes # extension field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d a::Vector{<:CTFieldElem} @@ -264,12 +264,12 @@ mutable struct GeneralizedSrivastavaCode <: AbstractGeneralizedSrivastavaCode H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} end ############################# - # Goppa.jl +# Goppa.jl ############################# mutable struct GoppaCode <: AbstractGoppaCode @@ -277,63 +277,63 @@ mutable struct GoppaCode <: AbstractGoppaCode E::CTFieldTypes # extension field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d G::CTMatrixTypes H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} L::Vector{CTFieldElem} g::FqPolyRingElem end ############################# - # concatenation.jl +# concatenation.jl ############################# mutable struct ConcatenatedCode <: AbstractLinearCode - C_in::Union{AbstractLinearCode, Vector{<:AbstractLinearCode}} - C_out::Union{AbstractLinearCode, Vector{<:AbstractLinearCode}} - type::Union{Symbol, Vector{Symbol}} - basis::Union{Missing, Vector{Union{Missing, <:CTFieldElem, Vector{<:CTFieldElem}}}} - dual_basis::Union{Missing, Vector{Union{Missing, <:CTFieldElem, Vector{<:CTFieldElem}}}} + C_in::Union{AbstractLinearCode,Vector{<:AbstractLinearCode}} + C_out::Union{AbstractLinearCode,Vector{<:AbstractLinearCode}} + type::Union{Symbol,Vector{Symbol}} + basis::Union{Missing,Vector{Union{Missing,<:CTFieldElem,Vector{<:CTFieldElem}}}} + dual_basis::Union{Missing,Vector{Union{Missing,<:CTFieldElem,Vector{<:CTFieldElem}}}} F::CTFieldTypes # base field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d G::CTMatrixTypes H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} end ############################# - # TwistedReedSolomon.jl +# TwistedReedSolomon.jl ############################# mutable struct TwistedReedSolomonCode <: AbstractTwistedReedSolomonCode F::CTFieldTypes # base field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d G::CTMatrixTypes H::CTMatrixTypes G_stand::CTMatrixTypes H_stand::CTMatrixTypes - P_stand::Union{CTMatrixTypes, Missing} # permutation matrix for G -> G_stand - weight_enum::Union{WeightEnumerator, Missing} - α::Vector{T} where T <: CTFieldElem + P_stand::Union{CTMatrixTypes,Missing} # permutation matrix for G -> G_stand + weight_enum::Union{WeightEnumerator,Missing} + α::Vector{T} where {T<:CTFieldElem} t::Vector{Int} h::Vector{Int} - η::Vector{T} where T <: CTFieldElem + η::Vector{T} where {T<:CTFieldElem} l::Int -end \ No newline at end of file +end diff --git a/src/Classical/weight_dist.jl b/src/Classical/weight_dist.jl index 1e40c673..01c6e844 100644 --- a/src/Classical/weight_dist.jl +++ b/src/Classical/weight_dist.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # General +# General ############################# # using AllocCheck # using Profile @@ -43,9 +43,9 @@ function _weight_enumerator_BF(G::CTMatrixTypes) lookup = Dict(value => key for (key, value) in enumerate(collect(E))) # for iter in Iterators.product(Iterators.repeated(E, nr)...) - for iter in Nemo.AbstractAlgebra.ProductIterator([E for _ in 1:nr], inplace = true) + for iter in Nemo.AbstractAlgebra.ProductIterator([E for _ = 1:nr], inplace = true) row = iter[1] * view(G, 1:1, :) - for r in 2:nr + for r = 2:nr if !iszero(iter[r]) row += iter[r] * view(G, r:r, :) end @@ -57,7 +57,7 @@ function _weight_enumerator_BF(G::CTMatrixTypes) term[lookup[x]] += 1 end term_poly = R(1) - for i in 1:ord_E + for i = 1:ord_E term_poly *= vars[i]^term[i] end poly += term_poly @@ -75,7 +75,7 @@ function CWE_to_HWE(CWE::WeightEnumerator) R, (x, y) = polynomial_ring(base_ring(CWE.polynomial), [:x, :y]) poly = R(0) - for i in 1:length(CWE.polynomial) + for i = 1:length(CWE.polynomial) exps = exponent_vector(CWE.polynomial, i) poly += coeff(CWE.polynomial, i) * x^sum(exps[2:end]) * y^exps[1] end @@ -88,13 +88,28 @@ end Search for codewords of `C` of weight `w` using Stern's attack and return any found. """ -function Sterns_attack(C::AbstractLinearCode, w::Int, p::Int, l::Int; num_find::Int = 2, max_iters::Int = 50000) +function Sterns_attack( + C::AbstractLinearCode, + w::Int, + p::Int, + l::Int; + num_find::Int = 2, + max_iters::Int = 50000, +) # requires 2 * x = 0 Int(order(C.F)) == 2 || throw(ArgumentError("Only valid for binary codes.")) if !ismissing(C.d) - C.d <= w <= C.n || throw(ArgumentError("Target weight must be between the minimum distance and code length.")) + C.d <= w <= C.n || throw( + ArgumentError( + "Target weight must be between the minimum distance and code length.", + ), + ) else - 1 <= w <= C.n || throw(ArgumentError("Target weight must be positive and no more than the code length.")) + 1 <= w <= C.n || throw( + ArgumentError( + "Target weight must be positive and no more than the code length.", + ), + ) end 1 <= p <= ceil(C.k / 2) || throw(ArgumentError("p must be between 1 and k/2")) @@ -122,7 +137,7 @@ function Sterns_attack(C::AbstractLinearCode, w::Int, p::Int, l::Int; num_find:: while have < nr i = rand(1:loc) nonzeros = [] - for j in 1:nr + for j = 1:nr if !iszero(H2[j, i]) append!(nonzeros, j) end @@ -137,7 +152,7 @@ function Sterns_attack(C::AbstractLinearCode, w::Int, p::Int, l::Int; num_find:: # H2[nz, :] = H2[nz, col_indices[i]]^-1 * H2[nz, :] # end - for j in 1:nr + for j = 1:nr # go through all rows and eliminate all nonzeros in column using the chosen row if j != nz && !iszero(H2[j, col_indices[i]]) if !isone(H2[j, col_indices[i]]) @@ -186,7 +201,7 @@ function Sterns_attack(C::AbstractLinearCode, w::Int, p::Int, l::Int; num_find:: # randomly split the remaning column indices X = Vector{Int}() Y = Vector{Int}() - for i in col_indices[1:nc - nr] + for i in col_indices[1:(nc-nr)] rand(Float16) <= 0.5 ? (append!(X, i);) : (append!(Y, i);) end @@ -213,24 +228,24 @@ function Sterns_attack(C::AbstractLinearCode, w::Int, p::Int, l::Int; num_find:: # storing this is a terrible idea but avoids repeated calculations of πB for each A # will have to check later if that's fast enough in parallel to do left = nr - l - AπAs = Vector{Tuple{Vector{Int}, Vector{fqPolyRepFieldElem}}}() + AπAs = Vector{Tuple{Vector{Int},Vector{fqPolyRepFieldElem}}}() # for every size-p subset A of X for A in powerset(X, p, p) # compute the sum of the columns in A for each of those l rows # this represents the contribution from these columns to the dot product - πA = [sum(H2[Z[left + 1], A])] - for i in 2:l - push!(πA, sum(H2[Z[left + i], A])) + πA = [sum(H2[Z[left+1], A])] + for i = 2:l + push!(πA, sum(H2[Z[left+i], A])) end push!(AπAs, (A, πA)) end # compute π(B) for every size-p subset B of Y - BπBs = Vector{Tuple{Vector{Int}, Vector{fqPolyRepFieldElem}}}() + BπBs = Vector{Tuple{Vector{Int},Vector{fqPolyRepFieldElem}}}() for B in powerset(Y, p, p) - πB = [sum(H2[Z[left + 1], B])] - for i in 2:l - push!(πB, sum(H2[Z[left + i], B])) + πB = [sum(H2[Z[left+1], B])] + for i = 2:l + push!(πB, sum(H2[Z[left+i], B])) end push!(BπBs, (B, πB)) end @@ -244,7 +259,7 @@ function Sterns_attack(C::AbstractLinearCode, w::Int, p::Int, l::Int; num_find:: AB = i[1] ∪ j[1] # compute the sum of the 2p columns in A ∪ B over all rows πAB = [sum(H2[1, AB])] - for k in 2:nr + for k = 2:nr push!(πAB, sum(H2[k, AB])) end @@ -255,7 +270,7 @@ function Sterns_attack(C::AbstractLinearCode, w::Int, p::Int, l::Int; num_find:: # so any time there is a 1 at index i, put a 1 in the i-th position of the end of col_indices # that will give w - 2p 1's at locations outside of A ∪ B vec_len_w = zeros(C.F, 1, nc) - for k in 1:nr + for k = 1:nr if isone(πAB[k]) vec_len_w[1, row_pivots_loc[k]] = C.F(1) end @@ -285,7 +300,7 @@ function Sterns_attack(C::AbstractLinearCode, w::Int, p::Int, l::Int; num_find:: end ############################# - # Enumeration Based Algs +# Enumeration Based Algs ############################# # TODO: @@ -295,19 +310,28 @@ end # TODO: this does not produce the optimal set of matrices # see section 7.3 of White's thesis for comments on this -function information_sets(G::CTMatrixTypes, alg::Symbol = :Edmonds; permute::Bool = false, only_A::Bool = false) - - alg ∈ (:Brouwer, :Zimmermann, :White, :Chen, :Bouyuklieva, :Edmonds) || throw(ArgumentError("Unknown information set algorithm. Expected `:Brouwer`, `:Zimmermann`, `:White`, `:Chen`, `:Bouyuklieva`, or `:Edmonds`.")) +function information_sets( + G::CTMatrixTypes, + alg::Symbol = :Edmonds; + permute::Bool = false, + only_A::Bool = false, +) + + alg ∈ (:Brouwer, :Zimmermann, :White, :Chen, :Bouyuklieva, :Edmonds) || throw( + ArgumentError( + "Unknown information set algorithm. Expected `:Brouwer`, `:Zimmermann`, `:White`, `:Chen`, `:Bouyuklieva`, or `:Edmonds`.", + ), + ) # TODO should rref to begin with and remove empty rows? nr, nc = size(G) gen_mats = Vector{}() perms = Vector{}() rnks = Vector{Int}() - + rnk = nr #TODO Brouw and Zimm should use the same code for rref then discard the last matrix if alg == :Brouwer - for i in 0:Int(floor(nc / nr)) - 1 + for i = 0:(Int(floor(nc/nr))-1) start_ind = i * nr + 1 rnk, Gi, Pi = _rref_col_swap(G, 1:nr, start_ind:nc) if rnk < nr # for Brouwer the Gi must all have full rank @@ -315,14 +339,14 @@ function information_sets(G::CTMatrixTypes, alg::Symbol = :Edmonds; permute::Boo end if only_A - Ai = Gi[:, setdiff(1:nc, start_ind:(i + 1) * nr)] + Ai = Gi[:, setdiff(1:nc, start_ind:((i+1)*nr))] push!(gen_mats, Ai) push!(perms, Pi) push!(rnks, rnk) else if permute # permute identities to the front - pivots = collect(start_ind:(i + 1) * nr) + pivots = collect(start_ind:((i+1)*nr)) σ = [pivots; setdiff(1:nc, pivots)] Gi = Gi[:, σ] Pi = Pi[:, σ] @@ -333,17 +357,17 @@ function information_sets(G::CTMatrixTypes, alg::Symbol = :Edmonds; permute::Boo end end elseif alg == :Zimmermann - for i in 0:Int(floor(nc / nr)) - rnk, Gi, Pi = _rref_col_swap(G, 1:nr, i * rnk + 1:nc) + for i = 0:Int(floor(nc/nr)) + rnk, Gi, Pi = _rref_col_swap(G, 1:nr, (i*rnk+1):nc) if only_A - Ai = Gi[:, setdiff(1:nc, i * nr + 1:i * nr + rnk)] + Ai = Gi[:, setdiff(1:nc, (i*nr+1):(i*nr+rnk))] push!(gen_mats, Ai) push!(perms, Pi) push!(rnks, rnk) else if permute # permute identities to the front - pivots = collect(i * nr + 1:(i + 1) * nr) + pivots = collect((i*nr+1):((i+1)*nr)) σ = [pivots; setdiff(1:nc, pivots)] Gi = Gi[:, σ] Pi = Pi[:, σ] @@ -356,9 +380,9 @@ function information_sets(G::CTMatrixTypes, alg::Symbol = :Edmonds; permute::Boo elseif alg == :White # TODO: this is not true when the parity-check matrix is true # the expansion factor of the code - for i in 0:div(nc, nr) - 1 + for i = 0:(div(nc, nr)-1) # could use Gi here instead of G - rnk, Gi, Pi = _rref_col_swap(G, 1:nr, i * nr + 1:(i + 1) * nr) + rnk, Gi, Pi = _rref_col_swap(G, 1:nr, (i*nr+1):((i+1)*nr)) # display(Gi) # println(rnk) push!(gen_mats, Gi) @@ -368,7 +392,7 @@ function information_sets(G::CTMatrixTypes, alg::Symbol = :Edmonds; permute::Boo elseif alg == :Chen Gi, _, Pi, rnk = _standard_form(G) if only_A - Ai = Gi[:, rnk + 1:nc] + Ai = Gi[:, (rnk+1):nc] push!(gen_mats, Ai) push!(perms, Pi) push!(rnks, rnk) @@ -381,31 +405,46 @@ function information_sets(G::CTMatrixTypes, alg::Symbol = :Edmonds; permute::Boo return gen_mats, perms, rnks end -function information_set_lower_bound(r::Int, n::Int, k::Int, l::Int, rank_defs::Vector{Int}, - info_set_alg::Symbol; even::Bool = false, doubly_even::Bool = false, triply_even::Bool = false) - - info_set_alg ∈ (:auto, :Brouwer, :Zimmermann, :White, :Chen, :Bouyuklieva, :Edmonds) || throw(ArgumentError("Unknown information set algorithm. Expected `:auto`, `:Brouwer`, `:Zimmermann`, `:White`, `:Chen`, `:Bouyuklieva`, or `:Edmonds`.")) +function information_set_lower_bound( + r::Int, + n::Int, + k::Int, + l::Int, + rank_defs::Vector{Int}, + info_set_alg::Symbol; + even::Bool = false, + doubly_even::Bool = false, + triply_even::Bool = false, +) + + info_set_alg ∈ (:auto, :Brouwer, :Zimmermann, :White, :Chen, :Bouyuklieva, :Edmonds) || + throw( + ArgumentError( + "Unknown information set algorithm. Expected `:auto`, `:Brouwer`, `:Zimmermann`, `:White`, `:Chen`, `:Bouyuklieva`, or `:Edmonds`.", + ), + ) lower = 0 if info_set_alg == :Brouwer lower = r * length(rank_defs) elseif info_set_alg == :Zimmermann h = length(rank_defs) - lower = count(x -> x != 0, rank_defs) - for i in 1:h - lower += maximum([0, r - rank_defs[i]]) + lower = count(x -> x != 0, rank_defs) + for i = 1:h + lower += maximum([0, r - rank_defs[i]]) end elseif info_set_alg == :Chen lower = Int(ceil(n * r / k)) elseif info_set_alg == :White lower = 0 - for i in 1:l - lower += Int(ceil(n * maximum([0, r - rank_defs[i]]) / (l * (k + rank_defs[i])))) + for i = 1:l + lower += + Int(ceil(n * maximum([0, r - rank_defs[i]]) / (l * (k + rank_defs[i])))) end - # elseif info_set_alg == :Bouyuklieva - # continue - # elseif info_set_alg == :Edmonds - # continue + # elseif info_set_alg == :Bouyuklieva + # continue + # elseif info_set_alg == :Edmonds + # continue end if lower == 0 println("initial lower bound is set to 0") @@ -428,8 +467,12 @@ is returned. show_progress will display a progress meter for each iteration of a weight that takes longer than a second """ -function minimum_distance_Gray(C::AbstractLinearCode; alg::Symbol = :auto, verbose::Bool = false, - show_progress = true) +function minimum_distance_Gray( + C::AbstractLinearCode; + alg::Symbol = :auto, + verbose::Bool = false, + show_progress = true, +) ord_F = Int(order(C.F)) ord_F == 2 || throw(ArgumentError("Currently only implemented for binary codes.")) @@ -440,7 +483,11 @@ function minimum_distance_Gray(C::AbstractLinearCode; alg::Symbol = :auto, verbo # :Zimmermann Algo 2.4 # :Chen Algo 2.6 # :White Algo 3.1 - alg ∈ (:auto, :Brouwer, :Zimmermann, :White, :Chen) || throw(ArgumentError("Unknown information set algorithm. Expected `:auto`, `:Brouwer`, `:Zimmermann`, `:White`, `:Chen`")) + alg ∈ (:auto, :Brouwer, :Zimmermann, :White, :Chen) || throw( + ArgumentError( + "Unknown information set algorithm. Expected `:auto`, `:Brouwer`, `:Zimmermann`, `:White`, `:Chen`", + ), + ) if alg == :auto if typeof(C) <: AbstractCyclicCode @@ -456,22 +503,30 @@ function minimum_distance_Gray(C::AbstractLinearCode; alg::Symbol = :auto, verbo end end # TODO should never hit this case with the else in there? - alg == :auto && throw(ErrorException("Could not determine minimum distance algo automatically")) + alg == :auto && + throw(ErrorException("Could not determine minimum distance algo automatically")) # really this should work for all just the same? if alg in (:Brouwer, :Zimmermann) return _minimum_distance_BZ(C::AbstractLinearCode, alg, verbose, show_progress) end println("Warning: old enumeration algorithm selected. Performance will be slow") # TODO remove when all code updated - return _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCode; info_set_alg = alg) + return _minimum_distance_enumeration_with_matrix_multiply( + C::AbstractLinearCode; + info_set_alg = alg, + ) end # this is a private function, so there's no point in having keyword arguments -function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbose::Bool, - show_progress::Bool) - +function _minimum_distance_BZ( + C::AbstractLinearCode, + info_set_alg::Symbol, + verbose::Bool, + show_progress::Bool, +) + # you never pass this in anywhere so moving out - dbg::Dict{String, Int} = Dict() + dbg::Dict{String,Int} = Dict() dbg_key_exit_r = "exit_r" # removing since checked in main function @@ -479,24 +534,36 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo # ord_F == 2 || throw(ArgumentError("Currently only implemented for binary codes.")) # put this at user entry point, although if 2^k is large, 2^(n - k) maybe small enough to do # so we should put this in an if statement above if we are doing G or H - C.k < 2^16 || throw(DomainError("The given linear code has length k >= 2^16 which is not supported")) + C.k < 2^16 || throw( + DomainError("The given linear code has length k >= 2^16 which is not supported"), + ) - info_set_alg ∈ (:Brouwer, :Zimmermann) || throw(ArgumentError("Unknown information set algorithm. Expected `:Brouwer`, `:Zimmermann`")) + info_set_alg ∈ (:Brouwer, :Zimmermann) || throw( + ArgumentError( + "Unknown information set algorithm. Expected `:Brouwer`, `:Zimmermann`", + ), + ) generator_matrix(C, true) # ensure G_stand exists - if _has_empty_vec(C.G, :cols) + if _has_empty_vec(C.G, :cols) #TODO err string can instruct the user to construct a new code without 0 cols and tell them the function for that - throw(ArgumentError("Codes with standard form of generator matrix having 0 columns not supported")) + throw( + ArgumentError( + "Codes with standard form of generator matrix having 0 columns not supported", + ), + ) # is that actually possible? I thought we remove this in the linear code constructor? If we don't we should and then remove this here end # generate if not pre-stored parity_check_matrix(C) - A_mats, perms_mats, rnks = information_sets(C.G, info_set_alg, permute = true, only_A = false) + A_mats, perms_mats, rnks = + information_sets(C.G, info_set_alg, permute = true, only_A = false) A_mats = [deepcopy(_Flint_matrix_to_Julia_T_matrix(Ai, UInt16)') for Ai in A_mats] # A_mats_trunc = () - perms_mats = [deepcopy(_Flint_matrix_to_Julia_T_matrix(Pi, UInt16)') for Pi in perms_mats] + perms_mats = + [deepcopy(_Flint_matrix_to_Julia_T_matrix(Pi, UInt16)') for Pi in perms_mats] h = length(A_mats) # println("Starting loop to refine upper bound. Initial upper bound ", C.u_bound, " num of mats is ", length(A_mats), " dimension ", size(A_mats[1])) rank_defs = zeros(Int, h) @@ -506,14 +573,16 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo end if haskey(dbg, dbg_key_exit_r) - verbose && println("dbg Dict: largest message weight searched stored @key = $dbg_key_exit_r") + verbose && println( + "dbg Dict: largest message weight searched stored @key = $dbg_key_exit_r", + ) dbg[dbg_key_exit_r] = -1 end k, n = size(C.G) - A_mats_trunc = [Matrix{UInt16}(undef, k, n - k) for _ in 1:length(A_mats)] - for i in 1:size(A_mats, 1) - A_mats_trunc[i] = deepcopy(A_mats[i][k + 1 : n, :]) + A_mats_trunc = [Matrix{UInt16}(undef, k, n - k) for _ = 1:length(A_mats)] + for i = 1:size(A_mats, 1) + A_mats_trunc[i] = deepcopy(A_mats[i][(k+1):n, :]) end # I don't remember this case in the paper @@ -524,7 +593,7 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo # I think we have to remove this from the verbose statement to work if verbose print("Generated $h information sets with ranks: ") - for i in 1:h + for i = 1:h i == h ? (println(rnks[i]);) : (print("$(rnks[i]), ");) # will only be using the rank deficits here # at the moment, the information sets are always disjoint so the relative @@ -533,7 +602,7 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo rank_defs[i] = C.k - rnks[i] end end - + even_flag = false doubly_even_flag = false triply_even_flag = false @@ -543,7 +612,8 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo if verbose triply_even_flag && println("Detected a triply even code.") (!triply_even_flag && doubly_even_flag) && println("Detected a doubly even code.") - (!triply_even_flag && !doubly_even_flag && even_flag) && println("Detected an even code.") + (!triply_even_flag && !doubly_even_flag && even_flag) && + println("Detected an even code.") end # initial_perm_ind will match the permutation we use for the 'found' vector if the found vector is nonzero. To simplify the code below we're going to choose an initial permutation arbitrarily. @@ -553,9 +623,9 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo # can make this faster with dots and views w, i = _min_wt_col(g) if w <= C.u_bound - found = g[:, i] + found = g[:, i] C.u_bound = w - y = perms_mats[j] * found + y = perms_mats[j] * found end end @@ -568,7 +638,19 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo if verbose _, _, b_rnks = information_sets(C.G, :Brouwer, permute = true, only_A = false) b_h = length(b_rnks) - b_lower_bounds = [information_set_lower_bound(r + 1, n, k, l, [k - 0 for i in 1:b_h], :Brouwer, even = even_flag, doubly_even = doubly_even_flag, triply_even = triply_even_flag) for r in 1:k - 1] + b_lower_bounds = [ + information_set_lower_bound( + r + 1, + n, + k, + l, + [k - 0 for i = 1:b_h], + :Brouwer, + even = even_flag, + doubly_even = doubly_even_flag, + triply_even = triply_even_flag, + ) for r = 1:(k-1) + ] b_r_term = findfirst(x -> x ≥ C.u_bound, b_lower_bounds) # _, _, z_rnks = information_sets(G, :Zimmermann, permute = true, only_A = false) @@ -580,31 +662,56 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo end # Note the r + 1 here - lower_bounds_for_prediction = [information_set_lower_bound(r + 1, n, k, l, rank_defs, info_set_alg, even = even_flag, doubly_even = doubly_even_flag, triply_even = triply_even_flag) for r in 1:k - 1] + lower_bounds_for_prediction = [ + information_set_lower_bound( + r + 1, + n, + k, + l, + rank_defs, + info_set_alg, + even = even_flag, + doubly_even = doubly_even_flag, + triply_even = triply_even_flag, + ) for r = 1:(k-1) + ] r_term = findfirst(x -> x ≥ C.u_bound, lower_bounds_for_prediction) if isnothing(r_term) - raise(DomainError("Invalid termination r")) + raise(DomainError("Invalid termination r")) end verbose && println("Predicted termination weight based on current upper bound: $r_term") # In the main loop we check if lower bound > upper bound before we enumerate and so the lower bounds for the loop use r not r + 1 - lower_bounds = [information_set_lower_bound(r, n, k, l, rank_defs, info_set_alg, even = even_flag, doubly_even = doubly_even_flag, triply_even = triply_even_flag) for r in 1:k - 1] - - predicted_work_factor = fld(n, k) * sum([binomial(k, i) for i in 1:r_term]) + lower_bounds = [ + information_set_lower_bound( + r, + n, + k, + l, + rank_defs, + info_set_alg, + even = even_flag, + doubly_even = doubly_even_flag, + triply_even = triply_even_flag, + ) for r = 1:(k-1) + ] + + predicted_work_factor = fld(n, k) * sum([binomial(k, i) for i = 1:r_term]) verbose && println("Predicted work factor: $predicted_work_factor") - if show_progress + if show_progress prog_bar = Progress(predicted_work_factor, dt = 1.0, showspeed = true) # updates no faster than once every 1s end # don't understand this but okay weight_sum_bound = min(2 * C.u_bound + 5, n - k) - verbose && println("Codeword weights initially checked on first $weight_sum_bound entries") + verbose && + println("Codeword weights initially checked on first $weight_sum_bound entries") num_thrds = Threads.nthreads() verbose && println("Number of threads ", num_thrds) - for r in 2:k + for r = 2:k # TODO this case should never happen given the error above? if r > 2^16 - verbose && println("Warning: Reached an r larger than 2^16") + verbose && println("Warning: Reached an r larger than 2^16") end C.l_bound < lower_bounds[r] && (C.l_bound = lower_bounds[r];) # I assume we want to uncomment these? @@ -622,41 +729,45 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo if verbose i_count = 0 - for i in 1:h + for i = 1:h r - rank_defs[i] ≤ 0 && (i_count += 1;) end - i_count > 0 && println("$i_count of the original $h information sets no longer contribute to the lower bound") + i_count > 0 && println( + "$i_count of the original $h information sets no longer contribute to the lower bound", + ) end # wait... does this work for nonbinary? cause we do throw an error above if it's not binary p = Int(characteristic(C.F)) - uppers = [C.u_bound for _ in 1:num_thrds] - founds = [found for _ in 1:num_thrds] - exit_thread_indicator_vec = [initial_perm_ind for _ in 1:num_thrds] + uppers = [C.u_bound for _ = 1:num_thrds] + founds = [found for _ = 1:num_thrds] + exit_thread_indicator_vec = [initial_perm_ind for _ = 1:num_thrds] keep_going = Threads.Atomic{Bool}(true) bin = extended_binomial(C.k, r) thrd_stop_msg = "Stopping current thread, main loop finished" - Threads.@threads for ind in 1:num_thrds - len = (ind == num_thrds) ? bin - (num_thrds - 1) * fld(bin, num_thrds) : fld(bin, num_thrds) + Threads.@threads for ind = 1:num_thrds + len = + (ind == num_thrds) ? bin - (num_thrds - 1) * fld(bin, num_thrds) : + fld(bin, num_thrds) # iteration begins with a single matrix multiplication of the generator matrix by first_vec init_rank = 1 + (ind - 1) * fld(bin, num_thrds) first_vec = zeros(Int, k) if init_rank == 1 - for i in 1:r + for i = 1:r first_vec[i] = 1 end else # we shouldn't need the CT. here anymore CodingTheory._subset_unrank_to_vec!(init_rank, UInt64(r), first_vec) end - + # I couldn't figure out why we want to do this but sure # as in White Algo 7.1 we loop over matrices first - for i in 1:h + for i = 1:h if keep_going[] == false verbose && println(thrd_stop_msg) break @@ -675,14 +786,14 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo show_progress && ProgressMeter.next!(prog_bar) if r - rank_defs[i] > 0 - if is_first + if is_first LinearAlgebra.mul!(c_itr, curr_mat, first_vec) @inbounds @simd for j in eachindex(c_itr) c_itr[j] %= p end is_first = false else - for ci in u + for ci in u if ci != -1 @simd for i in eachindex(c_itr) @inbounds c_itr[i] = xor(c_itr[i], curr_mat[i, ci]) @@ -694,27 +805,35 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo partial_weight = r + sum(view(c_itr, 1:weight_sum_bound)) if uppers[ind] > partial_weight - w = r + sum(c_itr) + w = r + sum(c_itr) verbose && @assert w != 0 - if uppers[ind] > w + if uppers[ind] > w subset_vec_full = zeros(Int, k) # CT. - CodingTheory._subset_unrank_to_vec!(UInt128(init_rank + count), UInt64(r), subset_vec_full) + CodingTheory._subset_unrank_to_vec!( + UInt128(init_rank + count), + UInt64(r), + subset_vec_full, + ) - uppers[ind] = w + uppers[ind] = w founds[ind] = vcat(subset_vec_full, c_itr) # is it possible to hit this assert if programmed correctly and checked on one or two runs? - verbose && @assert size(founds[ind], 1) == C.n "found vector has length $(size(founds[ind], 1)) but should be n = $(C.n)" + verbose && + @assert size(founds[ind], 1) == C.n "found vector has length $(size(founds[ind], 1)) but should be n = $(C.n)" exit_thread_indicator_vec[ind] = i - println("Adjusting (local) upper bound: $w for c_itr = $(Int.(c_itr))") + println( + "Adjusting (local) upper bound: $w for c_itr = $(Int.(c_itr))", + ) if C.l_bound == uppers[ind] verbose && println("Early exit") Threads.atomic_cas!(keep_going, true, false) else r_term = findfirst(x -> x ≥ C.u_bound, lower_bounds) isnothing(r_term) && (r_term = k;) - verbose && println("Updated termination weight: $r_term") + verbose && + println("Updated termination weight: $r_term") # can we update the progress meter size here or just maybe add an amount equal to the amount now skipped? end end @@ -742,19 +861,32 @@ function _minimum_distance_BZ(C::AbstractLinearCode, info_set_alg::Symbol, verbo return C.u_bound, y end -function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCode; info_set_alg::Symbol = :auto, - verbose::Bool = false, dbg = Dict()) +function _minimum_distance_enumeration_with_matrix_multiply( + C::AbstractLinearCode; + info_set_alg::Symbol = :auto, + verbose::Bool = false, + dbg = Dict(), +) ord_F = Int(order(C.F)) ord_F == 2 || throw(ArgumentError("Currently only implemented for binary codes.")) - info_set_alg ∈ (:auto, :Brouwer, :Zimmermann, :White, :Chen, :Bouyuklieva, :Edmonds) || throw(ArgumentError("Unknown information set algorithm. Expected `:auto`, `:Brouwer`, `:Zimmermann`, `:White`, `:Chen`, `:Bouyuklieva`, or `:Edmonds`.")) + info_set_alg ∈ (:auto, :Brouwer, :Zimmermann, :White, :Chen, :Bouyuklieva, :Edmonds) || + throw( + ArgumentError( + "Unknown information set algorithm. Expected `:auto`, `:Brouwer`, `:Zimmermann`, `:White`, `:Chen`, `:Bouyuklieva`, or `:Edmonds`.", + ), + ) generator_matrix(C, true) # ensure G_stand exists - if _has_empty_vec(C.G, :cols) + if _has_empty_vec(C.G, :cols) #TODO err string can instruct the user to construct a new code without 0 cols and tell them the function for that - throw(ArgumentError("Codes with standard form of generator matrix having 0 columns not supported")) + throw( + ArgumentError( + "Codes with standard form of generator matrix having 0 columns not supported", + ), + ) end - G = C.G + G = C.G # generate if not pre-stored parity_check_matrix(C) @@ -771,7 +903,8 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod end end # should have no need to permute to find better ranks because of Edmond's? - A_mats, perms_mats, rnks = information_sets(G, info_set_alg, permute = true, only_A = false) + A_mats, perms_mats, rnks = + information_sets(G, info_set_alg, permute = true, only_A = false) A_mats = [deepcopy(_Flint_matrix_to_Julia_int_matrix(Ai)') for Ai in A_mats] perms_mats = [deepcopy(_Flint_matrix_to_Julia_int_matrix(Pi)') for Pi in perms_mats] h = length(A_mats) @@ -780,7 +913,7 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod k, n = size(G) if verbose print("Generated $h information sets with ranks: ") - for i in 1:h + for i = 1:h i == h ? (println(rnks[i]);) : (print("$(rnks[i]), ");) # will only be using the rank deficits here # at the moment, the information sets are always disjoint so the relative @@ -789,7 +922,7 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod rank_defs[i] = C.k - rnks[i] end end - + even_flag = false doubly_even_flag = false triply_even_flag = false @@ -799,20 +932,21 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod if verbose triply_even_flag && println("Detected a triply even code.") (!triply_even_flag && doubly_even_flag) && println("Detected a doubly even code.") - (!triply_even_flag && !doubly_even_flag && even_flag) && println("Detected an even code.") + (!triply_even_flag && !doubly_even_flag && even_flag) && + println("Detected an even code.") end # initial_perm_ind will match the permutation we use for the 'found' vector if the found vector is nonzero. To simplify the code below we're going to choose an initial permutation arbitrarily. - initial_perm_ind = 1 - found = A_mats[1][:, 1] + initial_perm_ind = 1 + found = A_mats[1][:, 1] for (j, g) in enumerate(A_mats) # loop over the A_mats rather than the original G because it would add another case to deal with later # can make this faster with dots and views w, i = _min_wt_col(g) if w <= C.u_bound - found = g[:, i] + found = g[:, i] C.u_bound = w initial_perm_ind = j - y = perms_mats[initial_perm_ind] * found + y = perms_mats[initial_perm_ind] * found end end @@ -820,7 +954,19 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod verbose && !iszero(found) && println("Found element matching upper bound.") info_set_alg == :Chen ? (l = C.l;) : (l = 0;) - lower_bounds = [information_set_lower_bound(r, n, k, l, rank_defs, info_set_alg, even = even_flag, doubly_even = doubly_even_flag, triply_even = triply_even_flag) for r in 1:k] + lower_bounds = [ + information_set_lower_bound( + r, + n, + k, + l, + rank_defs, + info_set_alg, + even = even_flag, + doubly_even = doubly_even_flag, + triply_even = triply_even_flag, + ) for r = 1:k + ] r_term = findfirst(x -> x ≥ C.u_bound, lower_bounds) isnothing(r_term) && (r_term = k;) verbose && println("Predicted termination weight based on current upper bound: $r_term") @@ -829,7 +975,7 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod verbose && println("Detected $num_thrds threads.") power = Int(floor(log(2, num_thrds))) - for r in 1:k + for r = 1:k C.l_bound < lower_bounds[r] && (C.l_bound = lower_bounds[r];) # an even code can't have have an odd minimum weight # (!triply_even_flag && !doubly_even_flag && even_flag) && (C.l_bound += C.l_bound % 2;) @@ -840,46 +986,51 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod verbose && println("Upper bound: $(C.u_bound)") if C.l_bound >= C.u_bound C.d = C.u_bound - y = perms_mats[initial_perm_ind] * found - return C.u_bound, (C.F).(y) + y = perms_mats[initial_perm_ind] * found + return C.u_bound, (C.F).(y) end if verbose count = 0 - for i in 1:h + for i = 1:h r - rank_defs[i] ≤ 0 && (count += 1;) end - count > 0 && println("$count of the original $h information sets no longer contribute to the lower bound") + count > 0 && println( + "$count of the original $h information sets no longer contribute to the lower bound", + ) end flag = Threads.Atomic{Bool}(true) verbose && println("Detected $num_thrds threads.") p = Int(characteristic(C.F)) - uppers = [C.u_bound for _ in 1:num_thrds] - founds = [found for _ in 1:num_thrds] - exit_thread_indicator_vec = [initial_perm_ind for _ in 1:num_thrds] + uppers = [C.u_bound for _ = 1:num_thrds] + founds = [found for _ = 1:num_thrds] + exit_thread_indicator_vec = [initial_perm_ind for _ = 1:num_thrds] c = zeros(Int, C.n) - itrs = [GrayCode(C.k, r, digits(m - 1, base = 2, pad = power), mutate = true) for m in 1:num_thrds] - Threads.@threads for m in 1:num_thrds + itrs = [ + GrayCode(C.k, r, digits(m - 1, base = 2, pad = power), mutate = true) for + m = 1:num_thrds + ] + Threads.@threads for m = 1:num_thrds itr = itrs[m] - for u in itr + for u in itr if flag[] - for i in 1:h + for i = 1:h vec = u - if r - rank_defs[i] > 0 + if r - rank_defs[i] > 0 LinearAlgebra.mul!(c, A_mats[i], vec) w = r - @inbounds for j in 1:n + @inbounds for j = 1:n c[j] % p != 0 && (w += 1;) end if uppers[m] > w uppers[m] = w - founds[m] .= c - exit_thread_indicator_vec[m] = i + founds[m] .= c + exit_thread_indicator_vec[m] = i verbose && println("Adjusting (local) upper bound: $w") if C.l_bound == uppers[m] Threads.atomic_cas!(flag, true, false) @@ -887,7 +1038,8 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod else r_term = findfirst(x -> x ≥ C.u_bound, lower_bounds) isnothing(r_term) && (r_term = k;) - verbose && println("Updated termination weight: $r_term") + verbose && + println("Updated termination weight: $r_term") end end end @@ -905,7 +1057,7 @@ function _minimum_distance_enumeration_with_matrix_multiply(C::AbstractLinearCod # at this point we are guaranteed to have found the answer C.d = C.u_bound - y = perms_mats[initial_perm_ind] * found + y = perms_mats[initial_perm_ind] * found # iszero(C.H * transpose(y)) return C.u_bound, (C.F).(y) end @@ -915,11 +1067,17 @@ end Return all the codewords of `C` of Hamming weight in the range `[l_bound, u_bound]`. """ -function words_of_weight(C::AbstractLinearCode, l_bound::Int, u_bound::Int; verbose::Bool = false) +function words_of_weight( + C::AbstractLinearCode, + l_bound::Int, + u_bound::Int; + verbose::Bool = false, +) ord_F = Int(order(C.F)) ord_F == 2 || throw(ArgumentError("Currently only implemented for binary codes.")) - 1 <= l_bound <= u_bound <= C.n || throw(ArgumentError("Expected 1 <= l_bound <= u_bound <= C.n")) + 1 <= l_bound <= u_bound <= C.n || + throw(ArgumentError("Expected 1 <= l_bound <= u_bound <= C.n")) if l_bound < C.n / 2 && ord_F == 2 # faster to enumerate backwards, but only in binary return _words_of_weight_high(C, l_bound, u_bound, verbose) @@ -941,7 +1099,7 @@ function words_of_weight(C::AbstractLinearCode, l_bound::Int, u_bound::Int; verb rank_defs = zeros(Int, h) if verbose print("Generated $h information sets with ranks: ") - for i in 1:h + for i = 1:h i == h ? (println(gen_mats[i][1]);) : (print("$(gen_mats[i][1]), ")) # will only be using the rank deficits here # at the moment, the information sets are always disjoint so the relative @@ -959,13 +1117,14 @@ function words_of_weight(C::AbstractLinearCode, l_bound::Int, u_bound::Int; verb if verbose triply_even_flag && println("Detected a triply even code.") (!triply_even_flag && doubly_even_flag) && println("Detected a doubly even code.") - (!triply_even_flag && !doubly_even_flag && even_flag) && println("Detected an even code.") + (!triply_even_flag && !doubly_even_flag && even_flag) && + println("Detected an even code.") end num_thrds = Threads.nthreads() verbose && println("Detected $num_thrds threads.") power = 0 - for i in 1:20 + for i = 1:20 if 2^i > num_thrds power = i - 1 break @@ -973,7 +1132,7 @@ function words_of_weight(C::AbstractLinearCode, l_bound::Int, u_bound::Int; verb end W = Set{typeof(G)}() - for r in 1:C.k + for r = 1:C.k if typeof(C) <: AbstractCyclicCode lower = _lower_bounds(r, C.n, C.k, 0, [0], :Chen) elseif typeof(C) <: AbstractQuasiCyclicCode @@ -992,15 +1151,15 @@ function words_of_weight(C::AbstractLinearCode, l_bound::Int, u_bound::Int; verb return W end - Ws = [Set{typeof(G)}() for _ in 1:num_thrds] - Threads.@threads for m in 1:num_thrds + Ws = [Set{typeof(G)}() for _ = 1:num_thrds] + Threads.@threads for m = 1:num_thrds c = zeros(Int, C.n) - prefix = digits(m - 1, base=2, pad=power) - for u in GrayCode(C.k, r, prefix, mutate=true) - for i in 1:h + prefix = digits(m - 1, base = 2, pad = power) + for u in GrayCode(C.k, r, prefix, mutate = true) + for i = 1:h LinearAlgebra.mul!(c, gen_mats_Julia[i], u) w = 0 - @inbounds for j in 1:C.n + @inbounds for j = 1:C.n c[j] % p != 0 && (w += 1;) end @@ -1012,7 +1171,7 @@ function words_of_weight(C::AbstractLinearCode, l_bound::Int, u_bound::Int; verb end end end - for m in 1:num_thrds + for m = 1:num_thrds union!(W, Ws[m]) end end @@ -1023,12 +1182,17 @@ end Return all the codewords of `C` of Hamming weight `bound`. """ -words_of_weight(C::AbstractLinearCode, bound::Int; verbose::Bool = false) = words_of_weight(C, bound, bound, verbose = verbose) +words_of_weight(C::AbstractLinearCode, bound::Int; verbose::Bool = false) = + words_of_weight(C, bound, bound, verbose = verbose) # untested # TODO: figure out if even weight upper weight needs to subtract or not -function _words_of_weight_high(C::AbstractLinearCode, l_bound::Int, u_bound::Int; - verbose::Bool = false) +function _words_of_weight_high( + C::AbstractLinearCode, + l_bound::Int, + u_bound::Int; + verbose::Bool = false, +) p = Int(characteristic(C.F)) G = generator_matrix(C) @@ -1046,7 +1210,7 @@ function _words_of_weight_high(C::AbstractLinearCode, l_bound::Int, u_bound::Int rank_defs = zeros(Int, h) if verbose print("Generated $h information sets with ranks: ") - for i in 1:h + for i = 1:h i == h ? (println(gen_mats[i][1]);) : (print("$(gen_mats[i][1]), ")) # will only be using the rank deficits here # at the moment, the information sets are always disjoint so the relative @@ -1064,13 +1228,14 @@ function _words_of_weight_high(C::AbstractLinearCode, l_bound::Int, u_bound::Int if verbose triply_even_flag && println("Detected a triply even code.") (!triply_even_flag && doubly_even_flag) && println("Detected a doubly even code.") - (!triply_even_flag && !doubly_even_flag && even_flag) && println("Detected an even code.") + (!triply_even_flag && !doubly_even_flag && even_flag) && + println("Detected an even code.") end num_thrds = Threads.nthreads() verbose && println("Detected $num_thrds threads.") power = 0 - for i in 1:20 + for i = 1:20 if 2^i > num_thrds power = i - 1 break @@ -1078,7 +1243,7 @@ function _words_of_weight_high(C::AbstractLinearCode, l_bound::Int, u_bound::Int end W = Set{typeof(G)}() - for r in C.k:-1:1 + for r = C.k:-1:1 if typeof(C) <: AbstractCyclicCode upper = _lower_bounds(r, C.n, C.k, 0, [0], :Chen) elseif typeof(C) <: AbstractQuasiCyclicCode @@ -1097,15 +1262,15 @@ function _words_of_weight_high(C::AbstractLinearCode, l_bound::Int, u_bound::Int return W end - Ws = [Set{typeof(G)}() for _ in 1:num_thrds] - Threads.@threads for m in 1:num_thrds + Ws = [Set{typeof(G)}() for _ = 1:num_thrds] + Threads.@threads for m = 1:num_thrds c = zeros(Int, C.n) - prefix = digits(m - 1, base=2, pad=power) - for u in GrayCode(C.k, r, prefix, mutate=true) - for i in 1:h + prefix = digits(m - 1, base = 2, pad = power) + for u in GrayCode(C.k, r, prefix, mutate = true) + for i = 1:h LinearAlgebra.mul!(c, gen_mats_Julia[i], u) w = 0 - @inbounds for j in 1:C.n + @inbounds for j = 1:C.n c[j] % p != 0 && (w += 1;) end @@ -1117,7 +1282,7 @@ function _words_of_weight_high(C::AbstractLinearCode, l_bound::Int, u_bound::Int end end end - for m in 1:num_thrds + for m = 1:num_thrds union!(W, Ws[m]) end end @@ -1134,19 +1299,23 @@ number of codewords of `C` of Hamming weight `i - 1`. Otherwise, the result is a `Vector{Tuple{Int, BigInt}}` whose entries specify the nonzero indices and values of the above. """ -function partial_weight_distribution(C::AbstractLinearCode, bound::Int; compact::Bool = false) - 1 <= bound <= C.n || throw(ArgumentError("Bound must be between 1 and n.")) - - W = words_of_weight(C, 1, bound) +function partial_weight_distribution( + C::AbstractLinearCode, + bound::Int; + compact::Bool = false, +) + 1 <= bound <= C.n || throw(ArgumentError("Bound must be between 1 and n.")) + + W = words_of_weight(C, 1, bound) wt_dist = zeros(BigInt, bound + 1) bio = BigInt(1) - wt_dist[1] = bio - for c in W - wt_dist[wt(c) + 1] += bio - end - + wt_dist[1] = bio + for c in W + wt_dist[wt(c)+1] += bio + end + if compact - wt_dist_comp = Vector{Tuple{Int, BigInt}}() + wt_dist_comp = Vector{Tuple{Int,BigInt}}() for (i, x) in enumerate(wt_dist) !iszero(x) && (push!(wt_dist_comp, (i - 1, x))) end @@ -1190,7 +1359,7 @@ function minimum_words(C::AbstractLinearCode) rank_defs = zeros(Int, h) if verbose print("Generated $h information sets with ranks: ") - for i in 1:h + for i = 1:h i == h ? (println(gen_mats[i][1]);) : (print("$(gen_mats[i][1]), ")) # will only be using the rank deficits here # at the moment, the information sets are always disjoint so the relative @@ -1198,7 +1367,7 @@ function minimum_words(C::AbstractLinearCode) rank_defs[i] = C.k - gen_mats[i][1] end end - + even_flag = false doubly_even_flag = false triply_even_flag = false @@ -1208,13 +1377,14 @@ function minimum_words(C::AbstractLinearCode) if verbose triply_even_flag && println("Detected a triply even code.") (!triply_even_flag && doubly_even_flag) && println("Detected a doubly even code.") - (!triply_even_flag && !doubly_even_flag && even_flag) && println("Detected an even code.") + (!triply_even_flag && !doubly_even_flag && even_flag) && + println("Detected an even code.") end - + upper = C.n - C.k + 1 verbose && println("Singleton upper bound: $upper") for (j, g) in enumerate(gen_mats_Julia) - for i in 1:C.k + for i = 1:C.k w = wt(g[:, i]) # for transposed matrix if w < upper found = g[:, i] @@ -1229,7 +1399,7 @@ function minimum_words(C::AbstractLinearCode) num_thrds = Threads.nthreads() verbose && println("Detected $num_thrds threads.") power = 0 - for i in 1:20 + for i = 1:20 if 2^i > num_thrds power = i - 1 break @@ -1237,7 +1407,7 @@ function minimum_words(C::AbstractLinearCode) end W = Set{typeof(G)}() - for r in 1:C.k + for r = 1:C.k if typeof(C) <: AbstractCyclicCode lower = _lower_bounds(r, C.n, C.k, 0, [0], :Chen) elseif typeof(C) <: AbstractQuasiCyclicCode @@ -1258,16 +1428,16 @@ function minimum_words(C::AbstractLinearCode) return upper, W end - uppers = [upper for _ in 1:num_thrds] - Ws = [Set{typeof(G)}() for _ in 1:num_thrds] - Threads.@threads for m in 1:num_thrds + uppers = [upper for _ = 1:num_thrds] + Ws = [Set{typeof(G)}() for _ = 1:num_thrds] + Threads.@threads for m = 1:num_thrds c = zeros(Int, C.n) prefix = digits(m - 1, base = 2, pad = power) for u in GrayCode(C.k, r, prefix, mutate = true) - for i in 1:h + for i = 1:h LinearAlgebra.mul!(c, gen_mats_Julia[i], u) w = 0 - @inbounds for j in 1:C.n + @inbounds for j = 1:C.n c[j] % p != 0 && (w += 1;) end @@ -1292,7 +1462,7 @@ function minimum_words(C::AbstractLinearCode) upper = uppers[loc] W = Set{typeof(G)}() end - for m in 1:num_thrds + for m = 1:num_thrds if uppers[m] == upper union!(W, Ws[m]) end @@ -1306,16 +1476,23 @@ end Return an upper bound on the minimum distance of `C` and a codeword of that weight using `max_iters` random information sets. """ -function random_information_set_minimum_distance_bound!(C::AbstractLinearCode; max_iters::Int = 10000, verbose::Bool = false) - - order(field(C)) == 2 || throw(DomainError(C, "Currently only implemented for binary codes.")) - is_positive(max_iters) || throw(DomainError(max_iters, "The number of iterations must be a positive integer.")) +function random_information_set_minimum_distance_bound!( + C::AbstractLinearCode; + max_iters::Int = 10000, + verbose::Bool = false, +) + + order(field(C)) == 2 || + throw(DomainError(C, "Currently only implemented for binary codes.")) + is_positive(max_iters) || throw( + DomainError(max_iters, "The number of iterations must be a positive integer."), + ) !ismissing(C.d) && (println("Distance already known"); return C.d;) verbose && println("Bounding the distance") G = _Flint_matrix_to_Julia_T_matrix(_rref_no_col_swap(C.G), UInt8) G = _remove_empty(G, :rows) - upper, ind = _min_wt_row(G) + upper, ind = _min_wt_row(G) found = G[ind, :] # TODO this can contradict C.u_bound cause that requires a different found verbose && println("Starting lower bound: $(C.l_bound)") @@ -1328,24 +1505,31 @@ function random_information_set_minimum_distance_bound!(C::AbstractLinearCode; m return uppers[loc], matrix(field(C), permutedims(founds[loc])) end -function _RIS_bound_loop(operators_to_reduce::Matrix{T}, curr_l_bound::Int, curr_u_bound::Int, - found::Vector{T}, max_iters::Int, n::Int, verbose::Bool) where T <: Integer +function _RIS_bound_loop( + operators_to_reduce::Matrix{T}, + curr_l_bound::Int, + curr_u_bound::Int, + found::Vector{T}, + max_iters::Int, + n::Int, + verbose::Bool, +) where {T<:Integer} num_thrds = Threads.nthreads() verbose && println("Detected $num_thrds threads.") flag = Threads.Atomic{Bool}(true) - uppers = [curr_u_bound for _ in 1:num_thrds] - founds = [found for _ in 1:num_thrds] + uppers = [curr_u_bound for _ = 1:num_thrds] + founds = [found for _ = 1:num_thrds] thread_load = Int(floor(max_iters / num_thrds)) remaining = max_iters - thread_load * num_thrds verbose && (prog_meter = Progress(max_iters);) - Threads.@threads for t in 1:num_thrds + Threads.@threads for t = 1:num_thrds orig_ops = deepcopy(operators_to_reduce) perm_ops = similar(orig_ops) ops = similar(orig_ops) perm = collect(1:n) - for _ in 1:(thread_load + (t <= remaining ? 1 : 0)) + for _ = 1:(thread_load+(t<=remaining ? 1 : 0)) if flag[] shuffle!(perm) _col_permutation!(perm_ops, orig_ops, perm) @@ -1354,7 +1538,7 @@ function _RIS_bound_loop(operators_to_reduce::Matrix{T}, curr_l_bound::Int, curr for i in axes(perm_ops, 1) w = 0 - @inbounds for j in 1:n + @inbounds for j = 1:n isodd(ops[i, j]) && (w += 1;) end @@ -1363,7 +1547,9 @@ function _RIS_bound_loop(operators_to_reduce::Matrix{T}, curr_l_bound::Int, curr founds[t] .= ops[i, :] verbose && println("Adjusting (thread's local) upper bound: $w") if curr_l_bound == w - verbose && println("Found a logical that matched the lower bound of $curr_l_bound") + verbose && println( + "Found a logical that matched the lower bound of $curr_l_bound", + ) Threads.atomic_cas!(flag, true, false) break end @@ -1379,12 +1565,15 @@ function _RIS_bound_loop(operators_to_reduce::Matrix{T}, curr_l_bound::Int, curr end ############################# - # Weight Enumerators +# Weight Enumerators ############################# # TODO: doc string? function weight_enumerator_classical(T::Trellis; type::Symbol = :complete) - type ∈ (:complete, :Hamming) || - throw(ArgumentError("Unsupported weight enumerator type '$type'. Expected ':complete' or ':Hamming'.")) + type ∈ (:complete, :Hamming) || throw( + ArgumentError( + "Unsupported weight enumerator type '$type'. Expected ':complete' or ':Hamming'.", + ), + ) if type == :complete && !ismissing(T.CWE) return T.CWE @@ -1401,11 +1590,11 @@ function weight_enumerator_classical(T::Trellis; type::Symbol = :complete) E = T.edges V[1][1].polynomial = R(1) # V[1][1].polynomial[1][1] = 1 - for i in 2:length(V) + for i = 2:length(V) for (j, v) in enumerate(V[i]) outer = R(0) - Threads.@threads for e in E[i - 1][j] - inner = deepcopy(V[i - 1][e.outvertex].polynomial) + Threads.@threads for e in E[i-1][j] + inner = deepcopy(V[i-1][e.outvertex].polynomial) for k in e.label inner *= vars[lookup[k]] end @@ -1420,12 +1609,14 @@ function weight_enumerator_classical(T::Trellis; type::Symbol = :complete) if !isshifted(T) && !ismissing(T.code) T.code.weight_enum = T.CWE HWE = CWE_to_HWE(T.CWE) - T.code.d = minimum([collect(exponent_vectors(polynomial(HWE)))[i][1] - for i in 1:length(polynomial(HWE))]) + T.code.d = minimum([ + collect(exponent_vectors(polynomial(HWE)))[i][1] for + i = 1:length(polynomial(HWE)) + ]) end # clean up vertices - for i in 1:length(V) + for i = 1:length(V) for v in V[i] v.polynomial = missing end @@ -1442,18 +1633,33 @@ end Return the weight enumerator of the dual (`:Euclidean` or `:Hermitian`) of `C` obtained by applying the MacWilliams identities to `W`. """ -function MacWilliams_identity(C::AbstractLinearCode, W::WeightEnumerator; dual::Symbol = :Euclidean) - dual ∈ (:Euclidean, :Hermitian) || - throw(ArgumentError("The MacWilliams identities are only programmed for the Euclidean and Hermitian duals.")) - (dual == :Hermitian && Int(order(C.F)) != 4) && - throw(ArgumentError("The MacWilliams identity for the Hermitian dual is only programmed for GF(4).")) +function MacWilliams_identity( + C::AbstractLinearCode, + W::WeightEnumerator; + dual::Symbol = :Euclidean, +) + dual ∈ (:Euclidean, :Hermitian) || throw( + ArgumentError( + "The MacWilliams identities are only programmed for the Euclidean and Hermitian duals.", + ), + ) + (dual == :Hermitian && Int(order(C.F)) != 4) && throw( + ArgumentError( + "The MacWilliams identity for the Hermitian dual is only programmed for GF(4).", + ), + ) if W.type == :Hamming # (1/|C|)W(y - x, y + (q - 1)x) R = parent(W.polynomial) vars = gens(R) - return WeightEnumerator(divexact(W.polynomial(vars[2] - vars[1], vars[2] + - (Int(order(C.F)) - 1) * vars[1]), cardinality(C)), :Hamming) + return WeightEnumerator( + divexact( + W.polynomial(vars[2] - vars[1], vars[2] + (Int(order(C.F)) - 1) * vars[1]), + cardinality(C), + ), + :Hamming, + ) end # complete weight enumerators @@ -1462,21 +1668,35 @@ function MacWilliams_identity(C::AbstractLinearCode, W::WeightEnumerator; dual:: # (1/|C|)W(x_0 + (q - 1)x_1, x_0 - x_1) R = parent(W.polynomial) vars = gens(R) - return WeightEnumerator(divexact(W.polynomial(vars[1] + - (Int(order(C.F)) - 1) * vars[2], vars[1] - vars[2]), - cardinality(C)), :complete) + return WeightEnumerator( + divexact( + W.polynomial(vars[1] + (Int(order(C.F)) - 1) * vars[2], vars[1] - vars[2]), + cardinality(C), + ), + :complete, + ) elseif Int(order(C.F)) == 3 # (1/|C|)W(x_0 + x_1 + x_2, x_0 + ω x_1 + ω^2 x_2, x_0 + ω^2 x_1 + ω x_2) K, ζ = cyclotomic_field(3, :ζ) R, vars = polynomial_ring(K, 3) # might have to switch this here - poly = divexact(W.polynomial( - vars[1] + vars[2] + vars[3], - vars[1] + ζ * vars[2] + ζ^2 * vars[3], - vars[1] + ζ^2 * vars[2] + ζ * vars[3]), cardinality(C)) + poly = divexact( + W.polynomial( + vars[1] + vars[2] + vars[3], + vars[1] + ζ * vars[2] + ζ^2 * vars[3], + vars[1] + ζ^2 * vars[2] + ζ * vars[3], + ), + cardinality(C), + ) # works so far but now needs to recast down to the integer ring - return WeightEnumerator(Oscar.map_coefficients(c -> Nemo.ZZ(coeff(c, 0)), poly, - parent=parent(W.polynomial)), :complete) + return WeightEnumerator( + Oscar.map_coefficients( + c -> Nemo.ZZ(coeff(c, 0)), + poly, + parent = parent(W.polynomial), + ), + :complete, + ) elseif Int(order(C.F)) == 4 # these order 4 formulas are from "Self-Dual Codes" by Rains and Sloane without proof # the differ in order from the formula in MacWilliams and Sloane used in the general @@ -1493,12 +1713,18 @@ function MacWilliams_identity(C::AbstractLinearCode, W::WeightEnumerator; dual:: vars = gens(R) # switched lines 2 and 3 from Rains & Sloane (Huffman & Press) formula because it # appears to implicitly assuming a primitive basis and here we permute for our basis - return WeightEnumerator(divexact(W.polynomial( - vars[1] + vars[2] + vars[3] + vars[4], - vars[1] - vars[2] - vars[3] + vars[4], - vars[1] + vars[2] - vars[3] - vars[4], - vars[1] - vars[2] + vars[3] - vars[4]), cardinality(C)), - :complete) + return WeightEnumerator( + divexact( + W.polynomial( + vars[1] + vars[2] + vars[3] + vars[4], + vars[1] - vars[2] - vars[3] + vars[4], + vars[1] + vars[2] - vars[3] - vars[4], + vars[1] - vars[2] + vars[3] - vars[4], + ), + cardinality(C), + ), + :complete, + ) else # for Hermitian dual # (1/|C|)W(x_0 + x_1 + x_2 + x_3, x_0 + x_1 - x_2 - x_3, x_0 - x_1 + x_2 - x_3, x_0 - x_1 - x_2 + x_3) @@ -1506,12 +1732,18 @@ function MacWilliams_identity(C::AbstractLinearCode, W::WeightEnumerator; dual:: vars = gens(R) # switched lines 2 and 3 from Rains & Sloane (Huffman & Press) formula because it # appears to implicitly assuming a primitive basis and here we permute for our basis - return WeightEnumerator(divexact(W.polynomial( - vars[1] + vars[2] + vars[3] + vars[4], - vars[1] - vars[2] + vars[3] - vars[4], - vars[1] + vars[2] - vars[3] - vars[4], - vars[1] - vars[2] - vars[3] + vars[4]), cardinality(C)), - :complete) + return WeightEnumerator( + divexact( + W.polynomial( + vars[1] + vars[2] + vars[3] + vars[4], + vars[1] - vars[2] + vars[3] - vars[4], + vars[1] + vars[2] - vars[3] - vars[4], + vars[1] - vars[2] - vars[3] + vars[4], + ), + cardinality(C), + ), + :complete, + ) end else q = Int(order(C.F)) @@ -1520,15 +1752,17 @@ function MacWilliams_identity(C::AbstractLinearCode, W::WeightEnumerator; dual:: R, vars = polynomial_ring(K, q) elms = collect(C.F) func_args = [] - for i in 1:q + for i = 1:q inner_sum = R(0) - for j in 1:q + for j = 1:q inner_sum += ω^coeff(elms[i] * elms[j], 0) * vars[j] end append!(func_args, inner_sum) end - return WeightEnumerator(divexact(W.polynomial(func_args), cardinality(C)), - :complete) + return WeightEnumerator( + divexact(W.polynomial(func_args), cardinality(C)), + :complete, + ) else K, ω = cyclotomic_field(Int(characteristic(C.F)), :ω) R, vars = polynomial_ring(K, q) @@ -1536,9 +1770,9 @@ function MacWilliams_identity(C::AbstractLinearCode, W::WeightEnumerator; dual:: _, λ = primitive_basis(C.F, prime_field) elms = collect(C.F) func_args = [] - for i in 1:q + for i = 1:q inner_sum = R(0) - for j in 1:q + for j = 1:q β = elms[i] * elms[j] β_exp = _expand_element(β, prime_field, λ, false) inner_sum += ω^coeff(β_exp[1], 0) * vars[j] @@ -1546,7 +1780,10 @@ function MacWilliams_identity(C::AbstractLinearCode, W::WeightEnumerator; dual:: push!(func_args, inner_sum) end display(func_args) - return WeightEnumerator(divexact(W.polynomial(func_args...), cardinality(C)), :complete) + return WeightEnumerator( + divexact(W.polynomial(func_args...), cardinality(C)), + :complete, + ) end end end @@ -1556,9 +1793,16 @@ end Return either the `:complete` or `:Hamming` weight enumerator of `C` using the algorithm `alg`. """ -function weight_enumerator(C::AbstractLinearCode; type::Symbol = :complete, alg::Symbol = :auto) - type ∈ (:complete, :Hamming) || - throw(ArgumentError("Unsupported weight enumerator type '$type'. Expected ':complete' or ':Hamming'.")) +function weight_enumerator( + C::AbstractLinearCode; + type::Symbol = :complete, + alg::Symbol = :auto, +) + type ∈ (:complete, :Hamming) || throw( + ArgumentError( + "Unsupported weight enumerator type '$type'. Expected ':complete' or ':Hamming'.", + ), + ) alg ∈ (:auto, :trellis, :bruteforce) || throw(ArgumentError("Algorithm `$alg` is not implemented in weight_enumerator.")) @@ -1572,8 +1816,15 @@ function weight_enumerator(C::AbstractLinearCode; type::Symbol = :complete, alg: if cardinality(C) <= 1e6 # random cutoff C.weight_enum = _weight_enumerator_BF(C.G) HWE = CWE_to_HWE(C.weight_enum) - C.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(HWE.polynomial))[i][1] - for i in 1:length(HWE.polynomial)])) + C.d = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(HWE.polynomial))[i][1] for + i = 1:length(HWE.polynomial) + ], + ), + ) type == :Hamming && return HWE return C.weight_enum elseif rate(C) > 0.5 @@ -1581,24 +1832,47 @@ function weight_enumerator(C::AbstractLinearCode; type::Symbol = :complete, alg: if cardinality(D) <= 1e6 # random cutoff D.weight_enum = _weight_enumerator_BF(D.G) else - weight_enumerator_classical(syndrome_trellis(D, "primal", false), type = type) + weight_enumerator_classical( + syndrome_trellis(D, "primal", false), + type = type, + ) end C.weight_enum = MacWilliams_identity(D, D.weight_enum) HWE = CWE_to_HWE(C.weight_enum) - C.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(HWE.polynomial))[i][1] - for i in 1:length(HWE.polynomial)])) + C.d = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(HWE.polynomial))[i][1] for + i = 1:length(HWE.polynomial) + ], + ), + ) type == :Hamming && return HWE return C.weight_enum else - return weight_enumerator_classical(syndrome_trellis(C, "primal", false), type = type) + return weight_enumerator_classical( + syndrome_trellis(C, "primal", false), + type = type, + ) end elseif alg == :trellis - return weight_enumerator_classical(syndrome_trellis(C, "primal", false), type = type) + return weight_enumerator_classical( + syndrome_trellis(C, "primal", false), + type = type, + ) elseif alg == :bruteforce C.weight_enum = _weight_enumerator_BF(C.G) HWE = CWE_to_HWE(C.weight_enum) - C.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(HWE.polynomial))[i][1] - for i in 1:length(HWE.polynomial)])) + C.d = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(HWE.polynomial))[i][1] for + i = 1:length(HWE.polynomial) + ], + ), + ) type == :Hamming && return HWE return C.weight_enum end @@ -1613,7 +1887,11 @@ number of codewords of `C` of Hamming weight `i - 1`. Otherwise, the result is a `Vector{Tuple{Int, BigInt}}` whose entries specify the nonzero indices and values of the above. """ -function weight_distribution(C::AbstractLinearCode; alg::Symbol = :auto, compact::Bool = true) +function weight_distribution( + C::AbstractLinearCode; + alg::Symbol = :auto, + compact::Bool = true, +) alg ∈ (:auto, :trellis, :bruteforce) || throw(ArgumentError("Algorithm `$alg` is not implemented in weight_enumerator.")) @@ -1622,14 +1900,16 @@ function weight_distribution(C::AbstractLinearCode; alg::Symbol = :auto, compact if compact wt_dist = Vector{Tuple}() - for i in 1:length(HWE.polynomial) - push!(wt_dist, (exponent_vector(HWE.polynomial, i)[1], - coeff(HWE.polynomial, i))) + for i = 1:length(HWE.polynomial) + push!( + wt_dist, + (exponent_vector(HWE.polynomial, i)[1], coeff(HWE.polynomial, i)), + ) end else wt_dist = zeros(Int, 1, C.n + 1) - for i in 1:length(HWE.polynomial) - wt_dist[exponent_vector(HWE.polynomial, i)[1] + 1] = coeff(HWE.polynomial, i) + for i = 1:length(HWE.polynomial) + wt_dist[exponent_vector(HWE.polynomial, i)[1]+1] = coeff(HWE.polynomial, i) end end return wt_dist @@ -1653,11 +1933,11 @@ Returns the support of `C`. # Notes - The support of `C` is the collection of nonzero exponents of the Hamming weight enumerator of `C`. """ -support(C::AbstractLinearCode) = [i for (i, _) in weight_distribution(C, alg = :auto, - compact = true)] +support(C::AbstractLinearCode) = + [i for (i, _) in weight_distribution(C, alg = :auto, compact = true)] ############################# - # Minimum Distance +# Minimum Distance ############################# # TODO: update doc strings for these and this whole file in general @@ -1668,33 +1948,54 @@ Return the minimum distance of the linear code if known, otherwise computes it using the algorithm of `alg`. If `alg = "trellis"`, the sectionalization flag `sect` can be set to true to further compactify the reprsentation. """ -function minimum_distance(C::AbstractLinearCode; alg::Symbol = :trellis, sect::Bool = false, - verbose::Bool = false) +function minimum_distance( + C::AbstractLinearCode; + alg::Symbol = :trellis, + sect::Bool = false, + verbose::Bool = false, +) !ismissing(C.d) && return C.d alg ∈ (:auto, :Gray, :trellis, :Leon, :bruteforce, :wt_dist) || throw(ArgumentError("Unexpected algorithm '$alg'.")) - + if alg == :auto D = dual(C) if cardinality(C) <= 1e6 # random cutoff C.weight_enum = _weight_enumerator_BF(C.G) HWE = CWE_to_HWE(C.weight_enum) - C.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(HWE.polynomial))[i][1] - for i in 1:length(HWE.polynomial)])) + C.d = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(HWE.polynomial))[i][1] for + i = 1:length(HWE.polynomial) + ], + ), + ) return C.d elseif rate(C) > 0.5 D = dual(C) if cardinality(D) <= 1e6 # random cutoff D.weight_enum = _weight_enumerator_BF(D.G) else - weight_enumerator_classical(syndrome_trellis(D, "primal", false), type = type) + weight_enumerator_classical( + syndrome_trellis(D, "primal", false), + type = type, + ) end C.weight_enum = MacWilliams_identity(D, D.weight_enum) HWE = CWE_to_HWE(C.weight_enum) - C.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(HWE.polynomial))[i][1] - for i in 1:length(HWE.polynomial)])) + C.d = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(HWE.polynomial))[i][1] for + i = 1:length(HWE.polynomial) + ], + ), + ) return C.d else return minimum_distance_Gray(C, verbose = verbose) @@ -1707,8 +2008,15 @@ function minimum_distance(C::AbstractLinearCode; alg::Symbol = :trellis, sect::B elseif alg == :bruteforce C.weight_enum = _weight_enumerator_BF(C.G) HWE = CWE_to_HWE(C.weight_enum) - C.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(HWE.polynomial))[i][1] - for i in 1:length(HWE.polynomial)])) + C.d = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(HWE.polynomial))[i][1] for + i = 1:length(HWE.polynomial) + ], + ), + ) return C.d elseif alg == :wt_dist HWE = weight_enumerator(C, type = :Hamming, alg = alg) @@ -1716,10 +2024,17 @@ function minimum_distance(C::AbstractLinearCode; alg::Symbol = :trellis, sect::B # this line should only be needed to be run if the weight enumerator is known # but the minimum distance is intentionally set to missing # ordering here can be a bit weird - C.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(HWE.polynomial))[i][1] - for i in 1:length(HWE.polynomial)])) + C.d = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(HWE.polynomial))[i][1] for + i = 1:length(HWE.polynomial) + ], + ), + ) return C.d - # elseif alg == "Leon" - # Leon(C) + # elseif alg == "Leon" + # Leon(C) end end diff --git a/src/Classical/weight_reduction.jl b/src/Classical/weight_reduction.jl index f354722e..4b39c389 100644 --- a/src/Classical/weight_reduction.jl +++ b/src/Classical/weight_reduction.jl @@ -4,28 +4,41 @@ # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. -function _reduce_rows(H::Union{CTMatrixTypes, MatElem{<: ResElem}}, rows::AbstractVector{Int}, - compressed::Bool = false, permute::Bool = false, target::Int = 3) +function _reduce_rows( + H::Union{CTMatrixTypes,MatElem{<: ResElem}}, + rows::AbstractVector{Int}, + compressed::Bool = false, + permute::Bool = false, + target::Int = 3, +) # TODO: for compressed, should use the target weight as well so it can be even more compressed if possible. - compressed && target > 3 && @warn("Compressed weight-reduction for weights greater than 3 not yet implemented.") + compressed && + target > 3 && + @warn("Compressed weight-reduction for weights greater than 3 not yet implemented.") isempty(rows) && return H nr, nc = size(H) if compressed temp = sum(count(!iszero, H[r, :]) - 3 for r in rows) H_new = zero_matrix(base_ring(H), nr + temp, nc + temp) - t_C(n) = matrix(base_ring(H), diagm(n, n - 1, 0 => ones(Int, n - 1), -1 => ones(Int, n - 1))) + t_C(n) = matrix( + base_ring(H), + diagm(n, n - 1, 0 => ones(Int, n - 1), -1 => ones(Int, n - 1)), + ) i = 1 j = nc + 1 - for r in 1:nr + for r = 1:nr if r in rows wt = count(!iszero, H[r, :]) - for (k, p) in enumerate(permute ? shuffle([[i, i + wt - 3]; i:i + wt - 3]) : [[i, i + wt - 3]; i:i + wt - 3]) + for (k, p) in enumerate( + permute ? shuffle([[i, i + wt - 3]; i:(i+wt-3)]) : + [[i, i + wt - 3]; i:(i+wt-3)], + ) columns = getindex.(findall(!iszero, H[r, :]), 2) H_new[p, columns[k]] = H[r, columns[k]] end - H_new[i:i + wt - 3, j:j + wt - 4] = t_C(wt - 2) + H_new[i:(i+wt-3), j:(j+wt-4)] = t_C(wt - 2) i += wt - 2 j += wt - 3 else @@ -36,17 +49,20 @@ function _reduce_rows(H::Union{CTMatrixTypes, MatElem{<: ResElem}}, rows::Abstra else temp = sum(count(!iszero, H[r, :]) - 1 for r in rows) H_new = zero_matrix(base_ring(H), nr + temp, nc + temp) - t(n) = matrix(base_ring(H), diagm(n, n - 1, 0 => ones(Int, n - 1), -1 => ones(Int, n - 1))) + t(n) = matrix( + base_ring(H), + diagm(n, n - 1, 0 => ones(Int, n - 1), -1 => ones(Int, n - 1)), + ) i = 1 j = nc + 1 - for r in 1:nr + for r = 1:nr if r in rows wt = count(!iszero, H[r, :]) - for (k, p) in enumerate(permute ? shuffle(i:i + wt - 1) : i:i + wt - 1) + for (k, p) in enumerate(permute ? shuffle(i:(i+wt-1)) : i:(i+wt-1)) columns = getindex.(findall(!iszero, H[r, :]), 2) H_new[p, columns[k]] = H[r, columns[k]] end - H_new[i:i + wt - 1, j:j + wt - 2] = t(wt) + H_new[i:(i+wt-1), j:(j+wt-2)] = t(wt) i += wt j += wt - 1 else @@ -66,14 +82,25 @@ weight_reduction(H::Union{CTMatrixTypes, MatElem{<: ResElem}}; rows::Bool = true Return the weight-reduced parity-check matrix of `H` with the given arguments. """ -function weight_reduction(H::Union{CTMatrixTypes, MatElem{<: ResElem}}; rows::Bool = true, - row_indices::AbstractVector{Int} = Int[], permute_rows::Bool = true, row_target::Int = 3, - columns::Bool = true, column_indices::AbstractVector{Int} = Int[], permute_columns::Bool = true, - column_target::Int = 3, compressed::Bool = false, seed::Union{Nothing, Int} = nothing) +function weight_reduction( + H::Union{CTMatrixTypes,MatElem{<: ResElem}}; + rows::Bool = true, + row_indices::AbstractVector{Int} = Int[], + permute_rows::Bool = true, + row_target::Int = 3, + columns::Bool = true, + column_indices::AbstractVector{Int} = Int[], + permute_columns::Bool = true, + column_target::Int = 3, + compressed::Bool = false, + seed::Union{Nothing,Int} = nothing, +) # method ∈ (:compressed, :identity) || throw(ArgumentError("Unknown reduction method")) - all(1 <= r <= nrows(H) for r in row_indices) || throw(ArgumentError("Invalid row indices")) - all(1 <= r <= ncols(H) for r in column_indices) || throw(ArgumentError("Invalid col indices")) + all(1 <= r <= nrows(H) for r in row_indices) || + throw(ArgumentError("Invalid row indices")) + all(1 <= r <= ncols(H) for r in column_indices) || + throw(ArgumentError("Invalid col indices")) Random.seed!(seed) if rows @@ -91,7 +118,15 @@ function weight_reduction(H::Union{CTMatrixTypes, MatElem{<: ResElem}}; rows::Bo col_wts, _ = _degree_distribution(H_reduced) column_indices = findall(x -> x > column_target, col_wts) end - H_reduced = transpose(_reduce_rows(transpose(H_reduced), column_indices, compressed, permute_columns, column_target)) + H_reduced = transpose( + _reduce_rows( + transpose(H_reduced), + column_indices, + compressed, + permute_columns, + column_target, + ), + ) end return H_reduced end @@ -104,16 +139,34 @@ weight_reduction(C::Union{AbstractLinearCode, AbstractLDPCCode}; rows::Bool = tr Return the code with the weight-reduced parity-check matrix of `C` with the given arguments. """ -function weight_reduction(C::Union{AbstractLinearCode, AbstractLDPCCode}; rows::Bool = true, - row_indices::AbstractVector{Int} = Int[], permute_rows::Bool = true, row_target::Int = 3, - columns::Bool = true, column_indices::AbstractVector{Int} = Int[], permute_columns::Bool = true, - column_target::Int = 3, compressed::Bool = false, seed::Union{Nothing, Int} = nothing) +function weight_reduction( + C::Union{AbstractLinearCode,AbstractLDPCCode}; + rows::Bool = true, + row_indices::AbstractVector{Int} = Int[], + permute_rows::Bool = true, + row_target::Int = 3, + columns::Bool = true, + column_indices::AbstractVector{Int} = Int[], + permute_columns::Bool = true, + column_target::Int = 3, + compressed::Bool = false, + seed::Union{Nothing,Int} = nothing, +) + + H_reduced = weight_reduction( + parity_check_matrix(C), + rows = rows, + row_indices = row_indices, + permute_rows = permute_rows, + row_target = row_target, + columns = columns, + column_indices = column_indices, + permute_columns = permute_columns, + column_target = column_target, + compressed = compressed, + seed = seed, + ) - H_reduced = weight_reduction(parity_check_matrix(C), rows = rows, row_indices = row_indices, - permute_rows = permute_rows, row_target = row_target, columns = columns, - column_indices = column_indices, permute_columns = permute_columns, - column_target = column_target, compressed = compressed, seed = seed) - if C isa QuasiCyclicCode return QuasiCyclicCode(H_reduced, true) elseif C isa AbstractLinearCode diff --git a/src/CodingTheory.jl b/src/CodingTheory.jl index 621e9988..4b69afdf 100644 --- a/src/CodingTheory.jl +++ b/src/CodingTheory.jl @@ -22,15 +22,49 @@ using ProgressMeter using DocStringExtensions import LinearAlgebra: tr, Adjoint, transpose, kron, diagm -import Oscar: dual, factor, transpose, order, polynomial, nrows, ncols, degree, - lift, quo, vector_space, dimension, extend, support, complement, - is_regular, is_cyclic, genus, density, is_degenerate, index, generators, copy, is_subfield, ⊗, - girth, generator_matrix, polynomial_ring, is_primitive, normal_subgroups, vector_space, - tensor_product, gens, dim, is_isomorphic, field, is_irreducible +import Oscar: + dual, + factor, + transpose, + order, + polynomial, + nrows, + ncols, + degree, + lift, + quo, + vector_space, + dimension, + extend, + support, + complement, + is_regular, + is_cyclic, + genus, + density, + is_degenerate, + index, + generators, + copy, + is_subfield, + ⊗, + girth, + generator_matrix, + polynomial_ring, + is_primitive, + normal_subgroups, + vector_space, + tensor_product, + gens, + dim, + is_isomorphic, + field, + is_irreducible import Oscar.Nemo: exponent_vectors import Oscar.GAP: GapObj, Globals, Packages -import Base: circshift, iseven, show, length, in, zeros, ⊆, /, *, ==, ∩, +, -, copy, isequal, ∘, ∈ -import Combinatorics: powerset +import Base: + circshift, iseven, show, length, in, zeros, ⊆, /, *, ==, ∩, +, -, copy, isequal, ∘, ∈ +import Combinatorics: powerset, combinations import DataStructures: capacity # tilings.jl @@ -43,134 +77,315 @@ else end ############################# - # types.jl +# types.jl ############################# const CTFieldTypes = FinField const CTFieldElem = FinFieldElem -const CTMatrixTypes = Union{fpMatrix, FqMatrix} # MatElem{<:CTFieldElem} +const CTMatrixTypes = Union{fpMatrix,FqMatrix} # MatElem{<:CTFieldElem} const CTPolyRing = PolyRing{<:CTFieldElem} const CTPolyRingElem = PolyRingElem{<:CTFieldElem} -const CTGroupAlgebra = GroupAlgebraElem{fpFieldElem, GroupAlgebra{fpFieldElem, FinGenAbGroup, FinGenAbGroupElem}} +const CTGroupAlgebra = + GroupAlgebraElem{fpFieldElem,GroupAlgebra{fpFieldElem,FinGenAbGroup,FinGenAbGroupElem}} const CTChainComplex = Union{ComplexOfMorphisms{AbstractAlgebra.FPModule{fpFieldElem}}} # residue and group algebras later -const CTPolyMatrix = Union{AbstractAlgebra.Generic.MatSpaceElem{fpPolyRingElem}, AbstractAlgebra.Generic.MatSpaceElem{FqPolyRingElem}} -const CTLRPolyElem = AbstractAlgebra.Generic.LaurentMPolyWrap{fpFieldElem, fpMPolyRingElem, -AbstractAlgebra.Generic.LaurentMPolyWrapRing{fpFieldElem, fpMPolyRing}} +const CTPolyMatrix = Union{ + AbstractAlgebra.Generic.MatSpaceElem{fpPolyRingElem}, + AbstractAlgebra.Generic.MatSpaceElem{FqPolyRingElem}, +} +const CTLRPolyElem = AbstractAlgebra.Generic.LaurentMPolyWrap{ + fpFieldElem, + fpMPolyRingElem, + AbstractAlgebra.Generic.LaurentMPolyWrapRing{fpFieldElem,fpMPolyRing}, +} include("Classical/types.jl") -export AbstractCode, AbstractNonadditiveCode, AbstractNonlinearCode, AbstractAdditiveCode, - AbstractLinearCode, AbstractLDPCCode, AbstractMatrixProductCode, AbstractReedMullerCode, - AbstractCyclicCode, AbstractBCHCode, AbstractReedSolomonCode, AbstractQuasiCyclicCode, - AbstractGeneralizedReedSolomonCode, AbstractAlgebraicGeometryCode, WeightEnumerator, - AbstractAlternateCode, AbstractGoppaCode +export AbstractCode, + AbstractNonadditiveCode, + AbstractNonlinearCode, + AbstractAdditiveCode, + AbstractLinearCode, + AbstractLDPCCode, + AbstractMatrixProductCode, + AbstractReedMullerCode, + AbstractCyclicCode, + AbstractBCHCode, + AbstractReedSolomonCode, + AbstractQuasiCyclicCode, + AbstractGeneralizedReedSolomonCode, + AbstractAlgebraicGeometryCode, + WeightEnumerator, + AbstractAlternateCode, + AbstractGoppaCode include("LDPC/types.jl") -export AbstractLDPCCode, AbstractNoiseChannel, AbstractClassicalNoiseChannel, - AbstractBinaryErasureChannel, AbstractBinarySymmetricChannel, AbstractBAWGNChannel, +export AbstractLDPCCode, + AbstractNoiseChannel, + AbstractClassicalNoiseChannel, + AbstractBinaryErasureChannel, + AbstractBinarySymmetricChannel, + AbstractBAWGNChannel, LDPCEnsemble - # this needs an abstract type +# this needs an abstract type include("Quantum/types.jl") -export AbstractSubsystemCode, AbstractSubsystemCodeCSS, AbstractStabilizerCode, AbstractStabilizerCodeCSS, - AbstractGraphStateSubsystem, AbstractGraphStateSubsystemCSS, AbstractGraphStateStabilizer, - AbstractGraphStateStabilizerCSS, AbstractHypergraphProductCode, AbstractEASubsystemCode, - AbstractEASubsystemCodeCSS, AbstractEAStabilizerCode, AbstractEAStabilizerCodeCSS, AbstractGeneralizedToricCode +export AbstractSubsystemCode, + AbstractSubsystemCodeCSS, + AbstractStabilizerCode, + AbstractStabilizerCodeCSS, + AbstractGraphStateSubsystem, + AbstractGraphStateSubsystemCSS, + AbstractGraphStateStabilizer, + AbstractGraphStateStabilizerCSS, + AbstractHypergraphProductCode, + AbstractEASubsystemCode, + AbstractEASubsystemCodeCSS, + AbstractEAStabilizerCode, + AbstractEAStabilizerCodeCSS, + AbstractGeneralizedToricCode # misc -export LogicalTrait, GaugeTrait, CSSTrait, HasLogicals, HasNoLogicals, HasGauges, HasNoGauges, - IsCSS, IsNotCSS, copy, ChainComplex +export LogicalTrait, + GaugeTrait, + CSSTrait, + HasLogicals, + HasNoLogicals, + HasGauges, + HasNoGauges, + IsCSS, + IsNotCSS, + copy, + ChainComplex ############################# - # utils.jl +# utils.jl ############################# include("utils.jl") -export kronecker_product, Hamming_weight, weight, wt, Hamming_distance, distance, - dist, tr, expand_matrix, symplectic_inner_product, are_symplectic_orthogonal, - Hermitian_inner_product, Hermitian_conjugate_matrix, is_triorthogonal, - print_string_array, print_char_array, print_symplectic_array, pseudoinverse, - quadratic_to_symplectic, symplectic_to_quadratic, _remove_empty, quadratic_residues, - digits_to_int, is_basis, primitive_basis, #polynomial_basis, monomial_basis, - normal_basis, dual_basis, complementary_basis, verify_dual_basis, - verify_complementary_basis, are_equivalent_basis, is_self_dual_basis, - is_primitive_basis, is_normal_basis, is_extension, - is_regular, edge_vertex_incidence_matrix, edge_vertex_incidence_graph, - is_valid_bipartition, extract_bipartition, is_Hermitian_self_orthogonal, - row_supports, row_supports_symplectic, strongly_lower_triangular_reduction, - residue_polynomial_to_circulant_matrix, group_algebra_element_to_circulant_matrix, - load_alist, extended_binomial - # load_alist, _rref_non_pivot_cols - # , _min_wt_row - # , circ_shift - # , lift - # , _process_strings - # , _Pauli_string_to_symplectic - -############################# - # iterators.jl +export kronecker_product, + Hamming_weight, + weight, + wt, + Hamming_distance, + distance, + dist, + tr, + expand_matrix, + symplectic_inner_product, + are_symplectic_orthogonal, + Hermitian_inner_product, + Hermitian_conjugate_matrix, + is_triorthogonal, + print_string_array, + print_char_array, + print_symplectic_array, + pseudoinverse, + quadratic_to_symplectic, + symplectic_to_quadratic, + _remove_empty, + quadratic_residues, + digits_to_int, + is_basis, + primitive_basis, #polynomial_basis, monomial_basis, + normal_basis, + dual_basis, + complementary_basis, + verify_dual_basis, + verify_complementary_basis, + are_equivalent_basis, + is_self_dual_basis, + is_primitive_basis, + is_normal_basis, + is_extension, + is_regular, + edge_vertex_incidence_matrix, + edge_vertex_incidence_graph, + is_valid_bipartition, + extract_bipartition, + is_Hermitian_self_orthogonal, + row_supports, + row_supports_symplectic, + strongly_lower_triangular_reduction, + residue_polynomial_to_circulant_matrix, + group_algebra_element_to_circulant_matrix, + load_alist, + extended_binomial +# load_alist, _rref_non_pivot_cols +# , _min_wt_row +# , circ_shift +# , lift +# , _process_strings +# , _Pauli_string_to_symplectic + +############################# +# iterators.jl ############################# include("iterators.jl") ############################# - # Classical/cyclotomic.jl +# Classical/cyclotomic.jl ############################# include("Classical/cyclotomic.jl") -export ord, cyclotomic_coset, all_cyclotomic_cosets, complement_qcosets, - qcoset_pairings, qcoset_pairings, qcoset_table, dual_qcosets +export ord, + cyclotomic_coset, + all_cyclotomic_cosets, + complement_qcosets, + qcoset_pairings, + qcoset_pairings, + qcoset_table, + dual_qcosets ############################# - # Classical/linear_code.jl +# Classical/linear_code.jl ############################# include("Classical/linear_code.jl") -export LinearCode, field, length, dimension, cardinality, rate, relative_distance, generator_matrix, - parity_check_matrix, genus, Singleton_bound, number_correctable_errors, encode, syndrome, in, ⊆, ⊂, - is_subcode, dual, Hermitian_dual, are_equivalent, is_self_dual, is_self_orthogonal, is_weakly_self_dual, ⊕, - VectorSpace, set_minimum_distance!, permute_code, words, codewords, elements, is_MDS, is_even, - is_doubly_even, is_triply_even, characteristic_polynomial, is_Hermitian_LCD, is_Hermitian_dual_containing, - is_LCD, Hermitian_hull, hull, is_Hermitian_self_dual, is_dual_containing, minimum_distance_lower_bound, - minimum_distance_upper_bound, set_distance_upper_bound!, standard_form_permutation, genus, - is_overcomplete, are_permutation_equivalent, vector_space, contains_self_dual_subcode, information_set, - random_information_set, random_linear_code +export LinearCode, + field, + length, + dimension, + cardinality, + rate, + relative_distance, + generator_matrix, + parity_check_matrix, + genus, + Singleton_bound, + number_correctable_errors, + encode, + syndrome, + in, + ⊆, + ⊂, + is_subcode, + dual, + Hermitian_dual, + are_equivalent, + is_self_dual, + is_self_orthogonal, + is_weakly_self_dual, + ⊕, + VectorSpace, + set_minimum_distance!, + permute_code, + words, + codewords, + elements, + is_MDS, + is_even, + is_doubly_even, + is_triply_even, + characteristic_polynomial, + is_Hermitian_LCD, + is_Hermitian_dual_containing, + is_LCD, + Hermitian_hull, + hull, + is_Hermitian_self_dual, + is_dual_containing, + minimum_distance_lower_bound, + minimum_distance_upper_bound, + set_distance_upper_bound!, + standard_form_permutation, + genus, + is_overcomplete, + are_permutation_equivalent, + vector_space, + contains_self_dual_subcode, + information_set, + random_information_set, + random_linear_code ############################# # Classical/new_codes_from_old.jl ############################# include("Classical/new_codes_from_old.jl") -export code_complement, quo, quotient, /, direct_sum, ⊗, kron, tensor_product, direct_product, ×, - product_code, extend, puncture, expurgate, augment, shorten, lengthen, u_u_plus_v, - Plotkin_construction, subcode, juxtaposition, construction_X, construction_X3, - u_plus_w_v_plus_w_u_plus_v_plus_w, entrywise_product_code, *, Schur_product_code, Hadamard_product_code, - componentwise_product_code, expanded_code, subfield_subcode, trace_code, even_subcode, - doubly_even_subcode, subcode_of_dimension_between_codes - -############################# - # LDPC/codes.jl +export code_complement, + quo, + quotient, + /, + direct_sum, + ⊗, + kron, + tensor_product, + direct_product, + ×, + product_code, + extend, + puncture, + expurgate, + augment, + shorten, + lengthen, + u_u_plus_v, + Plotkin_construction, + subcode, + juxtaposition, + construction_X, + construction_X3, + u_plus_w_v_plus_w_u_plus_v_plus_w, + entrywise_product_code, + *, + Schur_product_code, + Hadamard_product_code, + componentwise_product_code, + expanded_code, + subfield_subcode, + trace_code, + even_subcode, + doubly_even_subcode, + subcode_of_dimension_between_codes + +############################# +# LDPC/codes.jl ############################# include("LDPC/codes.jl") -export LDPCCode, regular_LDPC_code, variable_degree_distribution, check_degree_distribution, - degree_distributions, column_bound, row_bound, column_row_bounds, limited, density, - is_regular, variable_degree_polynomial, check_degree_polynomial, degree_distributions_plot, - girth, computation_graph, enumerate_simple_cycles, simple_cycle_length_distribution, - average_simple_cycle_length, median_simple_cycle_length, - mode_simple_cycle_length, count_simple_cycles, simple_cycle_distribution_by_variable_node, - simple_cycle_distribution_by_variable_node, enumerate_short_cycles, +export LDPCCode, + regular_LDPC_code, + variable_degree_distribution, + check_degree_distribution, + degree_distributions, + column_bound, + row_bound, + column_row_bounds, + limited, + density, + is_regular, + variable_degree_polynomial, + check_degree_polynomial, + degree_distributions_plot, + girth, + computation_graph, + enumerate_simple_cycles, + simple_cycle_length_distribution, + average_simple_cycle_length, + median_simple_cycle_length, + mode_simple_cycle_length, + count_simple_cycles, + simple_cycle_distribution_by_variable_node, + simple_cycle_distribution_by_variable_node, + enumerate_short_cycles, short_cycle_length_distribution, - average_short_cycle_length, median_short_cycle_length, mode_short_cycle_length, - count_short_cycles, short_cycle_distribution_by_variable_node + average_short_cycle_length, + median_short_cycle_length, + mode_short_cycle_length, + count_short_cycles, + short_cycle_distribution_by_variable_node ############################# - # LDPC/cycles.jl +# LDPC/cycles.jl ############################# include("LDPC/cycles.jl") -export remove_cycles, simple_cycle_length_distribution_plot, - simple_cycle_distribution_by_variable_node_plot, short_cycle_length_distribution_plot, - short_cycle_distribution_by_variable_node_plot, ACE_spectrum_plot +export remove_cycles, + simple_cycle_length_distribution_plot, + simple_cycle_distribution_by_variable_node_plot, + short_cycle_length_distribution_plot, + short_cycle_distribution_by_variable_node_plot, + ACE_spectrum_plot # ############################# # # LDPC/algorithms.jl @@ -179,58 +394,96 @@ export remove_cycles, simple_cycle_length_distribution_plot, # include("LDPC/algorithms.jl") ############################# - # LDPC/simulations.jl +# LDPC/simulations.jl ############################# include("LDPC/simulations.jl") export MPNoiseModel ############################# - # LDPC/MP_decoders.jl +# LDPC/MP_decoders.jl ############################# include("LDPC/MP_decoders.jl") -export Gallager_A, Gallager_B, sum_product, sum_product_box_plus, sum_product_syndrome, - min_sum, min_sum_syndrome, min_sum_with_correction, min_sum_with_correction_syndrome, - layered_schedule, balance_of_layered_schedule - +export Gallager_A, + Gallager_B, + sum_product, + sum_product_box_plus, + sum_product_syndrome, + min_sum, + min_sum_syndrome, + min_sum_with_correction, + min_sum_with_correction_syndrome, + layered_schedule, + balance_of_layered_schedule + ############################# - # LDPC/GBP.jl +# LDPC/GBP.jl ############################# include("LDPC/GBP.jl") -export Region, id, parents, ancestors, subregions, descendents, overcounting_number, - counting_number, RegionGraph, regions, base_regions, outer_regions, basic_clusters, leaves, - canonical_region_graph, region_graph_from_base_nodes, region_graph_from_base_nodes, - is_valid_region_graph, remove_zero_overcounting_numbers, leaves - -############################# - # LDPC/LP_decoders.jl +export Region, + id, + parents, + ancestors, + subregions, + descendents, + overcounting_number, + counting_number, + RegionGraph, + regions, + base_regions, + outer_regions, + basic_clusters, + leaves, + canonical_region_graph, + region_graph_from_base_nodes, + region_graph_from_base_nodes, + is_valid_region_graph, + remove_zero_overcounting_numbers, + leaves + +############################# +# LDPC/LP_decoders.jl ############################# include("LDPC/LP_decoders.jl") export LP_decoder_LDPC ############################# - # LDPC/channels.jl +# LDPC/channels.jl ############################# include("LDPC/channels.jl") -export BinaryErasureChannel, BEC, BinarySymmetricChannel, BSC, BAWGNChannel, - BAWGNC, capacity +export BinaryErasureChannel, + BEC, BinarySymmetricChannel, BSC, BAWGNChannel, BAWGNC, capacity ############################# - # LDPC/analysis.jl +# LDPC/analysis.jl ############################# include("LDPC/analysis.jl") -export LDPCEnsemble, erasure_probability, crossover_probability, standard_deviation, variance, - type, density_evolution, density_evolution!, EXIT_chart_plot, multiplicative_gap, - multiplicative_gap_lower_bound, density_lower_bound, check_concentrated_degree_distribution - -export optimal_lambda, optimal_rho, optimal_lambda_and_rho, optimal_threshold, multiplicative_gap, +export LDPCEnsemble, + erasure_probability, + crossover_probability, + standard_deviation, + variance, + type, + density_evolution, + density_evolution!, + EXIT_chart_plot, + multiplicative_gap, + multiplicative_gap_lower_bound, + density_lower_bound, + check_concentrated_degree_distribution + +export optimal_lambda, + optimal_rho, + optimal_lambda_and_rho, + optimal_threshold, + multiplicative_gap, irregular_LDPC_code ############################# @@ -241,41 +494,86 @@ include("Classical/MatrixProductCode.jl") export MatrixProductCode ############################# - # Classical/ReedMuller.jl +# Classical/ReedMuller.jl ############################# include("Classical/ReedMuller.jl") export order, RMr, RMm, ReedMullerCode, number_of_variables ############################# - # Classical/cyclic_code.jl +# Classical/cyclic_code.jl ############################# # TODO is_cyclic exporting weird (removed here) due to Oscar import include("Classical/cyclic_code.jl") -export defining_set, splitting_field, polynomial_ring, primitive_root, offset, - design_distance, qcosets, qcosets_reps, generator_polynomial, parity_check_polynomial, - idempotent, is_primitive, is_narrowsense, is_reversible, find_delta, dual_defining_set, - CyclicCode, BCHCode, ReedSolomonCode, complement, ==, ∩, +, QuadraticResidueCode, - zeros, BCH_bound, is_degenerate, nonzeros, is_antiprimitive, FireCode +export defining_set, + splitting_field, + polynomial_ring, + primitive_root, + offset, + design_distance, + qcosets, + qcosets_reps, + generator_polynomial, + parity_check_polynomial, + idempotent, + is_primitive, + is_narrowsense, + is_reversible, + find_delta, + dual_defining_set, + CyclicCode, + BCHCode, + ReedSolomonCode, + complement, + ==, + ∩, + +, + QuadraticResidueCode, + zeros, + BCH_bound, + is_degenerate, + nonzeros, + is_antiprimitive, + FireCode ############################# # Classical/quasi-cyclic_code.jl ############################# include("Classical/quasi-cyclic_code.jl") -export weight_matrix, base_matrix, protograph_matrix, QuasiCyclicCode, index, - expansion_factor, type, polynomial_matrix, polynomial_matrix_type, - noncirculant_generator_matrix, noncirculant_parity_check_matrix, generators, - circulants, is_single_generator, lift +export weight_matrix, + base_matrix, + protograph_matrix, + QuasiCyclicCode, + index, + expansion_factor, + type, + polynomial_matrix, + polynomial_matrix_type, + noncirculant_generator_matrix, + noncirculant_parity_check_matrix, + generators, + circulants, + is_single_generator, + lift ############################# # Classical/miscknowncodes.jl ############################# include("Classical/misc_known_codes.jl") -export ZeroCode, IdentityCode, RepetitionCode, SingleParityCheckCode, SPCCode, - Hexacode, HammingCode, TetraCode, SimplexCode, GolayCode, ExtendedGolayCode, +export ZeroCode, + IdentityCode, + RepetitionCode, + SingleParityCheckCode, + SPCCode, + Hexacode, + HammingCode, + TetraCode, + SimplexCode, + GolayCode, + ExtendedGolayCode, best_known_linear_code ############################# @@ -283,11 +581,16 @@ export ZeroCode, IdentityCode, RepetitionCode, SingleParityCheckCode, SPCCode, ############################# include("Classical/GRS_alternate.jl") -export GeneralizedReedSolomonCode, scalars, dual_scalars, evaluation_points, AlternateCode, - SrivastavaCode, GeneralizedSrivastavaCode +export GeneralizedReedSolomonCode, + scalars, + dual_scalars, + evaluation_points, + AlternateCode, + SrivastavaCode, + GeneralizedSrivastavaCode ############################# - # Classical/Goppa.jl +# Classical/Goppa.jl ############################# include("Classical/Goppa.jl") @@ -298,54 +601,139 @@ export GoppaCode, Goppa_polynomial, is_seperable, is_cumulative, extension_field ############################# include("Classical/TwistedReedSolomon.jl") -export TwistedReedSolomonCode, twist_vector, hook_vector, coefficient_vector, number_of_twists +export TwistedReedSolomonCode, + twist_vector, hook_vector, coefficient_vector, number_of_twists ############################# # Classical/concatenation.jl ############################# include("Classical/concatenation.jl") -export concatenate, inner_code, outer_code, expansion_basis, expansion_dual_basis, concatenation_type +export concatenate, + inner_code, outer_code, expansion_basis, expansion_dual_basis, concatenation_type ############################# - # Quantum/subsystem_code.jl +# Quantum/subsystem_code.jl ############################# include("Quantum/subsystem_code.jl") -export SubsystemCode, field, length, num_qubits, dimension, cardinality, - rate, signs, X_signs, Z_signs, stabilizers, symplectic_stabilizers, X_stabilizers, Z_stabilizers, - num_X_stabs, num_Z_stabs, character_vector, is_over_complete, is_CSS, relative_distance, logicals, - logical_operators, bare_logicals, bare, logicals_matrix, gauges, gauge_operators, gauges_matrix, - gauge_operators_matrix, dressed, dressed_operators, dressed_logicals, gauge_group, gauge_group_matrix, - gauge_generators_matrix, gauge_group_generators_matrix, set_signs!, set_logicals!, set_minimum_distance!, - split_stabilizers, is_logical, syndrome, X_syndrome, Z_syndrome, promote_logicals_to_gauge!, swap_X_Z_logicals!, - swap_X_Z_gauge_operators!, all_stabilizers, elements, print_all_stabilizers, print_all_elements, - augment, expurgate, fix_gauge, set_X_stabilizers, set_Z_stabilizers, set_stabilizers, - set_Z_stabilizers!, set_distance_lower_bound!, permute_code!, permute_code, set_stabilizers!, - set_X_stabilizers!, standard_form_A, standard_form_A1, standard_form_A2, standard_form_B, standard_form_C1, - standard_form_C2, standard_form_D, standard_form_E, logicals_standard_form, promote_gauges_to_logical!, - promote_gauges_to_logical, promote_logicals_to_gauge, bare_minimum_distance_lower_bound, - bare_minimum_distance_upper_bound, dressed_minimum_distance_lower_bound, - dressed_minimum_distance_upper_bound, bare_X_minimum_distance_lower_bound, - bare_X_minimum_distance_upper_bound, dressed_X_minimum_distance_lower_bound, - bare_Z_minimum_distance_lower_bound, bare_Z_minimum_distance_upper_bound, - dressed_Z_minimum_distance_lower_bound, dressed_Z_minimum_distance_upper_bound, - X_minimum_distance, Z_minimum_distance, XZ_minimum_distance, set_bare_minimum_distance!, - set_bare_X_minimum_distance!, set_bare_Z_minimum_distance!, set_dressed_minimum_distance!, - set_dressed_X_minimum_distance!, set_dressed_Z_minimum_distance! - -############################# - # Quantum/stabilizer_code.jl +export SubsystemCode, + field, + length, + num_qubits, + dimension, + cardinality, + rate, + signs, + X_signs, + Z_signs, + stabilizers, + symplectic_stabilizers, + X_stabilizers, + Z_stabilizers, + num_X_stabs, + num_Z_stabs, + character_vector, + is_over_complete, + is_CSS, + relative_distance, + logicals, + logical_operators, + bare_logicals, + bare, + logicals_matrix, + gauges, + gauge_operators, + gauges_matrix, + gauge_operators_matrix, + dressed, + dressed_operators, + dressed_logicals, + gauge_group, + gauge_group_matrix, + gauge_generators_matrix, + gauge_group_generators_matrix, + set_signs!, + set_logicals!, + set_minimum_distance!, + split_stabilizers, + is_logical, + syndrome, + X_syndrome, + Z_syndrome, + promote_logicals_to_gauge!, + swap_X_Z_logicals!, + swap_X_Z_gauge_operators!, + all_stabilizers, + elements, + print_all_stabilizers, + print_all_elements, + augment, + expurgate, + fix_gauge, + set_X_stabilizers, + set_Z_stabilizers, + set_stabilizers, + set_Z_stabilizers!, + set_distance_lower_bound!, + permute_code!, + permute_code, + set_stabilizers!, + set_X_stabilizers!, + standard_form_A, + standard_form_A1, + standard_form_A2, + standard_form_B, + standard_form_C1, + standard_form_C2, + standard_form_D, + standard_form_E, + logicals_standard_form, + promote_gauges_to_logical!, + promote_gauges_to_logical, + promote_logicals_to_gauge, + bare_minimum_distance_lower_bound, + bare_minimum_distance_upper_bound, + dressed_minimum_distance_lower_bound, + dressed_minimum_distance_upper_bound, + bare_X_minimum_distance_lower_bound, + bare_X_minimum_distance_upper_bound, + dressed_X_minimum_distance_lower_bound, + bare_Z_minimum_distance_lower_bound, + bare_Z_minimum_distance_upper_bound, + dressed_Z_minimum_distance_lower_bound, + dressed_Z_minimum_distance_upper_bound, + X_minimum_distance, + Z_minimum_distance, + XZ_minimum_distance, + set_bare_minimum_distance!, + set_bare_X_minimum_distance!, + set_bare_Z_minimum_distance!, + set_dressed_minimum_distance!, + set_dressed_X_minimum_distance!, + set_dressed_Z_minimum_distance! + +############################# +# Quantum/stabilizer_code.jl ############################# include("Quantum/stabilizer_code.jl") -export StabilizerCodeCSS, CSSCode, StabilizerCode, random_CSS_code, is_CSS_T_code, - minimum_distance_lower_bound, minimum_distance_upper_bound, X_minimum_distance_lower_bound, - X_minimum_distance_upper_bound, Z_minimum_distance_lower_bound, Z_minimum_distance_upper_bound, - set_X_minimum_distance!, set_Z_minimum_distance! +export StabilizerCodeCSS, + CSSCode, + StabilizerCode, + random_CSS_code, + is_CSS_T_code, + minimum_distance_lower_bound, + minimum_distance_upper_bound, + X_minimum_distance_lower_bound, + X_minimum_distance_upper_bound, + Z_minimum_distance_lower_bound, + Z_minimum_distance_upper_bound, + set_X_minimum_distance!, + set_Z_minimum_distance! ############################# - # Quantum/graphstate.jl +# Quantum/graphstate.jl ############################# include("Quantum/graph_state.jl") @@ -357,57 +745,127 @@ export ClusterState, GraphState include("Quantum/misc_known_codes.jl") # subsystem -export GaugedShorCode, Q9143, BaconShorCode, BravyiBaconShorCode, GeneralizedBaconShorCode, - NappPreskill3DCode, NappPreskill4DCode, SubsystemToricCode, SubsystemSurfaceCode +export GaugedShorCode, + Q9143, + BaconShorCode, + BravyiBaconShorCode, + GeneralizedBaconShorCode, + NappPreskill3DCode, + NappPreskill4DCode, + SubsystemToricCode, + SubsystemSurfaceCode # stabilizer -export FiveQubitCode, Q513, SteaneCode, Q713, _SteaneCodeTrellis, ShorCode, Q913, - Q412, Q422, Q511, Q823, Q15RM, Q1513, Q1573, TriangularSurfaceCode, - RotatedSurfaceCode, XZZXSurfaceCode, TriangularColorCode488, TriangularColorCode666, - ToricCode, PlanarSurfaceCode, XYSurfaceCode, XYZ2Code, HCode, QC6, QC4, ToricCode4D, - Q832, SmallestInterestingColorCode, GrossCode #, PlanarSurfaceCode3D, ToricCode3D - -############################# - # trellis.jl +export FiveQubitCode, + Q513, + SteaneCode, + Q713, + _SteaneCodeTrellis, + ShorCode, + Q913, + Q412, + Q422, + Q511, + Q823, + Q15RM, + Q1513, + Q1573, + TriangularSurfaceCode, + RotatedSurfaceCode, + XZZXSurfaceCode, + TriangularColorCode488, + TriangularColorCode666, + ToricCode, + PlanarSurfaceCode, + XYSurfaceCode, + XYZ2Code, + HCode, + QC6, + QC4, + ToricCode4D, + Q832, + SmallestInterestingColorCode, + GrossCode #, PlanarSurfaceCode3D, ToricCode3D + +############################# +# trellis.jl ############################# include("trellis.jl") -export Trellis, vertices, edges, isisomorphic, isequal, loadbalancedecode, - trellisorientedformlinear,trellisprofiles, syndrometrellis, - trellisorientedformadditive, optimalsectionalizationQ, weightQ!, - shiftandweightQ!, shiftanddecodeQ!, shift!, isshifted - -############################# - # Classical/weight_dist.jl +export Trellis, + vertices, + edges, + isisomorphic, + isequal, + loadbalancedecode, + trellisorientedformlinear, + trellisprofiles, + syndrometrellis, + trellisorientedformadditive, + optimalsectionalizationQ, + weightQ!, + shiftandweightQ!, + shiftanddecodeQ!, + shift!, + isshifted + +############################# +# Classical/weight_dist.jl ############################# include("Classical/weight_dist.jl") -export polynomial, type, CWE_to_HWE, weight_enumerator, MacWilliams_identity, - weight_distribution, weight_plot, support, minimum_distance_Gray, minimum_distance, - Sterns_attack, minimum_words, words_of_weight +export polynomial, + type, + CWE_to_HWE, + weight_enumerator, + MacWilliams_identity, + weight_distribution, + weight_plot, + support, + minimum_distance_Gray, + minimum_distance, + Sterns_attack, + minimum_words, + words_of_weight ############################# - # Quantum/weight_dist.jl +# Quantum/weight_dist.jl ############################# include("Quantum/weight_dist.jl") # export weight_plot_CSS_X, weight_plot_CSS_Z, weight_plot_CSS, minimum_distance_X_Z, # minimum_distance_X, minimum_distance_Z, is_pure, QDistRndCSS -export minimum_distance_upper_bound!, random_information_set_minimum_distance_bound!, - QDistRnd! +export minimum_distance_upper_bound!, + random_information_set_minimum_distance_bound!, QDistRnd! ############################# # Quantum/product_codes.jl ############################# include("Quantum/product_codes.jl") -export HypergraphProductCode, GeneralizedShorCode, BaconCasaccinoConstruction, - HyperBicycleCodeCSS, HyperBicycleCode, GeneralizedBicycleCode, - generalized_hypergraph_product_matrices, GHGP_matrices, lifted_product_matrices, - GeneralizedHypergraphProductCode, LiftedProductCode, bias_tailored_lifted_product_matrices, - BiasTailoredLiftedProductCode, SPCDFoldProductCode, SingleParityCheckDFoldProductCode, - Quintavalle_basis, asymmetric_product, symmetric_product, random_homological_product_code, - homological_product, ⊠, BivariateBicycleCode, CoprimeBivariateBicycleCode +export HypergraphProductCode, + GeneralizedShorCode, + BaconCasaccinoConstruction, + HyperBicycleCodeCSS, + HyperBicycleCode, + GeneralizedBicycleCode, + generalized_hypergraph_product_matrices, + GHGP_matrices, + lifted_product_matrices, + GeneralizedHypergraphProductCode, + LiftedProductCode, + bias_tailored_lifted_product_matrices, + BiasTailoredLiftedProductCode, + SPCDFoldProductCode, + SingleParityCheckDFoldProductCode, + Quintavalle_basis, + asymmetric_product, + symmetric_product, + random_homological_product_code, + homological_product, + ⊠, + BivariateBicycleCode, + CoprimeBivariateBicycleCode ############################# # Quantum/simulation.jl @@ -424,23 +882,32 @@ include("Quantum/decoders/OTF.jl") export ordered_Tanner_forest ############################# - # tilings.jl +# tilings.jl ############################# include("tilings.jl") -export ReflectionGroup, triangle_group, r_s_group, tetrahedron_group, q_r_s_group, - star_tetrahedron_group, cycle_tetrahedron_group, normal_subgroups, is_fixed_point_free, - is_orientable, is_k_colorable, coset_intersection +export ReflectionGroup, + triangle_group, + r_s_group, + tetrahedron_group, + q_r_s_group, + star_tetrahedron_group, + cycle_tetrahedron_group, + normal_subgroups, + is_fixed_point_free, + is_orientable, + is_k_colorable, + coset_intersection ############################# - # Classical/Tanner.jl +# Classical/Tanner.jl ############################# include("Classical/Tanner.jl") export Tanner_graph_plot, Tanner_graph, Tanner_code ############################# - # chaincomplex.jl +# chaincomplex.jl ############################# # put into Oscar v14 @@ -465,8 +932,13 @@ export weight_reduction ############################# include("Quantum/weight_reduction.jl") -export copying, gauging, thickening_and_choose_heights, coning, quantum_weight_reduction, - copying_as_coning, gauging_as_coning +export copying, + gauging, + thickening_and_choose_heights, + coning, + quantum_weight_reduction, + copying_as_coning, + gauging_as_coning ############################# @@ -481,7 +953,11 @@ export homological_measurement, Cheeger_constant ############################# include("Quantum/GeneralizedToricCode.jl") -export GeneralizedToricCode, FiniteGeneralizedToricCode, maximum_dimension, - Laurent_polynomial_ring, defining_polynomials, twist_vectors +export GeneralizedToricCode, + FiniteGeneralizedToricCode, + maximum_dimension, + Laurent_polynomial_ring, + defining_polynomials, + twist_vectors end diff --git a/src/Convolutional/convolutional_code.jl b/src/Convolutional/convolutional_code.jl index 64f75a08..0b67341b 100644 --- a/src/Convolutional/convolutional_code.jl +++ b/src/Convolutional/convolutional_code.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -35,8 +35,8 @@ function ConvolutionalCode(G::CTPolyMatrix, parity::Bool = false) # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(H) H_tr = zero_matrix(base_ring(H), rnk_H, nr) - for r in 1:nr - for c in 1:rnk_H + for r = 1:nr + for c = 1:rnk_H !iszero(H[r, c]) && (H_tr[c, r] = H[r, c];) end end @@ -52,8 +52,8 @@ function ConvolutionalCode(G::CTPolyMatrix, parity::Bool = false) n = ncols(G_new) vi = zeros(Int, k) row_degs = zeros(Int, k) - for i in 1:k - row_deg = [degree(G_new[i, c]) for c in 1:n] + for i = 1:k + row_deg = [degree(G_new[i, c]) for c = 1:n] row_degs = sum(row_deg) vi[i] = maximum(row_deg) end @@ -62,11 +62,25 @@ function ConvolutionalCode(G::CTPolyMatrix, parity::Bool = false) mnrs = minors(G_new, k) int_deg = maximum([degree(x) for x in mnrs]) ext_deg = sum(row_degs) - return ConvolutionalCode(base_ring(G_new), n, k, missing, D, m, vi, mnrs, int_deg, ext_deg, G, H, missing) + return ConvolutionalCode( + base_ring(G_new), + n, + k, + missing, + D, + m, + vi, + mnrs, + int_deg, + ext_deg, + G, + H, + missing, + ) end ############################# - # getter functions +# getter functions ############################# """ @@ -147,11 +161,11 @@ Return the external degree of `C`. external_degree(C::AbstractConvolutionalCode) = C.ext_deg ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# """ @@ -183,7 +197,7 @@ function is_basic(C::AbstractConvolutionalCode) SNF, _, _ = snf_with_transform(C.G) # diag elements of SNF are invariant factors # all invariant factors (SNF) are 1 - return all(is_one, [SNF[i, i] for i in 1:k]) + return all(is_one, [SNF[i, i] for i = 1:k]) end # can always make minimal with row ops @@ -195,9 +209,9 @@ Return `true` if the generator matrix of `C` is minimal; otherwise, `false`. function is_minimal(C::AbstractConvolutionalCode) is_basic(C) || return false G_h = zeros(UInt8, C.k, C.n) - for r in 1:C.k + for r = 1:C.k for c in C.n - degree(C.G[r, c]) == C.vi[r] && (G_h[r, c] 1;) + degree(C.G[r, c]) == C.vi[r] && G_h[r, c] == 1 end end return k == rank(G_h) @@ -230,16 +244,16 @@ is_catastrophic(C::AbstractConvolutionalCode) = !is_one(sum(ZZ.(coefficients(gcd Return the generator matrix of `C` if `systematic` is `false` and a systematic generator matrix otherwise. """ -generator_matrix(C::AbstractConvolutionalCode, systematic::Bool = false) = +generator_matrix(C::AbstractConvolutionalCode, systematic::Bool = false) = systematic ? (return hnf(fraction_field(base_ring(C.G)).(C.G));) : (return C.G;) function terminated_generator_matrix(C::AbstractConvolutionalCode, L::Int) L ≥ 1 || throw(DomainError(L, "The number of rows must be at least one.")) - G_mats = [zero_matrix(C.F, C.k, C.n) for _ in 1:C.m] - for r in 1:C.k - for c in 1:C.n - for i in 1:m + G_mats = [zero_matrix(C.F, C.k, C.n) for _ = 1:C.m] + for r = 1:C.k + for c = 1:C.n + for i = 1:m G_mats[m][r, c] = coeff(C.G[r, c], i - 1) end end @@ -247,9 +261,9 @@ function terminated_generator_matrix(C::AbstractConvolutionalCode, L::Int) # this matrix has L shifts and truncates at row L G_L = zero_matrix(C.F, L * C.k, (m + L) * C.n) - for r in 1:L - for c in 1:m - G_L[(r - 1) * C.k + 1:r * C.k, (c - 1 + r - 1) * C.n + 1:(c + r - 1) * C.n] .= G_mats[c] + for r = 1:L + for c = 1:m + G_L[((r-1)*C.k+1):(r*C.k), ((c-1+r-1)*C.n+1):((c+r-1)*C.n)] .= G_mats[c] end end return G_L @@ -257,11 +271,11 @@ end function truncated_generator_matrix(C::AbstractConvolutionalCode, L::Int) L ≥ 1 || throw(DomainError(L, "The number of columns must be at least one.")) - - G_mats = [zero_matrix(C.F, C.k, C.n) for _ in 1:C.m] - for r in 1:C.k - for c in 1:C.n - for i in 1:m + + G_mats = [zero_matrix(C.F, C.k, C.n) for _ = 1:C.m] + for r = 1:C.k + for c = 1:C.n + for i = 1:m G_mats[m][r, c] = coeff(C.G[r, c], i - 1) end end @@ -269,11 +283,11 @@ function truncated_generator_matrix(C::AbstractConvolutionalCode, L::Int) # this matrix truncates at column L G_L = zeros(C.F, L * C.k, L * C.n) - for offset in 0:min(C.m - 1, L) - for i in 1:L - offset + for offset = 0:min(C.m-1, L) + for i = 1:(L-offset) rows = (1:C.k) .+ ((i - 1) * C.k) cols = (1:C.n) .+ ((offset + i - 1) * C.n) - G_L[rows, cols] .= G_mats[offset + 1] + G_L[rows, cols] .= G_mats[offset+1] end end return G_L @@ -282,10 +296,10 @@ end function tail_biting_generator_matrix(C::AbstractConvolutionalCode, L::Int) L ≥ 1 || throw(DomainError(L, "The number of columns must be at least one.")) - G_mats = [zero_matrix(C.F, C.k, C.n) for _ in 1:C.m] - for r in 1:C.k - for c in 1:C.n - for i in 1:m + G_mats = [zero_matrix(C.F, C.k, C.n) for _ = 1:C.m] + for r = 1:C.k + for c = 1:C.n + for i = 1:m G_mats[m][r, c] = coeff(C.G[r, c], i - 1) end end @@ -293,15 +307,15 @@ function tail_biting_generator_matrix(C::AbstractConvolutionalCode, L::Int) # this matrix has L shifts and truncates at row L G_L = zero_matrix(C.F, L * C.k, L * C.n) - for r in 1:L - for c in 1:m + for r = 1:L + for c = 1:m if c - 1 + r - 1 ≤ L if c + r - 2 > L - cols = ((c - 1 + r - 1) % L) * C.n + 1:((c + r - 1) % L) * C.n + cols = (((c-1+r-1)%L)*C.n+1):(((c+r-1)%L)*C.n) else - cols = (c - 1 + r - 1) * C.n + 1:(c + r - 1) * C.n + cols = ((c-1+r-1)*C.n+1):((c+r-1)*C.n) end - G_L[(r - 1) * C.k + 1:r * C.k, cols] .= G_mats[c] + G_L[((r-1)*C.k+1):(r*C.k), cols] .= G_mats[c] end end end @@ -328,8 +342,16 @@ function show(io::IO, C::AbstractConvolutionalCode) println(io, "Constraint length: $(overall_constraint_length(C))") if C.n ≤ 10 println(io, "Generator matrix: $(C.k) × $(C.n)") - println(io, "\t" * replace(replace(replace(repr(MIME("text/plain"), C.G), - r"\n" => "\n\t"), r"\[" => ""), r"\]" => "")) + println( + io, + "\t" * replace( + replace( + replace(repr(MIME("text/plain"), C.G), r"\n" => "\n\t"), + r"\[" => "", + ), + r"\]" => "", + ), + ) end # if !ismissing(C.weight_enum) # println(io, "\nComplete weight enumerator:") @@ -344,9 +366,13 @@ end Return the encoding of `v` into `C`. """ function encode(C::AbstractConvolutionalCode, v::CTPolyMatrix) - (size(v) != (1, C.k) && size(v) != (C.k, 1)) && - throw(ArgumentError("Vector has incorrect dimension; expected length $(C.k), received: $(size(v)).")) - parent(v) == parent(C.G) || throw(ArgumentError("Vector must have the same parent as the generator matrix.")) + (size(v) != (1, C.k) && size(v) != (C.k, 1)) && throw( + ArgumentError( + "Vector has incorrect dimension; expected length $(C.k), received: $(size(v)).", + ), + ) + parent(v) == parent(C.G) || + throw(ArgumentError("Vector must have the same parent as the generator matrix.")) nrows(v) ≠ 1 || return v * C.G return transpose(v) * C.G end @@ -363,4 +389,3 @@ end # interleave::Bool # scalar and polynomial versions # syndrome - diff --git a/src/Convolutional/types.jl b/src/Convolutional/types.jl index a065469d..659643a7 100644 --- a/src/Convolutional/types.jl +++ b/src/Convolutional/types.jl @@ -5,39 +5,39 @@ # LICENSE file in the root directory of this source tree. ############################# - # abstract types +# abstract types ############################# abstract type AbstractCode end abstract type AbstractConvolutionalCode <: AbstractCode end ############################# - # concrete types +# concrete types ############################# ############################# - # convolutional_code.jl +# convolutional_code.jl ############################# struct PathEnumerator - polynomial::Union{ZZMPolyRingElem, Nemo.AbsSimpleNumFieldElem} - type::Symbol + polynomial::Union{ZZMPolyRingElem,Nemo.AbsSimpleNumFieldElem} + type::Symbol end - + mutable struct ConvolutionalCode <: AbstractConvolutionalCode F::CTFieldTypes # base field n::Int # length k::Int # dimension - d::Union{Int, Missing} # free distance + d::Union{Int,Missing} # free distance # l_bound::Int # lower bound on d # u_bound::Int # upper bound on d D::CTFieldElem # delay operator m::Int # memory vi::Vector{Int} # constraint lengths - mnrs::Union{Vector{fqPolyRingElem}, Vector{FqPolyRingElem}} + mnrs::Union{Vector{fqPolyRingElem},Vector{FqPolyRingElem}} int_deg::Int # interal degree ext_deg::Int # external degree G::CTPolyMatrix H::CTPolyMatrix - path_enum::Union{PathEnumerator, Missing} + path_enum::Union{PathEnumerator,Missing} end diff --git a/src/LDPC/GBP.jl b/src/LDPC/GBP.jl index 9063053c..566a89ab 100644 --- a/src/LDPC/GBP.jl +++ b/src/LDPC/GBP.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # Region Graphs +# Region Graphs ############################# mutable struct Region @@ -19,16 +19,31 @@ mutable struct Region # size of parents, element is indices of parent marginalized to get child (this) missing_parent_indices::Vector{Vector{Int}} # size of parents, element is numerator for each edge in (region index, parent index) pairs - message_numerators::Vector{Vector{Tuple{Int, Int}}} + message_numerators::Vector{Vector{Tuple{Int,Int}}} # size of parents, element is denominator for each edge in (region index, parent index) pairs - message_denominators::Vector{Vector{Tuple{Int, Int}}} + message_denominators::Vector{Vector{Tuple{Int,Int}}} end -Region(id::Vector{Int}) = Region(id, Vector{Region}(), Vector{Region}(), Vector{Region}(), 1, - Vector{Vector{Int}}(), Vector{Vector{Tuple{Int, Int}}}(), Vector{Vector{Tuple{Int, Int}}}()) -Region(id::Vector{Int}, c_r::Int) = Region(id, Vector{Region}(), Vector{Region}(), - Vector{Region}(), c_r, Vector{Vector{Int}}(), Vector{Vector{Tuple{Int, Int}}}(), - Vector{Vector{Tuple{Int, Int}}}()) +Region(id::Vector{Int}) = Region( + id, + Vector{Region}(), + Vector{Region}(), + Vector{Region}(), + 1, + Vector{Vector{Int}}(), + Vector{Vector{Tuple{Int,Int}}}(), + Vector{Vector{Tuple{Int,Int}}}(), +) +Region(id::Vector{Int}, c_r::Int) = Region( + id, + Vector{Region}(), + Vector{Region}(), + Vector{Region}(), + c_r, + Vector{Vector{Int}}(), + Vector{Vector{Tuple{Int,Int}}}(), + Vector{Vector{Tuple{Int,Int}}}(), +) id(r::Region) = r.id label(r::Region) = id(r) @@ -45,7 +60,7 @@ message_denominators(r::Region) = r.message_denominators message_denominators(r::Region, i::Int) = r.message_denominators[i] function ==(r1::Region, r2::Region) -# do this entirely in terms of id's at every comparison + # do this entirely in terms of id's at every comparison end @@ -63,9 +78,9 @@ leaves(R::RegionGraph) = [r for r in R.regions if isempty(r.subregions)] function canonical_region_graph(H::CTMatrixTypes) num_check, num_var = size(H) - check_adj_list = [Int[] for _ in 1:num_check] - for r in 1:num_check - for c in 1:num_var + check_adj_list = [Int[] for _ = 1:num_check] + for r = 1:num_check + for c = 1:num_var iszero(H[r, c]) || push!(check_adj_list[r], c) end end @@ -79,8 +94,8 @@ function region_graph_from_base_nodes(regions::Vector{Region}) left = 1 right = length(regions) while left < right - for r1 in left:right - 1 - for r2 in left + 1:right + for r1 = left:(right-1) + for r2 = (left+1):right if r1 ≠ r2 cap = regions[r1].id ∩ regions[r2].id if !isempty(cap) && cap ≠ regions[r1].id && cap ≠ regions[r2].id @@ -103,8 +118,13 @@ function region_graph_from_base_nodes(regions::Vector{Region}) #### TODO here find missing labels between parents and child - - r.ancestors = unique!(reduce(vcat, [[r3.ancestors for r3 in r.parents]; r.parents])) + + r.ancestors = unique!( + reduce( + vcat, + [[r3.ancestors for r3 in r.parents]; r.parents], + ), + ) # do I want to blank this out? # r.subregions = Vector{Region}() @@ -116,15 +136,30 @@ function region_graph_from_base_nodes(regions::Vector{Region}) end if !found - ancestors = unique!([regions[r1].ancestors; regions[r2].ancestors; [regions[r1], regions[r2]]]) + ancestors = unique!( + [ + regions[r1].ancestors; + regions[r2].ancestors; + [regions[r1], regions[r2]] + ], + ) c_r = 1 for r3 in ancestors c_r -= r3.overcounting_number end - push!(regions, Region(cap, [regions[r1], regions[r2]], ancestors, Vector{Region}(), c_r)) - + push!( + regions, + Region( + cap, + [regions[r1], regions[r2]], + ancestors, + Vector{Region}(), + c_r, + ), + ) + # can we combine this with the above loop? for r3 in ancestors push!(r3.subregions, regions[end]) @@ -271,6 +306,5 @@ end # end ############################# - # GBP +# GBP ############################# - diff --git a/src/LDPC/LP_decoders.jl b/src/LDPC/LP_decoders.jl index 1e260489..6e0d193e 100644 --- a/src/LDPC/LP_decoders.jl +++ b/src/LDPC/LP_decoders.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # LP Decoders +# LP Decoders ############################# # function _init_LP_decoder_LDPC end diff --git a/src/LDPC/MP_decoders.jl b/src/LDPC/MP_decoders.jl index b79679c2..6d7438e3 100644 --- a/src/LDPC/MP_decoders.jl +++ b/src/LDPC/MP_decoders.jl @@ -5,42 +5,89 @@ # LICENSE file in the root directory of this source tree. ############################# - # Gallager +# Gallager ############################# -function _Gallager_A_check_node_message(c::Int, v::Int, iter::Int, check_adj_list::Vector{Vector{Int}}, - var_to_check_messages::Array{Int, 3}, attenuation::Float64) - - @inbounds reduce(⊻, var_to_check_messages[v2, c, iter] for v2 in check_adj_list[c] if v2 != v) +function _Gallager_A_check_node_message( + c::Int, + v::Int, + iter::Int, + check_adj_list::Vector{Vector{Int}}, + var_to_check_messages::Array{Int,3}, + attenuation::Float64, +) + + @inbounds reduce( + ⊻, + var_to_check_messages[v2, c, iter] for v2 in check_adj_list[c] if v2 != v + ) end -_Gallager_B_check_node_message(c::Int, v::Int, iter::Int, check_adj_list::Vector{Vector{Int}}, var_to_check_messages, - attenuation::Float64) = _Gallager_A_check_node_message(c, v, iter, check_adj_list, - var_to_check_messages, attenuation) +_Gallager_B_check_node_message( + c::Int, + v::Int, + iter::Int, + check_adj_list::Vector{Vector{Int}}, + var_to_check_messages, + attenuation::Float64, +) = _Gallager_A_check_node_message( + c, + v, + iter, + check_adj_list, + var_to_check_messages, + attenuation, +) """ Gallager_A(H::T, v::T; max_iter::Int = 100, schedule::Symbol = :parallel) where T <: CTMatrixTypes Run the Gallager-A decoder with the parity-check matrix `H` and received vector `v`. """ -function Gallager_A(H::T, v::T; max_iter::Int = 100, schedule::Symbol = :parallel) where T <: - CTMatrixTypes +function Gallager_A( + H::T, + v::T; + max_iter::Int = 100, + schedule::Symbol = :parallel, +) where {T<:CTMatrixTypes} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) + (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && + throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial) || throw(ArgumentError("Unknown schedule algorithm")) + schedule ∈ (:flooding, :parallel, :serial) || + throw(ArgumentError("Unknown schedule algorithm")) schedule == :parallel && (schedule = :flooding;) # initialization - do these outside to reduce allocations when looped - H_Int, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, var_to_check_messages, - current_bits, syn = _message_passing_init_Int(H, v, max_iter, :A, 2, schedule, Int[]) - - return _message_passing_Int(H_Int, missing, chn_inits_2, _Gallager_A_check_node_message, - var_adj_list, check_adj_list, max_iter, :A, schedule, current_bits, syn, - check_to_var_messages, var_to_check_messages, 0) + H_Int, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn = _message_passing_init_Int(H, v, max_iter, :A, 2, schedule, Int[]) + + return _message_passing_Int( + H_Int, + missing, + chn_inits_2, + _Gallager_A_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :A, + schedule, + current_bits, + syn, + check_to_var_messages, + var_to_check_messages, + 0, + ) end # TODO: threshold in docstring @@ -49,34 +96,66 @@ end Run the Gallager-B decoder with the parity-check matrix `H` and received vector `v`. """ -function Gallager_B(H::T, v::T; max_iter::Int = 100, threshold::Int = 2, schedule::Symbol = - :flooding) where T <: CTMatrixTypes - - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) +function Gallager_B( + H::T, + v::T; + max_iter::Int = 100, + threshold::Int = 2, + schedule::Symbol = :flooding, +) where {T<:CTMatrixTypes} + + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) + (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && + throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial) || throw(ArgumentError("Unknown schedule algorithm")) + schedule ∈ (:flooding, :parallel, :serial) || + throw(ArgumentError("Unknown schedule algorithm")) schedule == :parallel && (schedule = :flooding;) # initialization - do these outside to reduce allocations when looped - H_Int, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, var_to_check_messages, - current_bits, syn = _message_passing_init_Int(H, v, max_iter, :B, threshold, schedule, - Int[]) - - return _message_passing_Int(H_Int, missing, chn_inits_2, _Gallager_B_check_node_message, - var_adj_list, check_adj_list, max_iter, :B, schedule, current_bits, syn, - check_to_var_messages, var_to_check_messages, threshold) + H_Int, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn = _message_passing_init_Int(H, v, max_iter, :B, threshold, schedule, Int[]) + + return _message_passing_Int( + H_Int, + missing, + chn_inits_2, + _Gallager_B_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :B, + schedule, + current_bits, + syn, + check_to_var_messages, + var_to_check_messages, + threshold, + ) end ############################# - # Sum product +# Sum product ############################# -function _SP_check_node_message(c::Int, v::Int, iter::Int, check_adj_list::Vector{Vector{Int}}, var_to_check_messages::Array{Float64, 3}, - attenuation::Float64) +function _SP_check_node_message( + c::Int, + v::Int, + iter::Int, + check_adj_list::Vector{Vector{Int}}, + var_to_check_messages::Array{Float64,3}, + attenuation::Float64, +) # TODO why does the other one produce NaN ϕ(x) = -log(tanh(0.5 * x)) @@ -97,7 +176,7 @@ function _SP_check_node_message(c::Int, v::Int, iter::Int, check_adj_list::Vecto return s * ϕ(temp) end -function ϕ_test(x::Real) +function ϕ_test(x::Real) # TODO why does the other one produce NaN x >= 0 ? (return -log(tanh(0.5 * x));) : (return log(tanh(-0.5 * x));) # x >= 0 ? (return log((exp(x) + 1)/(exp(x) - 1));) : (return -log((exp(-x) + 1)/(exp(-x) - 1));) @@ -105,8 +184,14 @@ end ⊞(a::Float64, b::Float64) = log((1 + exp(a + b)) / (exp(a) + exp(b))) ⊞(a...) = reduce(⊞, a...) -function _SP_check_node_message_box_plus(c::Int, v::Int, iter::Int, check_adj_list::Vector{Vector{Int}}, - var_to_check_messages::Array{Float64, 3}, attenuation::Float64) +function _SP_check_node_message_box_plus( + c::Int, + v::Int, + iter::Int, + check_adj_list::Vector{Vector{Int}}, + var_to_check_messages::Array{Float64,3}, + attenuation::Float64, +) @inbounds ⊞(var_to_check_messages[v2, c, iter] for v2 in check_adj_list[c] if v2 != v) end @@ -121,33 +206,68 @@ Run the sum-product algorithm with the parity-check matrix `H`, received vector - Use `chn_inits` to pass in soft information. - The options for `schedule` are `:parallel` (`:flooding`), `:serial`, or `:layered` (`:semiserial`). """ -function sum_product(H::T, v::T, chn::AbstractClassicalNoiseChannel; max_iter::Int = 100, chn_inits::Union{Missing, - Vector{Float64}} = missing, schedule::Symbol = :parallel, rand_sched::Bool = false, - erasures::Vector{Int} = Int[]) where T <: CTMatrixTypes +function sum_product( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel; + max_iter::Int = 100, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) # (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) - H_Int, v_Int, syndrome_based, check_adj_list, check_to_var_messages, var_to_check_messages, - current_bits, syn = _message_passing_init_fast(H, v, chn, :SP, chn_inits, :serial, erasures) + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn = _message_passing_init_fast(H, v, chn, :SP, chn_inits, :serial, erasures) if schedule == :layered # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - return _message_passing_fast_layered(H_Int, v_Int, syndrome_based, check_adj_list, - check_to_var_messages, var_to_check_messages, current_bits, syn, ϕ_test, ϕ_test, - max_iter, layers) + return _message_passing_fast_layered( + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn, + ϕ_test, + ϕ_test, + max_iter, + layers, + ) else - return _message_passing_fast(H_Int, v_Int, syndrome_based, check_adj_list, - check_to_var_messages, var_to_check_messages, current_bits, syn, ϕ_test, ϕ_test, - max_iter) + return _message_passing_fast( + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn, + ϕ_test, + ϕ_test, + max_iter, + ) end end @@ -161,29 +281,59 @@ channel `chn`. - Use `chn_inits` to pass in soft information. - The options for `schedule` are `:parallel` (`:flooding`), `:serial`, or `:layered` (`:semiserial`). """ -function sum_product_box_plus(H::T, v::T, chn::AbstractClassicalNoiseChannel; max_iter::Int = 100, - chn_inits::Union{Missing, Vector{Float64}} = missing, schedule::Symbol = :parallel, - rand_sched::Bool = false, erasures::Vector{Int} = Int[]) where T <: CTMatrixTypes +function sum_product_box_plus( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel; + max_iter::Int = 100, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) + (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && + throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, _, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, v, chn, - :SP, chn_inits, schedule, erasures) - return _message_passing_layered(H_Int, missing, chn_inits_2, - _SP_check_node_message_box_plus, var_adj_list, check_adj_list, max_iter, schedule, - current_bits, totals, syn, check_to_var_messages, var_to_check_messages, 0.0, layers) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init(H, v, chn, :SP, chn_inits, schedule, erasures) + return _message_passing_layered( + H_Int, + missing, + chn_inits_2, + _SP_check_node_message_box_plus, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + 0.0, + layers, + ) end """ @@ -196,70 +346,149 @@ and channel `chn`. - Use `chn_inits` to pass in soft information. - The options for `schedule` are `:parallel` (`:flooding`), `:serial`, or `:layered` (`:semiserial`). """ -function sum_product_syndrome(H::T, syndrome::T, chn::AbstractClassicalNoiseChannel; max_iter::Int = 100, - chn_inits::Union{Missing, Vector{Float64}} = missing, schedule::Symbol = :parallel, - rand_sched::Bool = false, erasures::Vector{Int} = Int[]) where T <: CTMatrixTypes +function sum_product_syndrome( + H::T, + syndrome::T, + chn::AbstractClassicalNoiseChannel; + max_iter::Int = 100, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(syndrome) ≠ (nr, 1) && size(syndrome) ≠ (1, nr)) && throw(ArgumentError("Syndrome has incorrect dimension")) + (size(syndrome) ≠ (nr, 1) && size(syndrome) ≠ (1, nr)) && + throw(ArgumentError("Syndrome has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, _, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, - syndrome, chn, :SP, chn_inits, schedule, erasures) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init(H, syndrome, chn, :SP, chn_inits, schedule, erasures) syn_Int = _Flint_matrix_to_Julia_int_vector(syndrome) - return _message_passing_layered(H_Int, syn_Int, chn_inits_2, _SP_check_node_message, - var_adj_list, check_adj_list, max_iter, schedule, current_bits, totals, syn, - check_to_var_messages, var_to_check_messages, 0.0, layers) + return _message_passing_layered( + H_Int, + syn_Int, + chn_inits_2, + _SP_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + 0.0, + layers, + ) end # believe this can be merged into an optional argument of the above but keep for now so as not to break working code -function sum_product_decimation(H::T, v::T, chn::AbstractClassicalNoiseChannel, algorithm::Symbol; - decimated_bits_values::Vector{Tuple{Int, S}} = Tuple{Int, S}[], max_iter::Int = 100, - chn_inits::Union{Missing, Vector{Float64}} = missing, schedule::Symbol = :parallel, - rand_sched::Bool = false, guided_rounds::Int = 10, erasures::Vector{Int} = Int[]) where {T <: - CTMatrixTypes, S <: CTFieldElem} +function sum_product_decimation( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel, + algorithm::Symbol; + decimated_bits_values::Vector{Tuple{Int,S}} = Tuple{Int,S}[], + max_iter::Int = 100, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + guided_rounds::Int = 10, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes,S<:CTFieldElem} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) + (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && + throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) - algorithm ∈ (:auto, :manual, :guided) || throw(ArgumentError("Unknown decimation algorithm")) + algorithm ∈ (:auto, :manual, :guided) || + throw(ArgumentError("Unknown decimation algorithm")) (algorithm == :manual && !isempty(decimated_bits_values)) || throw(ArgumentError("Manual decimation but no decimated bits and values provided")) # unclear how to interpret passed in values if auto or guided is set, so ignore - (algorithm == :auto || algorithm == :guided) && (decimated_bits_values = Tuple{Int, S}[];) + (algorithm == :auto || algorithm == :guided) && + (decimated_bits_values = Tuple{Int,S}[];) if algorithm == :guided - guided_rounds > 0 || throw(DomainError("The number of rounds before decimation must be positive")) + guided_rounds > 0 || + throw(DomainError("The number of rounds before decimation must be positive")) end # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, w, var_adj_list, check_adj_list, chn_inits_2, decimated_bits, decimated_values, - check_to_var_messages, var_to_check_messages, current_bits, totals, syn = - _message_passing_init_decimation(H, v, chn, decimated_bits_values, :SP, 2, - chn_inits, schedule, erasures) + H_Int, + w, + var_adj_list, + check_adj_list, + chn_inits_2, + decimated_bits, + decimated_values, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init_decimation( + H, + v, + chn, + decimated_bits_values, + :SP, + 2, + chn_inits, + schedule, + erasures, + ) # TODO layers - return _message_passing_decimation(H_Int, w, chn_inits_2, _SP_check_node_message, - var_adj_list, check_adj_list, max_iter, :SP, schedule, decimated_bits, decimated_values, - current_bits, totals, syn, check_to_var_messages, var_to_check_messages, 0, 0.0, algorithm, - guided_rounds) + return _message_passing_decimation( + H_Int, + w, + chn_inits_2, + _SP_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :SP, + schedule, + decimated_bits, + decimated_values, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + 0, + 0.0, + algorithm, + guided_rounds, + ) end # decimation, guided decimation, automatic decimation @@ -267,16 +496,23 @@ end # syndrome-based decimation ############################# - # Min Sum +# Min Sum ############################# box_plus_min(a::Float64, b::Float64) = sign(a) * sign(b) * min(abs(a), abs(b)) box_plus_min(a...) = reduce(box_plus_min, a...) -function _MS_check_node_message(c::Int, v::Int, iter::Int, check_adj_list::Vector{Vector{Int}}, - var_to_check_messages::Array{Float64, 3}, attenuation::Float64) - - @inbounds box_plus_min(var_to_check_messages[v2, c, iter] for v2 in check_adj_list[c] if - v2 != v) +function _MS_check_node_message( + c::Int, + v::Int, + iter::Int, + check_adj_list::Vector{Vector{Int}}, + var_to_check_messages::Array{Float64,3}, + attenuation::Float64, +) + + @inbounds box_plus_min( + var_to_check_messages[v2, c, iter] for v2 in check_adj_list[c] if v2 != v + ) end """ @@ -290,29 +526,60 @@ Run the min-sum algorithm with the parity-check matrix `H`, received vector `v`, - The options for `schedule` are `:parallel` (`:flooding`), `:serial`, or `:layered` (`:semiserial`). - Set the normalization constant with `attenuation`. """ -function min_sum(H::T, v::T, chn::AbstractClassicalNoiseChannel; max_iter::Int = 100, attenuation::Float64 = - 0.5, chn_inits::Union{Missing, Vector{Float64}} = missing, schedule::Symbol = :parallel, - rand_sched::Bool = false, erasures::Vector{Int} = Int[]) where T <: CTMatrixTypes +function min_sum( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel; + max_iter::Int = 100, + attenuation::Float64 = 0.5, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) + (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && + throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, _, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, v, chn, - :MS, chn_inits, schedule, erasures) - return _message_passing_layered(H_Int, missing, chn_inits_2, _MS_check_node_message, - var_adj_list, check_adj_list, max_iter, schedule, current_bits, totals, syn, - check_to_var_messages, var_to_check_messages, attenuation, layers) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init(H, v, chn, :MS, chn_inits, schedule, erasures) + return _message_passing_layered( + H_Int, + missing, + chn_inits_2, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + attenuation, + layers, + ) end """ @@ -326,77 +593,157 @@ and channel `chn`. - The options for `schedule` are `:parallel` (`:flooding`), `:serial`, or `:layered` (`:semiserial`). - Set the normalization constant with `attenuation`. """ -function min_sum_syndrome(H::T, syndrome::T, chn::AbstractClassicalNoiseChannel; max_iter::Int = 100, - attenuation::Float64 = 0.5, chn_inits::Union{Missing, Vector{Float64}} = missing, - schedule::Symbol = :parallel, rand_sched::Bool = false, erasures::Vector{Int} = Int[]) where - T <: CTMatrixTypes +function min_sum_syndrome( + H::T, + syndrome::T, + chn::AbstractClassicalNoiseChannel; + max_iter::Int = 100, + attenuation::Float64 = 0.5, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(syndrome) ≠ (nr, 1) && size(syndrome) ≠ (1, nr)) && throw(ArgumentError("Syndrome has incorrect dimension")) + (size(syndrome) ≠ (nr, 1) && size(syndrome) ≠ (1, nr)) && + throw(ArgumentError("Syndrome has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, _, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, - syndrome, chn, :MS, chn_inits, schedule, erasures) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init(H, syndrome, chn, :MS, chn_inits, schedule, erasures) syn_Int = _Flint_matrix_to_Julia_int_vector(syndrome) - return _message_passing_layered(H_Int, syn_Int, chn_inits_2, _MS_check_node_message, - var_adj_list, check_adj_list, max_iter, schedule, current_bits, totals, syn, - check_to_var_messages, var_to_check_messages, attenuation, layers) + return _message_passing_layered( + H_Int, + syn_Int, + chn_inits_2, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + attenuation, + layers, + ) end # believe this can be merged into an optional argument of the above but keep for now so as not to break working code -function min_sum_decimation(H::T, v::T, chn::AbstractClassicalNoiseChannel, algorithm::Symbol; - decimated_bits_values::Vector{Tuple{Int, S}} = Tuple{Int, S}[], max_iter::Int = 100, - attenuation::Float64 = 0.5, chn_inits::Union{Missing, Vector{Float64}} = missing, - schedule::Symbol = :parallel, rand_sched::Bool = false, guided_rounds::Int = 10, - erasures::Vector{Int} = Int[]) where {T <: CTMatrixTypes, S <: CTFieldElem} +function min_sum_decimation( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel, + algorithm::Symbol; + decimated_bits_values::Vector{Tuple{Int,S}} = Tuple{Int,S}[], + max_iter::Int = 100, + attenuation::Float64 = 0.5, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + guided_rounds::Int = 10, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes,S<:CTFieldElem} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) + (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && + throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) - algorithm ∈ (:auto, :manual, :guided) || throw(ArgumentError("Unknown decimation algorithm")) + algorithm ∈ (:auto, :manual, :guided) || + throw(ArgumentError("Unknown decimation algorithm")) (algorithm == :manual && !isempty(decimated_bits_values)) || throw(ArgumentError("Manual decimation but no decimated bits and values provided")) # unclear how to interpret passed in values if auto or guided is set, so ignore - (algorithm == :auto || algorithm == :guided) && (decimated_bits_values = Tuple{Int, S}[];) + (algorithm == :auto || algorithm == :guided) && + (decimated_bits_values = Tuple{Int,S}[];) if algorithm == :guided - guided_rounds > 0 || throw(DomainError("The number of rounds before decimation must be positive")) + guided_rounds > 0 || + throw(DomainError("The number of rounds before decimation must be positive")) end # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, w, var_adj_list, check_adj_list, chn_inits_2, decimated_bits, decimated_values, - check_to_var_messages, var_to_check_messages, current_bits, totals, syn = - _message_passing_init_decimation(H, v, chn, decimated_bits_values, :MS, 2, - chn_inits, schedule, erasures) + H_Int, + w, + var_adj_list, + check_adj_list, + chn_inits_2, + decimated_bits, + decimated_values, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init_decimation( + H, + v, + chn, + decimated_bits_values, + :MS, + 2, + chn_inits, + schedule, + erasures, + ) # TODO layers - return _message_passing_decimation(H_Int, w, chn_inits_2, _MS_check_node_message, - var_adj_list, check_adj_list, max_iter, :MS, schedule, decimated_bits, decimated_values, - current_bits, totals, syn, check_to_var_messages, var_to_check_messages, 0, 0.0, algorithm, - guided_rounds) + return _message_passing_decimation( + H_Int, + w, + chn_inits_2, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :MS, + schedule, + decimated_bits, + decimated_values, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + 0, + 0.0, + algorithm, + guided_rounds, + ) end # syndrome-based min-sum with decimation ############################# - # Min Sum With Correction +# Min Sum With Correction ############################# function _min_sum_corr_s(a::Float64, b::Float64) @@ -408,13 +755,21 @@ function _min_sum_corr_s(a::Float64, b::Float64) return 0 end end -box_plus_min_c(a::Float64, b::Float64) = sign(a) * sign(b) * min(abs(a), abs(b)) + _min_sum_corr_s(a, b) +box_plus_min_c(a::Float64, b::Float64) = + sign(a) * sign(b) * min(abs(a), abs(b)) + _min_sum_corr_s(a, b) box_plus_min_c(a...) = reduce(box_plus_min_c, a...) -function _MS_correction_check_node_message(c::Int, v::Int, iter::Int, check_adj_list::Vector{Vector{Int}}, - var_to_check_messages::Array{Float64, 3}, attenuation::Float64) - - @inbounds box_plus_min_c(var_to_check_messages[v2, c, iter] for v2 in check_adj_list[c] if - v2 != v) +function _MS_correction_check_node_message( + c::Int, + v::Int, + iter::Int, + check_adj_list::Vector{Vector{Int}}, + var_to_check_messages::Array{Float64,3}, + attenuation::Float64, +) + + @inbounds box_plus_min_c( + var_to_check_messages[v2, c, iter] for v2 in check_adj_list[c] if v2 != v + ) end """ @@ -429,30 +784,60 @@ Run the min-sum algorithm with the parity-check matrix `H`, received vector `v`, - Set the normalization constant with `attenuation`. - A low-complexity approximation to the correction term is used. """ -function min_sum_with_correction(H::T, v::T, chn::AbstractClassicalNoiseChannel; max_iter::Int = 100, - attenuation::Float64 = 0.5, chn_inits::Union{Missing, Vector{Float64}} = missing, - schedule::Symbol = :parallel, rand_sched::Bool = false, erasures::Vector{Int} = Int[]) where - T <: CTMatrixTypes +function min_sum_with_correction( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel; + max_iter::Int = 100, + attenuation::Float64 = 0.5, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) + (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && + throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, _, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, v, chn, - :MS, chn_inits, schedule, erasures) - return _message_passing_layered(H_Int, missing, chn_inits_2, _MS_correction_check_node_message, - var_adj_list, check_adj_list, max_iter, schedule, current_bits, totals, syn, - check_to_var_messages, var_to_check_messages, attenuation, layers) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init(H, v, chn, :MS, chn_inits, schedule, erasures) + return _message_passing_layered( + H_Int, + missing, + chn_inits_2, + _MS_correction_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + attenuation, + layers, + ) end """ @@ -467,89 +852,174 @@ Run the syndrome-based min-sum-with-correction algorithm with the parity-check m - Set the normalization constant with `attenuation`. - A low-complexity approximation to the correction term is used. """ -function min_sum_with_correction_syndrome(H::T, syndrome::T, chn::AbstractClassicalNoiseChannel; max_iter::Int = 100, - attenuation::Float64 = 0.5, chn_inits::Union{Missing, Vector{Float64}} = missing, - schedule::Symbol = :parallel, rand_sched::Bool = false, erasures::Vector{Int} = Int[]) where - T <: CTMatrixTypes +function min_sum_with_correction_syndrome( + H::T, + syndrome::T, + chn::AbstractClassicalNoiseChannel; + max_iter::Int = 100, + attenuation::Float64 = 0.5, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(syndrome) ≠ (nr, 1) && size(syndrome) ≠ (1, nr)) && throw(ArgumentError("Syndrome has incorrect dimension")) + (size(syndrome) ≠ (nr, 1) && size(syndrome) ≠ (1, nr)) && + throw(ArgumentError("Syndrome has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, _, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, - syndrome, chn, :MS, chn_inits, schedule, erasures) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init(H, syndrome, chn, :MS, chn_inits, schedule, erasures) syn_Int = _Flint_matrix_to_Julia_int_vector(syndrome) - return _message_passing_layered(H_Int, syn_Int, chn_inits_2, _MS_correction_check_node_message, - var_adj_list, check_adj_list, max_iter, schedule, current_bits, totals, syn, - check_to_var_messages, var_to_check_messages, attenuation, layers) + return _message_passing_layered( + H_Int, + syn_Int, + chn_inits_2, + _MS_correction_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + attenuation, + layers, + ) end -function min_sum_correction_decimation(H::T, v::T, chn::AbstractClassicalNoiseChannel, algorithm::Symbol; - decimated_bits_values::Vector{Tuple{Int, S}} = Tuple{Int, S}[], max_iter::Int = 100, - attenuation::Float64 = 0.5, chn_inits::Union{Missing, Vector{Float64}} = missing, - schedule::Symbol = :parallel, rand_sched::Bool = false, guided_rounds::Int = 10, - erasures::Vector{Int} = Int[]) where {T <: CTMatrixTypes, S <: CTFieldElem} +function min_sum_correction_decimation( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel, + algorithm::Symbol; + decimated_bits_values::Vector{Tuple{Int,S}} = Tuple{Int,S}[], + max_iter::Int = 100, + attenuation::Float64 = 0.5, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + guided_rounds::Int = 10, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes,S<:CTFieldElem} - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("`H` cannot have a zero dimension")) - (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && throw(ArgumentError("Vector has incorrect dimension")) + (size(v) ≠ (nc, 1) && size(v) ≠ (1, nc)) && + throw(ArgumentError("Vector has incorrect dimension")) # do we want to flip it if necessary? 2 ≤ max_iter || throw(DomainError("Maximum number of iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) - algorithm ∈ (:auto, :manual, :guided) || throw(ArgumentError("Unknown decimation algorithm")) + algorithm ∈ (:auto, :manual, :guided) || + throw(ArgumentError("Unknown decimation algorithm")) (algorithm == :manual && !isempty(decimated_bits_values)) || throw(ArgumentError("Manual decimation but no decimated bits and values provided")) # unclear how to interpret passed in values if auto or guided is set, so ignore - (algorithm == :auto || algorithm == :guided) && (decimated_bits_values = Tuple{Int, S}[];) + (algorithm == :auto || algorithm == :guided) && + (decimated_bits_values = Tuple{Int,S}[];) if algorithm == :guided - guided_rounds > 0 || throw(DomainError("The number of rounds before decimation must be positive")) + guided_rounds > 0 || + throw(DomainError("The number of rounds before decimation must be positive")) end # initialization - do these outside to reduce allocations when looped layers = layered_schedule(H, schedule = schedule, random = rand_sched) - H_Int, w, var_adj_list, check_adj_list, chn_inits_2, decimated_bits, decimated_values, - check_to_var_messages, var_to_check_messages, current_bits, totals, syn = - _message_passing_init_decimation(H, v, chn, decimated_bits_values, :MS, 2, - chn_inits, schedule, erasures) + H_Int, + w, + var_adj_list, + check_adj_list, + chn_inits_2, + decimated_bits, + decimated_values, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init_decimation( + H, + v, + chn, + decimated_bits_values, + :MS, + 2, + chn_inits, + schedule, + erasures, + ) # TODO layers - return _message_passing_decimation(H_Int, w, chn_inits_2, _MS_correction_check_node_message, - var_adj_list, check_adj_list, max_iter, :MS, schedule, decimated_bits, decimated_values, - current_bits, totals, syn, check_to_var_messages, var_to_check_messages, 0, attenuation, - algorithm, guided_rounds) + return _message_passing_decimation( + H_Int, + w, + chn_inits_2, + _MS_correction_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :MS, + schedule, + decimated_bits, + decimated_values, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + 0, + attenuation, + algorithm, + guided_rounds, + ) end ############################# - # Initialization +# Initialization ############################# function _channel_init_BSC(v::Vector{<: Integer}, p::Float64) temp = log((1 - p) / p) chn_init = zeros(Float64, length(v)) - for i in 1:length(v) + for i = 1:length(v) @inbounds chn_init[i] = (-1)^v[i] * temp end return chn_init end -function _channel_init_BSC!(var_to_check_messages::Matrix{Float64}, v::CTMatrixTypes, p::Float64) +function _channel_init_BSC!( + var_to_check_messages::Matrix{Float64}, + v::CTMatrixTypes, + p::Float64, +) temp = log((1 - p) / p) - @inbounds for i in 1:length(v) - iszero(v[i]) ? (var_to_check_messages[i, 1] = temp;) : (var_to_check_messages[i, 1] = -temp;) + @inbounds for i = 1:length(v) + iszero(v[i]) ? (var_to_check_messages[i, 1] = temp;) : + (var_to_check_messages[i, 1] = -temp;) end return nothing end @@ -565,15 +1035,19 @@ end function _channel_init_BAWGNC_SP(v::Vector{<: AbstractFloat}, σ::Float64) temp = 2 / σ^2 chn_init = zeros(Float64, length(v)) - for i in 1:length(v) + for i = 1:length(v) @inbounds chn_init[i] = temp * v[i] end return chn_init end -function _channel_init_BAWGNC_SP!(var_to_check_messages::Matrix{Float64}, v::Vector{<: AbstractFloat}, σ::Float64) +function _channel_init_BAWGNC_SP!( + var_to_check_messages::Matrix{Float64}, + v::Vector{<: AbstractFloat}, + σ::Float64, +) temp = 2 / σ^2 - @inbounds for i in 1:length(v) + @inbounds for i = 1:length(v) var_to_check_messages[i, 1] = temp * v[i] end return nothing @@ -581,17 +1055,25 @@ end _channel_init_BAWGNC_MS(v::Vector{<: AbstractFloat}) = v -_channel_init_BAWGNC_MS!(var_to_check_messages::Matrix{Float64}, v::Vector{<: AbstractFloat}) = var_to_check_messages[:, 1] .= v - -function _message_passing_init_fast(H::Union{Matrix{S}, T}, v::Union{Vector{S}, Vector{AbstractFloat}, - T}, chn::AbstractClassicalNoiseChannel, kind::Symbol, chn_inits::Union{Missing, - Vector{Float64}}, schedule::Symbol, erasures::Vector{Int}) where {S <: Integer, - T <: CTMatrixTypes} +_channel_init_BAWGNC_MS!( + var_to_check_messages::Matrix{Float64}, + v::Vector{<: AbstractFloat}, +) = var_to_check_messages[:, 1] .= v + +function _message_passing_init_fast( + H::Union{Matrix{S},T}, + v::Union{Vector{S},Vector{AbstractFloat},T}, + chn::AbstractClassicalNoiseChannel, + kind::Symbol, + chn_inits::Union{Missing,Vector{Float64}}, + schedule::Symbol, + erasures::Vector{Int}, +) where {S<:Integer,T<:CTMatrixTypes} kind ∈ (:SP, :MS) || throw(ArgumentError("Unknown value for parameter `kind`")) if isa(H, CTMatrixTypes) Int(order(base_ring(H))) == 2 || - throw(ArgumentError("Currently only implemented for binary codes")) + throw(ArgumentError("Currently only implemented for binary codes")) H_Int = UInt8.(_Flint_matrix_to_Julia_int_matrix(H)) v_Int = UInt8.(_Flint_matrix_to_Julia_int_matrix(H)) else @@ -599,31 +1081,38 @@ function _message_passing_init_fast(H::Union{Matrix{S}, T}, v::Union{Vector{S}, v_Int = UInt8.(v) end num_check, num_var = size(H_Int) - num_check > 0 && num_var > 0 || throw(ArgumentError("Input matrix of improper dimension")) + num_check > 0 && num_var > 0 || + throw(ArgumentError("Input matrix of improper dimension")) len_v = length(v) if len_v == num_var syndrome_based = false - kind ∈ (:SP, :MS) && isa(chn, BAWGNChannel) && !isa(v, Vector{<: AbstractFloat}) && - throw(DomainError("Received message should be a vector of floats for BAWGNC.")) - kind ∈ (:SP, :MS) && isa(chn, BinarySymmetricChannel) && !isa(v, Vector{Int}) && !isa(v, CTMatrixTypes) && - throw(DomainError("Received message should be a vector of Ints for BSC.")) + kind ∈ (:SP, :MS) && + isa(chn, BAWGNChannel) && + !isa(v, Vector{<: AbstractFloat}) && + throw(DomainError("Received message should be a vector of floats for BAWGNC.")) + kind ∈ (:SP, :MS) && + isa(chn, BinarySymmetricChannel) && + !isa(v, Vector{Int}) && + !isa(v, CTMatrixTypes) && + throw(DomainError("Received message should be a vector of Ints for BSC.")) elseif len_v == num_check syndrome_based = true else throw(ArgumentError("Vector has incorrect dimension")) end - - check_adj_list = [Int[] for _ in 1:num_check] - for r in 1:num_check - for c in 1:num_var + + check_adj_list = [Int[] for _ = 1:num_check] + for r = 1:num_check + for c = 1:num_var if !iszero(H_Int[r, c]) push!(check_adj_list[r], c) end end end - check_to_var_messages::Vector{Vector{Float64}} = [zeros(Float64, length(check_adj_list[c])) for c in eachindex(check_adj_list)] + check_to_var_messages::Vector{Vector{Float64}} = + [zeros(Float64, length(check_adj_list[c])) for c in eachindex(check_adj_list)] if schedule == :serial var_to_check_messages = zeros(Float64, num_var, 1) else @@ -662,44 +1151,61 @@ function _message_passing_init_fast(H::Union{Matrix{S}, T}, v::Union{Vector{S}, current_bits = zeros(UInt8, num_var) syn = zeros(UInt8, num_check) - return H_Int, v_Int, syndrome_based, check_adj_list, check_to_var_messages, - var_to_check_messages, current_bits, syn + return H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn end -function _message_passing_init(H::Union{Matrix{S}, T}, v::Union{Vector{S}, Vector{AbstractFloat}, - T}, chn::AbstractClassicalNoiseChannel, kind::Symbol, chn_inits::Union{Missing, - Vector{Float64}}, schedule::Symbol, erasures::Vector{Int}) where {S <: Integer, - T <: CTMatrixTypes} +function _message_passing_init( + H::Union{Matrix{S},T}, + v::Union{Vector{S},Vector{AbstractFloat},T}, + chn::AbstractClassicalNoiseChannel, + kind::Symbol, + chn_inits::Union{Missing,Vector{Float64}}, + schedule::Symbol, + erasures::Vector{Int}, +) where {S<:Integer,T<:CTMatrixTypes} kind ∈ (:SP, :MS) || throw(ArgumentError("Unknown value for parameter kind")) # will this work? if isa(H, CTMatrixTypes) Int(order(base_ring(H))) == 2 || - throw(ArgumentError("Currently only implemented for binary codes")) + throw(ArgumentError("Currently only implemented for binary codes")) H_Int = _Flint_matrix_to_Julia_int_matrix(H) else H_Int = H end num_check, num_var = size(H_Int) - num_check > 0 && num_var > 0 || throw(ArgumentError("Input matrix of improper dimension")) + num_check > 0 && num_var > 0 || + throw(ArgumentError("Input matrix of improper dimension")) len_v = length(v) if len_v == num_var syndrome_based = false - kind ∈ (:SP, :MS) && isa(chn, BAWGNChannel) && !isa(v, Vector{<: AbstractFloat}) && - throw(DomainError("Received message should be a vector of floats for BAWGNC.")) - kind ∈ (:SP, :MS) && isa(chn, BinarySymmetricChannel) && !isa(v, Vector{Int}) && !isa(v, CTMatrixTypes) && - throw(DomainError("Received message should be a vector of Ints for BSC.")) + kind ∈ (:SP, :MS) && + isa(chn, BAWGNChannel) && + !isa(v, Vector{<: AbstractFloat}) && + throw(DomainError("Received message should be a vector of floats for BAWGNC.")) + kind ∈ (:SP, :MS) && + isa(chn, BinarySymmetricChannel) && + !isa(v, Vector{Int}) && + !isa(v, CTMatrixTypes) && + throw(DomainError("Received message should be a vector of Ints for BSC.")) elseif len_v == num_check syndrome_based = true else throw(ArgumentError("Vector has incorrect dimension")) end - check_adj_list = [Int[] for _ in 1:num_check] - var_adj_list = [Int[] for _ in 1:num_var] - for r in 1:num_check - for c in 1:num_var + check_adj_list = [Int[] for _ = 1:num_check] + var_adj_list = [Int[] for _ = 1:num_var] + for r = 1:num_check + for c = 1:num_var if !iszero(H_Int[r, c]) push!(check_adj_list[r], c) push!(var_adj_list[c], r) @@ -714,7 +1220,7 @@ function _message_passing_init(H::Union{Matrix{S}, T}, v::Union{Vector{S}, Vecto # else check_to_var_messages = zeros(Float64, num_check, num_var, 2) var_to_check_messages = zeros(Float64, num_var, num_check, 2) -# end + # end # TODO the way v is handled isn't going to work for non-BSC if !syndrome_based && ismissing(chn_inits) @@ -728,7 +1234,7 @@ function _message_passing_init(H::Union{Matrix{S}, T}, v::Union{Vector{S}, Vecto elseif syndrome_based && ismissing(chn_inits) && isa(chn, BinarySymmetricChannel) temp = log((1 - chn.param) / chn.param) # var_to_check_messages[:, 1] .= temp - chn_inits_2 = [temp for _ in 1:num_var] + chn_inits_2 = [temp for _ = 1:num_var] elseif !ismissing(chn_inits) length(chn_inits) ≠ num_var && throw(ArgumentError("Channel inputs has wrong size")) # var_to_check_messages[:, 1] .= chn_inits @@ -750,29 +1256,44 @@ function _message_passing_init(H::Union{Matrix{S}, T}, v::Union{Vector{S}, Vecto end end - return H_Int, syndrome_based, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn + return H_Int, + syndrome_based, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn end -function _message_passing_init_Int(H::Union{Matrix{S}, T}, v::Union{Vector{S}, - Vector{AbstractFloat}, T}, max_iter::Int, kind::Symbol, Bt::Int, schedule::Symbol, - erasures::Vector{Int}) where {S <: Integer, T <: CTMatrixTypes} +function _message_passing_init_Int( + H::Union{Matrix{S},T}, + v::Union{Vector{S},Vector{AbstractFloat},T}, + max_iter::Int, + kind::Symbol, + Bt::Int, + schedule::Symbol, + erasures::Vector{Int}, +) where {S<:Integer,T<:CTMatrixTypes} kind ∈ (:A, :B) || throw(ArgumentError("Unknown value for parameter kind")) # will this work? if isa(H, CTMatrixTypes) Int(order(base_ring(H))) == 2 || - throw(ArgumentError("Currently only implemented for binary codes")) + throw(ArgumentError("Currently only implemented for binary codes")) H_Int = _Flint_matrix_to_Julia_int_matrix(H) else H_Int = H end num_check, num_var = size(H_Int) - num_check > 0 && num_var > 0 || throw(ArgumentError("Input matrix of improper dimension")) + num_check > 0 && num_var > 0 || + throw(ArgumentError("Input matrix of improper dimension")) (kind == :B && !(1 ≤ Bt ≤ num_check)) && throw(DomainError("Improper threshold for Gallager B")) 2 ≤ max_iter || throw(DomainError("Number of maximum iterations must be at least two")) - + len_v = length(v) if len_v == num_var syndrome_based = false @@ -781,11 +1302,11 @@ function _message_passing_init_Int(H::Union{Matrix{S}, T}, v::Union{Vector{S}, else throw(ArgumentError("Vector has incorrect dimension")) end - - check_adj_list = [Int[] for _ in 1:num_check] - var_adj_list = [Int[] for _ in 1:num_var] - for r in 1:num_check - for c in 1:num_var + + check_adj_list = [Int[] for _ = 1:num_check] + var_adj_list = [Int[] for _ = 1:num_var] + for r = 1:num_check + for c = 1:num_var if !iszero(H_Int[r, c]) push!(check_adj_list[r], c) push!(var_adj_list[c], r) @@ -795,7 +1316,7 @@ function _message_passing_init_Int(H::Union{Matrix{S}, T}, v::Union{Vector{S}, # # TODO: what are proper inits for syndrome and erasures here? # if !syndrome_based && ismissing(chn_inits) - chn_inits = vec(_Flint_matrix_to_Julia_int_matrix(v)) + chn_inits = vec(_Flint_matrix_to_Julia_int_matrix(v)) # elseif syndrome_based && ismissing(chn_inits) # chn_inits = [log((1 - chn.cross_over_prob) / chn.cross_over_prob) for _ in 1:num_var] # end @@ -820,36 +1341,57 @@ function _message_passing_init_Int(H::Union{Matrix{S}, T}, v::Union{Vector{S}, # end # end - return H_Int, var_adj_list, check_adj_list, chn_inits, check_to_var_messages, - var_to_check_messages, current_bits, syn + return H_Int, + var_adj_list, + check_adj_list, + chn_inits, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn end -function _message_passing_init_decimation(H::T, v::T, chn::AbstractClassicalNoiseChannel, - decimated_bits_values::Vector{Tuple{Int, S}}, kind::Symbol, Bt::Int, - chn_inits::Union{Missing, Vector{Float64}}, schedule::Symbol, erasures::Vector{Int}) where {S <: CTFieldElem, - T <: CTMatrixTypes} +function _message_passing_init_decimation( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel, + decimated_bits_values::Vector{Tuple{Int,S}}, + kind::Symbol, + Bt::Int, + chn_inits::Union{Missing,Vector{Float64}}, + schedule::Symbol, + erasures::Vector{Int}, +) where {S<:CTFieldElem,T<:CTMatrixTypes} kind ∈ (:SP, :MS, :A, :B) || throw(ArgumentError("Unknown value for parameter kind")) - kind ∈ (:SP, :MS) && ismissing(chn) && throw(ArgumentError(":SP and :MS require a noise model")) + kind ∈ (:SP, :MS) && + ismissing(chn) && + throw(ArgumentError(":SP and :MS require a noise model")) Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) num_check, num_var = size(H) - num_check > 0 && num_var > 0 || throw(ArgumentError("Input matrix of improper dimension")) + num_check > 0 && num_var > 0 || + throw(ArgumentError("Input matrix of improper dimension")) length(v) == num_var || throw(ArgumentError("Vector has incorrect dimension")) (kind == :B && !(1 ≤ Bt ≤ num_check)) && throw(DomainError("Improper threshold for Gallager B")) - kind ∈ (:SP, :MS) && chn.type == :BAWGNC && !isa(v, Vector{<:AbstractFloat}) && + kind ∈ (:SP, :MS) && + chn.type == :BAWGNC && + !isa(v, Vector{<:AbstractFloat}) && throw(DomainError("Received message should be a vector of floats for BAWGNC.")) - kind ∈ (:SP, :MS) && chn.type == :BSC && !isa(v, Vector{Int}) && !isa(v, CTMatrixTypes) && + kind ∈ (:SP, :MS) && + chn.type == :BSC && + !isa(v, Vector{Int}) && + !isa(v, CTMatrixTypes) && throw(DomainError("Received message should be a vector of Ints for BSC.")) - + H_Int = _Flint_matrix_to_Julia_int_matrix(H) w = vec(_Flint_matrix_to_Julia_int_matrix(v)) - check_adj_list = [Int[] for _ in 1:num_check] - var_adj_list = [Int[] for _ in 1:num_var] + check_adj_list = [Int[] for _ = 1:num_check] + var_adj_list = [Int[] for _ = 1:num_var] - for r in 1:num_check - for c in 1:num_var + for r = 1:num_check + for c = 1:num_var if !iszero(H_Int[r, c]) push!(check_adj_list[r], c) push!(var_adj_list[c], r) @@ -923,45 +1465,65 @@ function _message_passing_init_decimation(H::T, v::T, chn::AbstractClassicalNois end end - return H_Int, w, var_adj_list, check_adj_list, chn_inits, decimated_bits, - decimated_values, check_to_var_messages, var_to_check_messages, current_bits, - totals, syn + return H_Int, + w, + var_adj_list, + check_adj_list, + chn_inits, + decimated_bits, + decimated_values, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn end ############################# - # Message Passing +# Message Passing ############################# -function _message_passing(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, - chn_inits::Vector{Float64}, c_to_v_mess::Function, var_adj_list::Vector{Vector{Int}}, - check_adj_list::Vector{Vector{Int}}, max_iter::Int, schedule::Symbol, - current_bits::Vector{Int}, totals::Vector{Float64}, syn::Vector{Int}, - check_to_var_messages::Array{Float64, 3}, var_to_check_messages::Array{Float64, 3}, - attenuation::Float64) where T <: Integer +function _message_passing( + H::Matrix{T}, + syndrome::Union{Missing,Vector{T}}, + chn_inits::Vector{Float64}, + c_to_v_mess::Function, + var_adj_list::Vector{Vector{Int}}, + check_adj_list::Vector{Vector{Int}}, + max_iter::Int, + schedule::Symbol, + current_bits::Vector{Int}, + totals::Vector{Float64}, + syn::Vector{Int}, + check_to_var_messages::Array{Float64,3}, + var_to_check_messages::Array{Float64,3}, + attenuation::Float64, +) where {T<:Integer} num_check, num_var = size(H) # first iteration for variable nodes - set to channel initialization - @inbounds for v in 1:num_var + @inbounds for v = 1:num_var @simd for c in var_adj_list[v] var_to_check_messages[v, c, 1] = chn_inits[v] end end - @inbounds @simd for c in 1:num_check + @inbounds @simd for c = 1:num_check for v in check_adj_list[c] if !ismissing(syndrome) - check_to_var_messages[c, v, 1] = (-1)^syndrome[c] * c_to_v_mess(c, v, 1, - check_adj_list, var_to_check_messages, attenuation) + check_to_var_messages[c, v, 1] = + (-1)^syndrome[c] * + c_to_v_mess(c, v, 1, check_adj_list, var_to_check_messages, attenuation) else - check_to_var_messages[c, v, 1] = c_to_v_mess(c, v, 1, check_adj_list, - var_to_check_messages, attenuation) + check_to_var_messages[c, v, 1] = + c_to_v_mess(c, v, 1, check_adj_list, var_to_check_messages, attenuation) end end end # one full iteration done, check if converged - @simd for v in 1:num_var + @simd for v = 1:num_var totals[v] = chn_inits[v] for c in var_adj_list[v] totals[v] += check_to_var_messages[c, v, 1] @@ -970,9 +1532,10 @@ function _message_passing(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, end LinearAlgebra.mul!(syn, H, current_bits) if !ismissing(syndrome) - all(syn[i] .% 2 == syndrome[i] for i in 1:num_check) && return true, current_bits, 1, totals + all(syn[i] .% 2 == syndrome[i] for i = 1:num_check) && + return true, current_bits, 1, totals else - all(iszero(syn[i] .% 2) for i in 1:num_check) && return true, current_bits, 1, totals + all(iszero(syn[i] .% 2) for i = 1:num_check) && return true, current_bits, 1, totals end iter = 2 @@ -981,40 +1544,55 @@ function _message_passing(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, prev_iter = 1 # does this propagate correctly? @inbounds while iter ≤ max_iter - @simd for v in 1:num_var + @simd for v = 1:num_var for c in var_adj_list[v] # this includes the channel inputs in total - var_to_check_messages[v, c, curr_iter] = totals[v] - - check_to_var_messages[c, v, prev_iter] + var_to_check_messages[v, c, curr_iter] = + totals[v] - check_to_var_messages[c, v, prev_iter] end end - @simd for c in 1:num_check + @simd for c = 1:num_check for v in check_adj_list[c] if !ismissing(syndrome) - check_to_var_messages[c, v, curr_iter] = (-1)^syndrome[c] * c_to_v_mess(c, v, - curr_iter, check_adj_list, var_to_check_messages, attenuation) + check_to_var_messages[c, v, curr_iter] = + (-1)^syndrome[c] * c_to_v_mess( + c, + v, + curr_iter, + check_adj_list, + var_to_check_messages, + attenuation, + ) else - check_to_var_messages[c, v, curr_iter] = c_to_v_mess(c, v, - curr_iter, check_adj_list, var_to_check_messages, attenuation) + check_to_var_messages[c, v, curr_iter] = c_to_v_mess( + c, + v, + curr_iter, + check_adj_list, + var_to_check_messages, + attenuation, + ) end end end - + # iteration done, check if converged - @simd for v in 1:num_var + @simd for v = 1:num_var totals[v] = chn_inits[v] for c in var_adj_list[v] totals[v] += check_to_var_messages[c, v, curr_iter] end current_bits[v] = totals[v] >= 0 ? 0 : 1 end - + LinearAlgebra.mul!(syn, H, current_bits) if !ismissing(syndrome) - all(syn[i] .% 2 == syndrome[i] for i in 1:num_check) && return true, current_bits, iter, totals + all(syn[i] .% 2 == syndrome[i] for i = 1:num_check) && + return true, current_bits, iter, totals else - all(iszero(syn[i] .% 2) for i in 1:num_check) && return true, current_bits, iter, totals + all(iszero(syn[i] .% 2) for i = 1:num_check) && + return true, current_bits, iter, totals end if schedule == :parallel @@ -1028,16 +1606,27 @@ function _message_passing(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, return false, current_bits, iter, totals end -function _message_passing_layered(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, - chn_inits::Vector{Float64}, c_to_v_mess::Function, var_adj_list::Vector{Vector{Int}}, - check_adj_list::Vector{Vector{Int}}, max_iter::Int, schedule::Symbol, - current_bits::Vector{Int}, totals::Vector{Float64}, syn::Vector{Int}, - check_to_var_messages::Array{Float64, 3}, var_to_check_messages::Array{Float64, 3}, - attenuation::Float64, layers::Vector{Vector{Int}}) where T <: Integer +function _message_passing_layered( + H::Matrix{T}, + syndrome::Union{Missing,Vector{T}}, + chn_inits::Vector{Float64}, + c_to_v_mess::Function, + var_adj_list::Vector{Vector{Int}}, + check_adj_list::Vector{Vector{Int}}, + max_iter::Int, + schedule::Symbol, + current_bits::Vector{Int}, + totals::Vector{Float64}, + syn::Vector{Int}, + check_to_var_messages::Array{Float64,3}, + var_to_check_messages::Array{Float64,3}, + attenuation::Float64, + layers::Vector{Vector{Int}}, +) where {T<:Integer} # first iteration for variable nodes - set to channel initialization num_check, num_var = size(H) - @inbounds for v in 1:num_var + @inbounds for v = 1:num_var @simd for c in var_adj_list[v] var_to_check_messages[v, c, 2] = chn_inits[v] end @@ -1052,17 +1641,30 @@ function _message_passing_layered(H::Matrix{T}, syndrome::Union{Missing, Vector{ @simd for c in layer for v in check_adj_list[c] if !ismissing(syndrome) - check_to_var_messages[c, v, curr_iter] = (-1)^syndrome[c] * c_to_v_mess(c, v, - curr_iter, check_adj_list, var_to_check_messages, attenuation) + check_to_var_messages[c, v, curr_iter] = + (-1)^syndrome[c] * c_to_v_mess( + c, + v, + curr_iter, + check_adj_list, + var_to_check_messages, + attenuation, + ) else - check_to_var_messages[c, v, curr_iter] = c_to_v_mess(c, v, - curr_iter, check_adj_list, var_to_check_messages, attenuation) + check_to_var_messages[c, v, curr_iter] = c_to_v_mess( + c, + v, + curr_iter, + check_adj_list, + var_to_check_messages, + attenuation, + ) end end end # TODO the only values that should be changing here are the ones connected to the check nodes in the layer - @simd for v in 1:num_var + @simd for v = 1:num_var totals[v] = chn_inits[v] for c in var_adj_list[v] totals[v] += check_to_var_messages[c, v, curr_iter] @@ -1070,19 +1672,20 @@ function _message_passing_layered(H::Matrix{T}, syndrome::Union{Missing, Vector{ current_bits[v] = totals[v] >= 0 ? 0 : 1 end - @simd for v in 1:num_var + @simd for v = 1:num_var for c in var_adj_list[v] # this includes the channel inputs in total # TODO: here prev was changed to curr - var_to_check_messages[v, c, curr_iter] = totals[v] - - check_to_var_messages[c, v, curr_iter] + var_to_check_messages[v, c, curr_iter] = + totals[v] - check_to_var_messages[c, v, curr_iter] end end # switch these current values to previous values so the next layer can use them @inbounds @simd for c in layer for v in check_adj_list[c] - check_to_var_messages[c, v, prev_iter] = check_to_var_messages[c, v, curr_iter] + check_to_var_messages[c, v, prev_iter] = + check_to_var_messages[c, v, curr_iter] end end @@ -1094,9 +1697,11 @@ function _message_passing_layered(H::Matrix{T}, syndrome::Union{Missing, Vector{ # iteration done, check if converged LinearAlgebra.mul!(syn, H, current_bits) if !ismissing(syndrome) - all(syn[i] % 2 == syndrome[i] for i in 1:num_check) && return true, current_bits, iter, totals + all(syn[i] % 2 == syndrome[i] for i = 1:num_check) && + return true, current_bits, iter, totals else - all(iszero(syn[i] % 2) for i in 1:num_check) && return true, current_bits, iter, totals + all(iszero(syn[i] % 2) for i = 1:num_check) && + return true, current_bits, iter, totals end iter += 1 @@ -1104,11 +1709,20 @@ function _message_passing_layered(H::Matrix{T}, syndrome::Union{Missing, Vector{ return false, current_bits, iter, totals end -function _message_passing_fast(H_Int::Matrix{UInt8}, v::Matrix{UInt8}, syndrome_based::Bool, - check_adj_list::Vector{Vector{Int}}, check_to_var_messages::Vector{Vector{Float64}}, - var_to_check_messages::Matrix{Float64}, current_bits::Vector{UInt8}, syn::Vector{UInt8}, - phi::Function, phi_inv::Function, max_iter::Int) - +function _message_passing_fast( + H_Int::Matrix{UInt8}, + v::Matrix{UInt8}, + syndrome_based::Bool, + check_adj_list::Vector{Vector{Int}}, + check_to_var_messages::Vector{Vector{Float64}}, + var_to_check_messages::Matrix{Float64}, + current_bits::Vector{UInt8}, + syn::Vector{UInt8}, + phi::Function, + phi_inv::Function, + max_iter::Int, +) + # TODO # 3. estabilish how phi and phi^{-1} behave wrt to above functions @@ -1117,8 +1731,8 @@ function _message_passing_fast(H_Int::Matrix{UInt8}, v::Matrix{UInt8}, syndrome_ schedule == :parallel ? (curr_iter = 2;) : (curr_iter = 1;) prev_iter = 1 @inbounds while iter < max_iter - # while iter < max_iter - for c in 1:num_check + # while iter < max_iter + for c = 1:num_check S::Float64 = 0.0 for (i, v) in enumerate(check_adj_list[c]) S += phi(var_to_check_messages[v, prev_iter] - check_to_var_messages[c][i]) @@ -1134,16 +1748,18 @@ function _message_passing_fast(H_Int::Matrix{UInt8}, v::Matrix{UInt8}, syndrome_ end end - @inbounds for i in 1:num_var - # for i in 1:num_var + @inbounds for i = 1:num_var + # for i in 1:num_var current_bits[i] = var_to_check_messages[i, curr_iter] >= 0 ? 0 : 1 end LinearAlgebra.mul!(syn, H_Int, current_bits) if syndrome_based - all(syn[i] % 2 == v[i, 1] for i in 1:num_check) && return true, current_bits, iter, var_to_check_messages[:, curr_iter] + all(syn[i] % 2 == v[i, 1] for i = 1:num_check) && + return true, current_bits, iter, var_to_check_messages[:, curr_iter] else - all(iszero(syn[i] % 2) for i in 1:num_check) && return true, current_bits, iter, var_to_check_messages[:, curr_iter] + all(iszero(syn[i] % 2) for i = 1:num_check) && + return true, current_bits, iter, var_to_check_messages[:, curr_iter] end if schedule == :parallel @@ -1154,18 +1770,28 @@ function _message_passing_fast(H_Int::Matrix{UInt8}, v::Matrix{UInt8}, syndrome_ iter += 1 end - @inbounds for i in 1:num_var - # for i in 1:num_var + @inbounds for i = 1:num_var + # for i in 1:num_var current_bits[i] = var_to_check_messages[i, curr_iter] >= 0 ? 0 : 1 end return false, current_bits, iter, var_to_check_messages[:, curr_iter] end -function _message_passing_fast_layered(H_Int::Matrix{UInt8}, v::Matrix{UInt8}, syndrome_based::Bool, - check_adj_list::Vector{Vector{Int}}, check_to_var_messages::Vector{Vector{Float64}}, - var_to_check_messages::Matrix{Float64}, current_bits::Vector{UInt8}, syn::Vector{UInt8}, - phi::Function, phi_inv::Function, max_iter::Int, layers::Vector{Vector{Int}}) - +function _message_passing_fast_layered( + H_Int::Matrix{UInt8}, + v::Matrix{UInt8}, + syndrome_based::Bool, + check_adj_list::Vector{Vector{Int}}, + check_to_var_messages::Vector{Vector{Float64}}, + var_to_check_messages::Matrix{Float64}, + current_bits::Vector{UInt8}, + syn::Vector{UInt8}, + phi::Function, + phi_inv::Function, + max_iter::Int, + layers::Vector{Vector{Int}}, +) + # TODO # 3. estabilish how phi and phi^{-1} behave wrt to above functions @@ -1178,35 +1804,42 @@ function _message_passing_fast_layered(H_Int::Matrix{UInt8}, v::Matrix{UInt8}, s for c in layer S = 0.0 for v in check_adj_list[c] - S += phi(var_to_check_messages[v, prev_iter] - check_to_var_messages[c][v]) + S += phi( + var_to_check_messages[v, prev_iter] - check_to_var_messages[c][v], + ) end for v in check_adj_list[c] - Q_temp = var_to_check_messages[v, prev_iter] - check_to_var_messages[c][v] + Q_temp = + var_to_check_messages[v, prev_iter] - check_to_var_messages[c][v] # TODO fix phi_inv here to not need this (-1)^sign term temp = S - phi(Q_temp) check_to_var_messages[c][v] = (-1)^sign(temp) * phi_inv(temp) - var_to_check_messages[v, curr_iter] = Q_temp + check_to_var_messages[c][v] + var_to_check_messages[v, curr_iter] = + Q_temp + check_to_var_messages[c][v] end end # switch these current values to previous values so the next layer can use them @inbounds @simd for c in layer for v in check_adj_list[c] - var_to_check_messages[v, prev_iter] = var_to_check_messages[v, curr_iter] + var_to_check_messages[v, prev_iter] = + var_to_check_messages[v, curr_iter] end end end - @inbounds for i in 1:num_var + @inbounds for i = 1:num_var current_bits[i] = var_to_check_messages[i, curr_iter] >= 0 ? 0 : 1 end LinearAlgebra.mul!(syn, H_Int, current_bits) if syndrome_based - all(syn[i] % 2 == v[i, 1] for i in 1:num_check) && return true, current_bits, iter, var_to_check_messages[:, curr_iter] + all(syn[i] % 2 == v[i, 1] for i = 1:num_check) && + return true, current_bits, iter, var_to_check_messages[:, curr_iter] else - all(iszero(syn[i] % 2) for i in 1:num_check) && return true, current_bits, iter, var_to_check_messages[:, curr_iter] + all(iszero(syn[i] % 2) for i = 1:num_check) && + return true, current_bits, iter, var_to_check_messages[:, curr_iter] end if schedule == :parallel @@ -1217,43 +1850,55 @@ function _message_passing_fast_layered(H_Int::Matrix{UInt8}, v::Matrix{UInt8}, s iter += 1 end - @inbounds for i in 1:num_var + @inbounds for i = 1:num_var current_bits[i] = var_to_check_messages[i, curr_iter] >= 0 ? 0 : 1 end return false, current_bits, iter, var_to_check_messages[:, curr_iter] end # significant speedups seperating the float and int code -function _message_passing_Int(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, - chn_inits::Vector{Int}, c_to_v_mess::Function, var_adj_list::Vector{Vector{Int}}, - check_adj_list::Vector{Vector{Int}}, max_iter::Int, kind::Symbol, schedule::Symbol, - current_bits::Vector{Int}, syn::Vector{Int}, check_to_var_messages::Array{Int, 3}, - var_to_check_messages::Array{Int, 3}, Bt::Int) where T <: Integer +function _message_passing_Int( + H::Matrix{T}, + syndrome::Union{Missing,Vector{T}}, + chn_inits::Vector{Int}, + c_to_v_mess::Function, + var_adj_list::Vector{Vector{Int}}, + check_adj_list::Vector{Vector{Int}}, + max_iter::Int, + kind::Symbol, + schedule::Symbol, + current_bits::Vector{Int}, + syn::Vector{Int}, + check_to_var_messages::Array{Int,3}, + var_to_check_messages::Array{Int,3}, + Bt::Int, +) where {T<:Integer} num_check, num_var = size(H) # first iteration for variable nodes - set to channel initialization - @inbounds for v in 1:num_var + @inbounds for v = 1:num_var @simd for c in var_adj_list[v] var_to_check_messages[v, c, 1] = v end end - @simd for c in 1:num_check + @simd for c = 1:num_check for v in check_adj_list[c] if !ismissing(syndrome) - check_to_var_messages[c, v, 1] = (-1)^syndrome[c] * c_to_v_mess(c, v, 1, - check_adj_list, var_to_check_messages, 0.0) + check_to_var_messages[c, v, 1] = + (-1)^syndrome[c] * + c_to_v_mess(c, v, 1, check_adj_list, var_to_check_messages, 0.0) else - check_to_var_messages[c, v, 1] = c_to_v_mess(c, v, 1, check_adj_list, - var_to_check_messages, 0.0) + check_to_var_messages[c, v, 1] = + c_to_v_mess(c, v, 1, check_adj_list, var_to_check_messages, 0.0) end end end # one full iteration done, check if converged curr_iter = 1 - @simd for v in 1:num_var + @simd for v = 1:num_var len = length(var_adj_list[v]) one_count = count(isone, view(check_to_var_messages, var_adj_list[v], v, curr_iter)) d = fld(len, 2) @@ -1261,9 +1906,9 @@ function _message_passing_Int(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, end LinearAlgebra.mul!(syn, H, current_bits) if !ismissing(syndrome) - all(syn[i] .% 2 == syndrome[i] for i in 1:num_check) && return true, current_bits, 1 + all(syn[i] .% 2 == syndrome[i] for i = 1:num_check) && return true, current_bits, 1 else - all(iszero(syn[i] .% 2) for i in 1:num_check) && return true, current_bits, 1 + all(iszero(syn[i] .% 2) for i = 1:num_check) && return true, current_bits, 1 end iter = 2 @@ -1271,17 +1916,23 @@ function _message_passing_Int(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, prev_iter = 1 # does this propagate correctly? @inbounds while iter ≤ max_iter - @simd for v in 1:num_var + @simd for v = 1:num_var for c in var_adj_list[v] if kind == :A && length(var_adj_list[v]) > 1 - if all(!Base.isequal(chn_inits[v]), check_to_var_messages[c2, v, prev_iter] for - c2 in var_adj_list[v] if c != c2) + if all( + !Base.isequal(chn_inits[v]), + check_to_var_messages[c2, v, prev_iter] for + c2 in var_adj_list[v] if c != c2 + ) var_to_check_messages[v, c, curr_iter] ⊻= 1 end elseif kind == :B && length(var_adj_list[v]) >= Bt - if count(!Base.isequal(chn_inits[v]), check_to_var_messages[c2, v, prev_iter] for - c2 in var_adj_list[v] if c != c2) >= Bt + if count( + !Base.isequal(chn_inits[v]), + check_to_var_messages[c2, v, prev_iter] for + c2 in var_adj_list[v] if c != c2 + ) >= Bt var_to_check_messages[v, c, curr_iter] ⊻= 1 end @@ -1289,34 +1940,49 @@ function _message_passing_Int(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, end end - @simd for c in 1:num_check + @simd for c = 1:num_check for v in check_adj_list[c] if !ismissing(syndrome) - check_to_var_messages[c, v, 1] = (-1)^syndrome[c] * c_to_v_mess(c, v, curr_iter, - check_adj_list, var_to_check_messages, 0.0) + check_to_var_messages[c, v, 1] = + (-1)^syndrome[c] * c_to_v_mess( + c, + v, + curr_iter, + check_adj_list, + var_to_check_messages, + 0.0, + ) else - check_to_var_messages[c, v, 1] = c_to_v_mess(c, v, curr_iter, check_adj_list, - var_to_check_messages, 0.0) + check_to_var_messages[c, v, 1] = c_to_v_mess( + c, + v, + curr_iter, + check_adj_list, + var_to_check_messages, + 0.0, + ) end end end - + # iteration done, check if converged - @simd for v in 1:num_var + @simd for v = 1:num_var len = length(var_adj_list[v]) - one_count = count(isone, view(check_to_var_messages, var_adj_list[v], v, curr_iter)) + one_count = + count(isone, view(check_to_var_messages, var_adj_list[v], v, curr_iter)) d = fld(len, 2) current_bits[v] = one_count + (isone(chn_inits[v]) && iseven(len)) > d end - + LinearAlgebra.mul!(syn, H, current_bits) if !ismissing(syndrome) - all(syn[i] .% 2 == syndrome[i] for i in 1:num_check) && return true, current_bits, - curr_iter + all(syn[i] .% 2 == syndrome[i] for i = 1:num_check) && + return true, current_bits, curr_iter else - all(iszero(syn[i] .% 2) for i in 1:num_check) && return true, current_bits, curr_iter + all(iszero(syn[i] .% 2) for i = 1:num_check) && + return true, current_bits, curr_iter end - + if schedule == :flooding temp = curr_iter curr_iter = prev_iter @@ -1328,14 +1994,28 @@ function _message_passing_Int(H::Matrix{T}, syndrome::Union{Missing, Vector{T}}, return false, current_bits, iter end -function _message_passing_decimation(H::Matrix{T}, w::Vector{T}, chn_inits::Union{Missing, - Vector{Float64}}, c_to_v_mess::Function, var_adj_list::Vector{Vector{Int}}, - check_adj_list::Vector{Vector{Int}}, max_iter::Int, kind::Symbol, schedule::Symbol, - decimated_bits::Vector{Int}, decimated_values::Vector{Int}, current_bits::Vector{Int}, - totals::Union{Vector{Int}, Vector{Float64}}, syn::Vector{Int}, - check_to_var_messages::Union{Array{Float64, 3}, Array{Int, 3}}, - var_to_check_messages::Union{Array{Float64, 3}, Array{Int, 3}}, Bt::Int, - attenuation::Float64, algorithm::Symbol, guided_rounds::Int) where T <: Integer +function _message_passing_decimation( + H::Matrix{T}, + w::Vector{T}, + chn_inits::Union{Missing,Vector{Float64}}, + c_to_v_mess::Function, + var_adj_list::Vector{Vector{Int}}, + check_adj_list::Vector{Vector{Int}}, + max_iter::Int, + kind::Symbol, + schedule::Symbol, + decimated_bits::Vector{Int}, + decimated_values::Vector{Int}, + current_bits::Vector{Int}, + totals::Union{Vector{Int},Vector{Float64}}, + syn::Vector{Int}, + check_to_var_messages::Union{Array{Float64,3},Array{Int,3}}, + var_to_check_messages::Union{Array{Float64,3},Array{Int,3}}, + Bt::Int, + attenuation::Float64, + algorithm::Symbol, + guided_rounds::Int, +) where {T<:Integer} # the inclusion of the kind statements add less than a microsecond num_check, num_var = size(H) @@ -1344,15 +2024,15 @@ function _message_passing_decimation(H::Matrix{T}, w::Vector{T}, chn_inits::Unio current_bits[v] = decimated_values[i] end end - + # first iteration for variable nodes - set to channel initialization if kind ∈ (:SP, :MS) - @inbounds for v in 1:num_var + @inbounds for v = 1:num_var var_to_check_messages[v, var_adj_list[v], 1] .= chn_inits[v] end elseif kind ∈ (:A, :B) # TODO: remove and set this to chn_inits - @inbounds for v in 1:num_var + @inbounds for v = 1:num_var var_to_check_messages[v, var_adj_list[v], :] .= w[v] end end @@ -1363,18 +2043,24 @@ function _message_passing_decimation(H::Matrix{T}, w::Vector{T}, chn_inits::Unio # does this propagate correctly? @inbounds while iter ≤ max_iter # variable node is already done for first iteration, so start with check nodes - @simd for c in 1:num_check + @simd for c = 1:num_check for v in check_adj_list[c] if v ∉ decimated_bits - check_to_var_messages[c, v, curr_iter] = c_to_v_mess(c, v, curr_iter, - check_adj_list, var_to_check_messages, attenuation) + check_to_var_messages[c, v, curr_iter] = c_to_v_mess( + c, + v, + curr_iter, + check_adj_list, + var_to_check_messages, + attenuation, + ) end end end # one full iteration done, check if converged if kind ∈ (:SP, :MS) - @simd for v in 1:num_var + @simd for v = 1:num_var if v ∉ decimated_bits totals[v] = chn_inits[v] for c in var_adj_list[v] @@ -1384,10 +2070,13 @@ function _message_passing_decimation(H::Matrix{T}, w::Vector{T}, chn_inits::Unio end end elseif kind ∈ (:A, :B) - @simd for v in 1:num_var + @simd for v = 1:num_var if v ∉ decimated_bits len = length(var_adj_list[v]) - one_count = count(isone, view(check_to_var_messages, var_adj_list[v], v, curr_iter)) + one_count = count( + isone, + view(check_to_var_messages, var_adj_list[v], v, curr_iter), + ) d = fld(len, 2) current_bits[v] = one_count + (isone(w[v]) && iseven(len)) > d end @@ -1418,13 +2107,13 @@ function _message_passing_decimation(H::Matrix{T}, w::Vector{T}, chn_inits::Unio end if iter ≤ max_iter - for v in 1:num_var + for v = 1:num_var if v ∉ decimated_bits for c in var_adj_list[v] if kind ∈ (:SP, :MS) # this includes the channel inputs in total - var_to_check_messages[v, c, curr_iter] = totals[v] - - check_to_var_messages[c, v, prev_iter] + var_to_check_messages[v, c, curr_iter] = + totals[v] - check_to_var_messages[c, v, prev_iter] if algorithm == :auto if var_to_check_messages[v, c, curr_iter] > 8 push!(decimated_bits, v) @@ -1437,15 +2126,21 @@ function _message_passing_decimation(H::Matrix{T}, w::Vector{T}, chn_inits::Unio end end elseif kind == :A && length(var_adj_list[v]) > 1 - if all(!Base.isequal(w[v]), check_to_var_messages[c2, v, prev_iter] for - c2 in var_adj_list[v] if c != c2) + if all( + !Base.isequal(w[v]), + check_to_var_messages[c2, v, prev_iter] for + c2 in var_adj_list[v] if c != c2 + ) var_to_check_messages[v, c, curr_iter] ⊻= 1 # TODO: how to auto this? end elseif kind == :B && length(var_adj_list[v]) >= Bt - if count(!Base.isequal(w[v]), check_to_var_messages[c2, v, prev_iter] for - c2 in var_adj_list[v] if c != c2) >= Bt + if count( + !Base.isequal(w[v]), + check_to_var_messages[c2, v, prev_iter] for + c2 in var_adj_list[v] if c != c2 + ) >= Bt var_to_check_messages[v, c, curr_iter] ⊻= 1 # TODO: how to auto this? @@ -1461,7 +2156,7 @@ function _message_passing_decimation(H::Matrix{T}, w::Vector{T}, chn_inits::Unio end ############################# - # Methods +# Methods ############################# # Mansour, Shanbhag, "Turbo Decoder Architectures for Low-Density Parity-Check Codes" (2002) @@ -1475,18 +2170,23 @@ Return a layered schedule for the parity-check matrix `H`. If `schedule` is `:pa `:serial`, layers representing these two extreme cases are returned. If `random` is `true`, the schedule is shuffled. """ -function layered_schedule(H::CTMatrixTypes; schedule::Symbol = :layered, random::Bool = false) +function layered_schedule( + H::CTMatrixTypes; + schedule::Symbol = :layered, + random::Bool = false, +) num_check, num_var = size(H) - num_check > 0 && num_var > 0 || throw(ArgumentError("Input matrix of improper dimension")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + num_check > 0 && num_var > 0 || + throw(ArgumentError("Input matrix of improper dimension")) + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) if schedule == :layered - check_adj_list = [Int[] for _ in 1:num_check] - for r in 1:num_check - for c in 1:num_var + check_adj_list = [Int[] for _ = 1:num_check] + for r = 1:num_check + for c = 1:num_var iszero(H[r, c]) || push!(check_adj_list[r], c) end end @@ -1512,7 +2212,7 @@ function layered_schedule(H::CTMatrixTypes; schedule::Symbol = :layered, random: random && shuffle!(sched_list[1]) else # serial - sched_list = [[i] for i in 1:num_check] + sched_list = [[i] for i = 1:num_check] random && shuffle!(sched_list) end return sched_list @@ -1522,7 +2222,8 @@ end # ref: Layered Decoding of Quantum LDPC Codes function balance_of_layered_schedule(sch::Vector{Vector{Int}}) is_empty(sch) && throw(ArgumentError("Schedule cannot be empty")) - any(x -> is_empty(x), sch) && throw(ArgumentError("Schedule cannot contain an empty layer")) + any(x -> is_empty(x), sch) && + throw(ArgumentError("Schedule cannot contain an empty layer")) len = sch[1] all(x -> length(x) == len, sch) && return 1 diff --git a/src/LDPC/algorithms.jl b/src/LDPC/algorithms.jl index 00711dba..9225ec52 100644 --- a/src/LDPC/algorithms.jl +++ b/src/LDPC/algorithms.jl @@ -21,7 +21,7 @@ # the variable node lists can be preallocated since we know the degree distribution # but the check node lists can be higher since the number of these is less than the number of variables # need to come up with an estimated average check node degree to preallocate - + # don't want the subgraph to be stored in an array because it will constantly grow and shrink # linked-list based structure most appropriate then @@ -31,6 +31,5 @@ # can most likely skip the latter and simply point to location in other array given ID # loop over this next layer and add them as children and make a RB tree out of them # arrange RB trees in each layer into a single array of RB tree pointers - -# end +# end diff --git a/src/LDPC/analysis.jl b/src/LDPC/analysis.jl index d741d6df..002d428a 100644 --- a/src/LDPC/analysis.jl +++ b/src/LDPC/analysis.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# # TODO: in tutorial, make sure we explain why we can't pass in L, R here @@ -22,10 +22,19 @@ function LDPCEnsemble(λ::PolyRingElem, ρ::PolyRingElem) r_avg = _compute_avg_degree(ρ) L, R = _compute_L_R(λ, ρ, l_avg, r_avg) design_rate = Float64(1 - l_avg / r_avg) - density_evo = Dict{AbstractClassicalNoiseChannel, NTuple{2, Vector{Float64}}}() - threshold = Dict{Type, Float64}() - return LDPCEnsemble(λ, ρ, L, R, Float64(l_avg), Float64(r_avg), design_rate, density_evo, - threshold) + density_evo = Dict{AbstractClassicalNoiseChannel,NTuple{2,Vector{Float64}}}() + threshold = Dict{Type,Float64}() + return LDPCEnsemble( + λ, + ρ, + L, + R, + Float64(l_avg), + Float64(r_avg), + design_rate, + density_evo, + threshold, + ) end # TODO: ERROR: MethodError: no method matching LDPCEnsemble(::QQPolyRingElem, ::QQPolyRingElem) @@ -38,31 +47,33 @@ degree distribution `ρ` of `L`, both from an edge perspective. LDPCEnsemble(L::AbstractLDPCCode) = LDPCEnsemble(L.λ, L.ρ) ############################# - # getter functions +# getter functions ############################# # do we not have getter functions for this type? ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# # TODO: are _d_poly(...) and _integrate_poly(...) useful? currently unused, probably delete -_d_poly(vec::Vector{<:Real}) = [vec[i] * (i - 1) for i in 2:length(vec)] +_d_poly(vec::Vector{<:Real}) = [vec[i] * (i - 1) for i = 2:length(vec)] _d_poly(f::PolyRingElem) = derivative(f) -_integrate_poly(vec::Vector{T}) where T <: Real = [zero(T); [c / i for (i, c) in enumerate(vec)]] +_integrate_poly(vec::Vector{T}) where {T<:Real} = + [zero(T); [c / i for (i, c) in enumerate(vec)]] _integrate_poly(f::PolyRingElem) = integral(f) # _poly_eval, _d_poly_eval, and _integrate_poly_0_1 are all used _poly_eval(x::Real, vec::Vector{<:Real}) = sum(c * x^(i - 1) for (i, c) in enumerate(vec)) _poly_eval(x::Real, f::PolyRingElem) = _poly_eval(x, Float64.(coeff.(f, 0:degree(f)))) -_d_poly_eval(x::Real, vec::Vector{<:Real}) = sum((i - 1) * c * x^(i - 2) for (i, c) in enumerate(vec)) +_d_poly_eval(x::Real, vec::Vector{<:Real}) = + sum((i - 1) * c * x^(i - 2) for (i, c) in enumerate(vec)) _d_poly_eval(x::Real, f::PolyRingElem) = _d_poly_eval(x, Float64.(coeff.(f, 0:degree(f)))) _integrate_poly_0_1(vec::Vector{<:Real}) = sum(c / i for (i, c) in enumerate(vec)) @@ -73,21 +84,29 @@ _integrate_poly_0_1(f::PolyRingElem) = _integrate_poly_0_1(Float64.(coeff.(f, 0: _binary_entropy(x::Real) = x * log2(1 / x) + (1 - x) * log2(1 / (1 - x)) # these should all be useful. Note that the QQ version of _compute_λ_ρ is necessary for the output to also be a QQPoly. The non-QQ version is for when the poly isn't directly callable (as in RealPoly) -_compute_avg_degree(f::PolyRingElem) = inv(sum(coeff(f, i) / (i + 1) for i in 0:degree(f))) -_compute_L_R(λ::PolyRingElem, ρ::PolyRingElem, l_avg, r_avg) = (integral(λ) * l_avg, integral(ρ) * r_avg) -_compute_L_R(λ::PolyRingElem, ρ::PolyRingElem) = _compute_L_R(λ, ρ, _compute_avg_degree(λ), _compute_avg_degree(ρ)) -_compute_λ_ρ(L::PolyRingElem, R::PolyRingElem) = (derivative(L) / _d_poly_eval(1, L), derivative(R) / _d_poly_eval(1, R)) -_compute_λ_ρ(L::QQPolyRingElem, R::QQPolyRingElem) = (derivative(L) / derivative(L)(1), derivative(R) / derivative(R)(1)) +_compute_avg_degree(f::PolyRingElem) = inv(sum(coeff(f, i) / (i + 1) for i = 0:degree(f))) +_compute_L_R(λ::PolyRingElem, ρ::PolyRingElem, l_avg, r_avg) = + (integral(λ) * l_avg, integral(ρ) * r_avg) +_compute_L_R(λ::PolyRingElem, ρ::PolyRingElem) = + _compute_L_R(λ, ρ, _compute_avg_degree(λ), _compute_avg_degree(ρ)) +_compute_λ_ρ(L::PolyRingElem, R::PolyRingElem) = + (derivative(L) / _d_poly_eval(1, L), derivative(R) / _d_poly_eval(1, R)) +_compute_λ_ρ(L::QQPolyRingElem, R::QQPolyRingElem) = + (derivative(L) / derivative(L)(1), derivative(R) / derivative(R)(1)) function _L2_dist_sq(p1::Vector{Float64}, p2::Vector{Float64}) @assert length(p1) == length(p2) v = p1 .- p2 - v2 = [sum(v[j] * v[k + 1 - j] for j in max(1, k + 1 - length(v)):min(k, length(v))) for k in 1:2length(v) - 1] + v2 = [ + sum(v[j] * v[k+1-j] for j = max(1, k+1-length(v)):min(k, length(v))) for + k = 1:(2length(v)-1) + ] return _integrate_poly_0_1(v2) end Base.hash(Ch::AbstractClassicalNoiseChannel) = hash(Ch.param, hash(typeof(Ch))) -Base.isequal(Ch1::AbstractClassicalNoiseChannel, Ch2::AbstractClassicalNoiseChannel) = typeof(Ch1) == typeof(Ch2) && Ch1.param == Ch2.param +Base.isequal(Ch1::AbstractClassicalNoiseChannel, Ch2::AbstractClassicalNoiseChannel) = + typeof(Ch1) == typeof(Ch2) && Ch1.param == Ch2.param # function Base.setproperty!(Ch::BAWGNChannel, key, val) # key == :capacity && (setfield!(Ch, key, val);) @@ -111,12 +130,18 @@ end Return the density evolution of the LDPC ensemble given the noise channel. """ function density_evolution(E::LDPCEnsemble, Ch::AbstractClassicalNoiseChannel) - Ch ∈ keys(E.density_evo) || _density_evolution!(E::LDPCEnsemble, Ch::AbstractClassicalNoiseChannel) + Ch ∈ keys(E.density_evo) || + _density_evolution!(E::LDPCEnsemble, Ch::AbstractClassicalNoiseChannel) return E.density_evo[Ch] end -function _density_evolution_BEC(λ::Vector{<:Real}, ρ::Vector{<:Real}, ε::Real; - max_iters::Int=500, tol::Float64=1e-9) +function _density_evolution_BEC( + λ::Vector{<:Real}, + ρ::Vector{<:Real}, + ε::Real; + max_iters::Int = 500, + tol::Float64 = 1e-9, +) iter = 0 evo_x = [ε] @@ -155,7 +180,9 @@ Return the multiplicative gap of the ensemble with respect to channel. Return a lower bound on the multiplicative gap of the ensemble """ -multiplicative_gap_lower_bound(E::LDPCEnsemble) = (E.design_rate^E.r_avg * (1 - E.design_rate)) / (1 + E.design_rate^E.r_avg * (1 - E.design_rate)) +multiplicative_gap_lower_bound(E::LDPCEnsemble) = + (E.design_rate^E.r_avg * (1 - E.design_rate)) / + (1 + E.design_rate^E.r_avg * (1 - E.design_rate)) """ density_lower_bound(Ch::AbstractClassicalNoiseChannel, gap::Real) @@ -167,7 +194,8 @@ function density_lower_bound(Ch::AbstractClassicalNoiseChannel, gap::Real) 0 < gap < 1 || throw(DomainError("Multiplicative gap should be in (0, 1)")) if isa(Ch, BinaryErasureChannel) temp = log(1 - Ch.param) - return (Ch.param * (log(gap) - (log(Ch.param) - temp))) / ((1 - Ch.param) * (1 - gap) * temp) + return (Ch.param * (log(gap) - (log(Ch.param) - temp))) / + ((1 - Ch.param) * (1 - gap) * temp) else @error "Not yet implemented" end @@ -197,8 +225,8 @@ function check_concentrated_degree_distribution(Ch::BinaryErasureChannel, gap::R λ_vec = zeros(N - 1) λ_vec[1] = α - for i in 2:N - 1 - λ_vec[i] = ((i - 1) / i) * (1 - α / (i - 1)) * λ_vec[i - 1] + for i = 2:(N-1) + λ_vec[i] = ((i - 1) / i) * (1 - α / (i - 1)) * λ_vec[i-1] end norm = sum(λ_vec) λ_vec ./= norm @@ -255,7 +283,11 @@ Given distributions λ and ρ, find the optimal threshold under BP. # Notes * For checking stability, it can be useful to use, e.g., `Δ = BigFloat("1e-7")` """ -function optimal_threshold(λ::Union{Vector{<:Real}, PolyRingElem}, ρ::Union{Vector{<:Real}, PolyRingElem}; Δ::T = 1e-4) where T <: Real +function optimal_threshold( + λ::Union{Vector{<:Real},PolyRingElem}, + ρ::Union{Vector{<:Real},PolyRingElem}; + Δ::T = 1e-4, +) where {T<:Real} xs = Δ:Δ:one(T) minimum(x / (_poly_eval(1 - _poly_eval(1 - x, ρ), λ)) for x in xs) diff --git a/src/LDPC/channels.jl b/src/LDPC/channels.jl index 060cd6d1..7ee7a457 100644 --- a/src/LDPC/channels.jl +++ b/src/LDPC/channels.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -49,7 +49,7 @@ BAWGNC(σ::Float64) = BAWGNChannel(σ) # TODO: add an issymmetric parameter to simplify DE later ############################# - # getter functions +# getter functions ############################# """ @@ -81,7 +81,7 @@ Return the variance of the BAWGN channel. variance(Ch::BAWGNChannel) = Ch.param^2 ############################# - # general functions +# general functions ############################# """ @@ -91,7 +91,7 @@ Return the capacity of the noise channel. """ function capacity(Ch::AbstractClassicalNoiseChannel) ismissing(Ch.capacity) || return Ch.capacity - + # TODO: compute capacity functional error("Not yet written") end @@ -100,9 +100,12 @@ function show(io::IO, Ch::AbstractClassicalNoiseChannel) if isa(Ch, BinaryErasureChannel) print(io, "Binary erasure channel with erasure probability $(Ch.param)") elseif isa(Ch, BinarySymmetricChannel) - print(io, "Binary symmetric channel with crossover probability $(Ch.param)") + print(io, "Binary symmetric channel with crossover probability $(Ch.param)") elseif isa(Ch, BAWGNChannel) - print(io, "Binary (input) additive white Gaussian noise channel with standard deviation $(Ch.param)") + print( + io, + "Binary (input) additive white Gaussian noise channel with standard deviation $(Ch.param)", + ) else print(io, "Classical noise channel with parameter $(Ch.param)") end diff --git a/src/LDPC/codes.jl b/src/LDPC/codes.jl index 55cb75fe..669067fd 100644 --- a/src/LDPC/codes.jl +++ b/src/LDPC/codes.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -21,12 +21,12 @@ function LDPCCode(H::CTMatrixTypes) cols, rows = _degree_distribution(H) is_reg = true c1 = cols[1] - for i in 2:length(cols) + for i = 2:length(cols) c1 == cols[i] || (is_reg = false; break;) end if is_reg r1 = rows[1] - for i in 2:length(rows) + for i = 2:length(rows) r1 == rows[i] || (is_reg = false; break;) end end @@ -45,9 +45,29 @@ function LDPCCode(H::CTMatrixTypes) row_poly = divexact(row_poly, nnz) C = LinearCode(H, true) - return LDPCCode(base_ring(H), C.n, C.k, C.d, C.l_bound, C.u_bound, H, nnz, - cols, rows, c, r, maximum([c, r]), den, is_reg, col_poly, - row_poly, missing, [Vector{Int}() for _ in 1:C.n], Vector{Vector{Int}}(), 0) + return LDPCCode( + base_ring(H), + C.n, + C.k, + C.d, + C.l_bound, + C.u_bound, + H, + nnz, + cols, + rows, + c, + r, + maximum([c, r]), + den, + is_reg, + col_poly, + row_poly, + missing, + [Vector{Int}() for _ = 1:C.n], + Vector{Vector{Int}}(), + 0, + ) end """ @@ -66,14 +86,21 @@ and row degree `r`. If a seed is given, i.e. `regular_LDPC_Code(4, 1200, 3, 6, seed=123)`, the results are reproducible. """ -function regular_LDPC_code(q::Int, n::Int, l::Int, r::Int; seed::Union{Nothing, Int} = nothing) +function regular_LDPC_code( + q::Int, + n::Int, + l::Int, + r::Int; + seed::Union{Nothing,Int} = nothing, +) Random.seed!(seed) m = divexact(n * l, r) F = if is_prime(q) Oscar.Nemo.Native.GF(q) else factors = Nemo.factor(q) - length(factors) == 1 || throw(DomainError("There is no finite field of order $q")) + length(factors) == 1 || + throw(DomainError("There is no finite field of order $q")) (p, t), = factors GF(p, t, :α) end @@ -81,7 +108,7 @@ function regular_LDPC_code(q::Int, n::Int, l::Int, r::Int; seed::Union{Nothing, H = zero_matrix(F, m, n) col_sums = zeros(Int, n) for i in axes(H, 1) - ind = reduce(vcat, shuffle(filter(k -> col_sums[k] == s, 1:n)) for s in 0:l - 1)[1:r] + ind = reduce(vcat, shuffle(filter(k -> col_sums[k] == s, 1:n)) for s = 0:(l-1))[1:r] for j in ind H[i, j] = rand(elems) end @@ -92,15 +119,35 @@ function regular_LDPC_code(q::Int, n::Int, l::Int, r::Int; seed::Union{Nothing, R, x = polynomial_ring(Nemo.QQ, :x) C = LinearCode(H, true) - return LDPCCode(C.F, C.n, C.k, C.d, C.l_bound, C.u_bound, H, n * l, l * ones(Int, n), - r * ones(Int, m), l, r, max(l, r), r / n, true, (1 // l) * x^l, (1 // r) * x^r, missing, - [Vector{Int}() for _ in 1:C.n], Vector{Vector{Int}}(), 0) + return LDPCCode( + C.F, + C.n, + C.k, + C.d, + C.l_bound, + C.u_bound, + H, + n * l, + l * ones(Int, n), + r * ones(Int, m), + l, + r, + max(l, r), + r / n, + true, + (1 // l) * x^l, + (1 // r) * x^r, + missing, + [Vector{Int}() for _ = 1:C.n], + Vector{Vector{Int}}(), + 0, + ) end -regular_LDPC_code(n::Int, l::Int, r::Int; seed::Union{Nothing, Int} = nothing) = +regular_LDPC_code(n::Int, l::Int, r::Int; seed::Union{Nothing,Int} = nothing) = regular_LDPC_code(2, n, l, r, seed = seed) ############################# - # getter functions +# getter functions ############################# """ @@ -184,24 +231,25 @@ Return the check degree polynomial of `C`. check_degree_polynomial(C::AbstractLDPCCode) = C.ρ ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# -function _degree_distribution(H::Union{CTMatrixTypes, - MatElem{EuclideanRingResidueRingElem{fpPolyRingElem}}}) +function _degree_distribution( + H::Union{CTMatrixTypes,MatElem{EuclideanRingResidueRingElem{fpPolyRingElem}}}, +) nr, nc = size(H) cols = zeros(Int, 1, nc) - @inbounds @views @simd for i in 1:nc + @inbounds @views @simd for i = 1:nc # cols[i] = wt(H[:, i]) cols[i] = count(x -> !iszero(x), H[:, i]) end rows = zeros(Int, 1, nr) - @inbounds @views @simd for i in 1:nr + @inbounds @views @simd for i = 1:nr # rows[i] = wt(H[i, :]) rows[i] = count(x -> !iszero(x), H[i, :]) end @@ -211,8 +259,8 @@ end function _density(H::CTMatrixTypes) count = 0 nr, nc = size(H) - for c in 1:nc - for r in 1:nr + for c = 1:nc + for r = 1:nr !iszero(H[r, c]) && (count += 1;) end end @@ -223,15 +271,27 @@ end function show(io::IO, C::AbstractLDPCCode) if ismissing(C.d) if C.is_reg - println(io, "[$(C.n), $(C.k)]_$(order(C.F)) regular ($(C.col_bound), $(C.row_bound))-LDPC code with density $(C.density).") + println( + io, + "[$(C.n), $(C.k)]_$(order(C.F)) regular ($(C.col_bound), $(C.row_bound))-LDPC code with density $(C.density).", + ) else - println(io, "[$(C.n), $(C.k)]_$(order(C.F)) irregular $(C.limited)-limited LDPC code with density $(C.density).") + println( + io, + "[$(C.n), $(C.k)]_$(order(C.F)) irregular $(C.limited)-limited LDPC code with density $(C.density).", + ) end else if C.is_reg - println(io, "[$(C.n), $(C.k), $(C.d)]_$(order(C.F)) regular ($(C.col_bound), $(C.row_bound))-LDPC code with density $(C.density).") + println( + io, + "[$(C.n), $(C.k), $(C.d)]_$(order(C.F)) regular ($(C.col_bound), $(C.row_bound))-LDPC code with density $(C.density).", + ) else - println(io, "[$(C.n), $(C.k), $(C.d)]_$(order(C.F)) irregular $(C.limited)-limited LDPC code with density $(C.density).") + println( + io, + "[$(C.n), $(C.k), $(C.d)]_$(order(C.F)) irregular $(C.limited)-limited LDPC code with density $(C.density).", + ) end end if get(io, :compact, true) @@ -243,9 +303,9 @@ function show(io::IO, C::AbstractLDPCCode) # was using Horig here, which is probably what I want nr, nc = size(C.H) println(io, "Parity-check matrix: $nr × $nc") - for i in 1:nr + for i = 1:nr print(io, "\t") - for j in 1:nc + for j = 1:nc if j != nc print(io, "$(C.H[i, j]) ") elseif j == nc && i != nr @@ -255,10 +315,10 @@ function show(io::IO, C::AbstractLDPCCode) end end end - # if !ismissing(C.weightenum) - # println(io, "\nComplete weight enumerator:") - # println(io, "\t", C.weightenum.polynomial) - # end + # if !ismissing(C.weightenum) + # println(io, "\nComplete weight enumerator:") + # println(io, "\t", C.weightenum.polynomial) + # end end end end diff --git a/src/LDPC/cycles.jl b/src/LDPC/cycles.jl index c200ff06..36de8e9e 100644 --- a/src/LDPC/cycles.jl +++ b/src/LDPC/cycles.jl @@ -5,19 +5,19 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# ############################# - # getter functions +# getter functions ############################# ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# """ @@ -31,15 +31,15 @@ An error is thrown if the maximum number of iterations is reached and function girth(C::AbstractLDPCCode; max_iter::Int = 100) check_adj_list, var_adj_list = _node_adjacencies(C.H) girth_arr = zeros(Int, C.n) - Threads.@threads for vn in 1:C.n + Threads.@threads for vn = 1:C.n iter = 0 not_found = true to_check = [(0, [vn])] while not_found iter += 1 - to_check_next = Vector{Tuple{Int, Vector{Int}}}() - for i in 1:length(to_check) - for (prev, v_arr) in (to_check[i], ) + to_check_next = Vector{Tuple{Int,Vector{Int}}}() + for i = 1:length(to_check) + for (prev, v_arr) in (to_check[i],) for v in v_arr for cn in var_adj_list[v] if cn != prev @@ -48,7 +48,10 @@ function girth(C::AbstractLDPCCode; max_iter::Int = 100) girth_arr[vn] = iter + 1 break else - push!(to_check_next, (cn, [v2 for v2 in check_adj_list[cn] if v2 != v])) + push!( + to_check_next, + (cn, [v2 for v2 in check_adj_list[cn] if v2 != v]), + ) end end end @@ -84,10 +87,11 @@ for node `v`. If `v_type` is `:v`, `v` is interpreted as a variable node; otherw """ function computation_graph end -function remove_cycles(H::Union{Matrix{<: Integer}, CTMatrixTypes}, n_max::Int) +function remove_cycles(H::Union{Matrix{<: Integer},CTMatrixTypes}, n_max::Int) n_max ≥ 4 || throw(DomainError("n_max must be an even number greater than four")) iseven(n_max) || (n_max -= 1;) - size(H, 1) ≥ 1 && size(H, 2) ≥ 1 || throw(ArgumentError("Matrix cannot have a zero dimension")) + size(H, 1) ≥ 1 && size(H, 2) ≥ 1 || + throw(ArgumentError("Matrix cannot have a zero dimension")) # also used in Tanner.jl, perhaps should make into its own function # A = _adjacency_matrix_from_code(H) @@ -95,44 +99,45 @@ function remove_cycles(H::Union{Matrix{<: Integer}, CTMatrixTypes}, n_max::Int) nr_H, nc_H = size(I) A = vcat(hcat(zeros(Int, nc_H, nc_H), transpose(I)), hcat(I, zeros(Int, nr_H, nr_H))) # display(A) - matrices = [A^i for i in 0:n_max - 1] + matrices = [A^i for i = 0:(n_max-1)] # for M in matrices # display(M) # println(" ") # end nr, nc = size(A) - for n in 4:2:n_max + for n = 4:2:n_max n2 = div(n, 2) n2m1 = n2 - 1 n2m2 = n2 - 2 nm1 = n - 1 - for i in 1:nr - for j in 1:nc + for i = 1:nr + for j = 1:nc if i ≠ j - if matrices[n2 + 1][i, j] ≥ 2 && iszero(matrices[n2m2 + 1][i, j]) + if matrices[n2+1][i, j] ≥ 2 && iszero(matrices[n2m2+1][i, j]) # println("$i, $j") # println(matrices[n2 + 1][i, j]) temp = Int[] - for k in 1:nc + for k = 1:nc # should be exactly two of these - if matrices[n2m1 + 1][i, k] > 0 && matrices[1 + 1][j, k] == 1 + if matrices[n2m1+1][i, k] > 0 && matrices[1+1][j, k] == 1 append!(temp, k) end end - + if !isempty(temp) k = rand(temp) C_e = Int[] - for x in 1:nc - if iszero(matrices[nm1 + 1][j, x]) && iszero(matrices[nm1 + 1][k, x]) + for x = 1:nc + if iszero(matrices[nm1+1][j, x]) && + iszero(matrices[nm1+1][k, x]) append!(C_e, x) end end - E_e = Vector{Tuple{Int, Int}}() + E_e = Vector{Tuple{Int,Int}}() for v1 in C_e for v2 in C_e - if matrices[1 + 1][v1, v2] > 0 + if matrices[1+1][v1, v2] > 0 push!(E_e, (v1, v2)) end end @@ -143,31 +148,55 @@ function remove_cycles(H::Union{Matrix{<: Integer}, CTMatrixTypes}, n_max::Int) (l, m) = rand(E_e) # println("here") # remove two old edges - matrices[1 + 1][j, k] -= 1 - matrices[1 + 1][k, j] -= 1 - matrices[1 + 1][l, m] -= 1 - matrices[1 + 1][m, l] -= 1 + matrices[1+1][j, k] -= 1 + matrices[1+1][k, j] -= 1 + matrices[1+1][l, m] -= 1 + matrices[1+1][m, l] -= 1 # add two new edges - matrices[1 + 1][j, m] += 1 - matrices[1 + 1][m, j] += 1 - matrices[1 + 1][l, k] += 1 - matrices[1 + 1][k, l] += 1 + matrices[1+1][j, m] += 1 + matrices[1+1][m, j] += 1 + matrices[1+1][l, k] += 1 + matrices[1+1][k, l] += 1 # update matrices in indices j, k, l, m - for indx in 2:n_max - 1 - for c in 1:nc - matrices[indx + 1][j, c] = dot(view(matrices[indx - 1 + 1], j, :), view(matrices[1 + 1], :, c)) - matrices[indx + 1][k, c] = dot(view(matrices[indx - 1 + 1], k, :), view(matrices[1 + 1], :, c)) - matrices[indx + 1][l, c] = dot(view(matrices[indx - 1 + 1], l, :), view(matrices[1 + 1], :, c)) - matrices[indx + 1][m, c] = dot(view(matrices[indx - 1 + 1], m, :), view(matrices[1 + 1], :, c)) + for indx = 2:(n_max-1) + for c = 1:nc + matrices[indx+1][j, c] = dot( + view(matrices[indx-1+1], j, :), + view(matrices[1+1], :, c), + ) + matrices[indx+1][k, c] = dot( + view(matrices[indx-1+1], k, :), + view(matrices[1+1], :, c), + ) + matrices[indx+1][l, c] = dot( + view(matrices[indx-1+1], l, :), + view(matrices[1+1], :, c), + ) + matrices[indx+1][m, c] = dot( + view(matrices[indx-1+1], m, :), + view(matrices[1+1], :, c), + ) end - for r in 1:nc - matrices[indx + 1][r, j] = dot(view(matrices[indx - 1 + 1], r, :), view(matrices[1 + 1], :, j)) - matrices[indx + 1][r, k] = dot(view(matrices[indx - 1 + 1], r, :), view(matrices[1 + 1], :, k)) - matrices[indx + 1][r, l] = dot(view(matrices[indx - 1 + 1], r, :), view(matrices[1 + 1], :, l)) - matrices[indx + 1][r, m] = dot(view(matrices[indx - 1 + 1], r, :), view(matrices[1 + 1], :, m)) + for r = 1:nc + matrices[indx+1][r, j] = dot( + view(matrices[indx-1+1], r, :), + view(matrices[1+1], :, j), + ) + matrices[indx+1][r, k] = dot( + view(matrices[indx-1+1], r, :), + view(matrices[1+1], :, k), + ) + matrices[indx+1][r, l] = dot( + view(matrices[indx-1+1], r, :), + view(matrices[1+1], :, l), + ) + matrices[indx+1][r, m] = dot( + view(matrices[indx-1+1], r, :), + view(matrices[1+1], :, m), + ) end end end @@ -178,37 +207,54 @@ function remove_cycles(H::Union{Matrix{<: Integer}, CTMatrixTypes}, n_max::Int) end end - return matrices[1 + 1][nc_H + 1:end, 1:nc_H] + return matrices[1+1][(nc_H+1):end, 1:nc_H] end -remove_cycles(L::LDPCCode, n_max::Int) = LDPCCode(remove_cycles(parity_check_matrix(L), n_max)) +remove_cycles(L::LDPCCode, n_max::Int) = + LDPCCode(remove_cycles(parity_check_matrix(L), n_max)) # remove_cycles(L::LDPCCode, n_max::Int) = remove_cycles(parity_check_matrix(L), n_max) ############################# - # simple cycles +# simple cycles ############################# # modified from implementation in Graphs.jl -function _modified_hawick_james(g::DiGraph{Int}, num_var_nodes::Int, - max_len::Int = 16) +function _modified_hawick_james(g::DiGraph{Int}, num_var_nodes::Int, max_len::Int = 16) # since this is bipartite, the input parameter tells you which are var nodes and which are # check nodes nvg = Graphs.nv(g) - local_cycles = [Vector{Vector{Int}}() for _ in 1:num_var_nodes] - Threads.@threads for i in 1:num_var_nodes + local_cycles = [Vector{Vector{Int}}() for _ = 1:num_var_nodes] + Threads.@threads for i = 1:num_var_nodes B = [Vector{Int}() for _ in Graphs.vertices(g)] blocked = zeros(Bool, nvg) stack = Vector{Int}() - keys_Dict = Dict{Vector{Int}, Bool}() - _circuit_recursive!(g, Graphs.vertices(g)[i], Graphs.vertices(g)[i], blocked, B, stack, - local_cycles[i], keys_Dict, max_len) + keys_Dict = Dict{Vector{Int},Bool}() + _circuit_recursive!( + g, + Graphs.vertices(g)[i], + Graphs.vertices(g)[i], + blocked, + B, + stack, + local_cycles[i], + keys_Dict, + max_len, + ) end return reduce(vcat, local_cycles) end -function _circuit_recursive!(g::DiGraph{Int}, v1::Int, v2::Int, blocked::Vector{Bool}, - B::Vector{Vector{Int}}, stack::Vector{Int}, cycles::Vector{Vector{Int}}, - keys_Dict::Dict{Vector{Int}, Bool}, max_len::Int) +function _circuit_recursive!( + g::DiGraph{Int}, + v1::Int, + v2::Int, + blocked::Vector{Bool}, + B::Vector{Vector{Int}}, + stack::Vector{Int}, + cycles::Vector{Vector{Int}}, + keys_Dict::Dict{Vector{Int},Bool}, + max_len::Int, +) if length(stack) + 1 <= max_len flag = false @@ -224,20 +270,36 @@ function _circuit_recursive!(g::DiGraph{Int}, v1::Int, v2::Int, blocked::Vector{ cycle = copy(stack) # println("cycle: $stack") # println("also checking: ", [cycle[1]; reverse(cycle[2:end])]) - if !haskey(keys_Dict, cycle) && !haskey(keys_Dict, [cycle[1]; reverse( - cycle[2:end])]) + if !haskey(keys_Dict, cycle) && + !haskey( + keys_Dict, + [ + cycle[1]; + reverse(cycle[2:end]) + ], + ) push!(cycles, cycle) keys_Dict[cycle] = true # println("is new") - # else - # println("is old") + # else + # println("is old") end end flag = true elseif !blocked[w] # bit-wise or - flag |= _circuit_recursive!(g, v1, w, blocked, B, stack, cycles, keys_Dict, max_len) + flag |= _circuit_recursive!( + g, + v1, + w, + blocked, + B, + stack, + cycles, + keys_Dict, + max_len, + ) end end @@ -251,7 +313,7 @@ function _circuit_recursive!(g::DiGraph{Int}, v1::Int, v2::Int, blocked::Vector{ end end end - + pop!(stack) else flag = true @@ -276,7 +338,7 @@ function _unblock!(v::Int, blocked::Vector{Bool}, B::Vector{Vector{Int}}) end ############################# - # simple cycles +# simple cycles ############################# function _enumerate_cycles(L::AbstractLDPCCode, len::Int) @@ -303,7 +365,7 @@ function _enumerate_cycles(L::AbstractLDPCCode, len::Int) end end end - + if !isempty(final_cycles) L.max_cyc_len = len L.simple_cycles = final_cycles @@ -333,7 +395,8 @@ is returned when there is no cycles. columns of `parity_check_matrix(L)` then top-to-bottom by rows. """ function enumerate_simple_cycles(L::AbstractLDPCCode; len::Int = 16) - ispositive(len) || throw(DomainError("Cycle length parameter must be a positive integer")) + ispositive(len) || + throw(DomainError("Cycle length parameter must be a positive integer")) # TODO add this variable to struct if len > L.max_cyc_len @@ -357,8 +420,8 @@ dictionary is returned when there are no cycles. - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -simple_cycle_length_distribution(L::AbstractLDPCCode; len::Int = 16) = StatsBase.countmap(length.( - enumerate_simple_cycles(L, len = len))) +simple_cycle_length_distribution(L::AbstractLDPCCode; len::Int = 16) = + StatsBase.countmap(length.(enumerate_simple_cycles(L, len = len))) """ simple_cycle_length_distribution_plot(L::AbstractLDPCCode; len::Int = 16) @@ -386,8 +449,8 @@ Return the average cycle length of unique simple cycles up to length `len` of th - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -average_simple_cycle_length(L::AbstractLDPCCode; len::Int = 16) = mean(length.( - enumerate_simple_cycles(L, len = len))) +average_simple_cycle_length(L::AbstractLDPCCode; len::Int = 16) = + mean(length.(enumerate_simple_cycles(L, len = len))) """ median_simple_cycle_length(L::AbstractLDPCCode; len::Int = 16) @@ -400,8 +463,8 @@ Return the median cycle length of unique simple cycles up to length `len` of the - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -median_simple_cycle_length(L::AbstractLDPCCode; len::Int = 16) = median(length.( - enumerate_simple_cycles(L, len = len))) +median_simple_cycle_length(L::AbstractLDPCCode; len::Int = 16) = + median(length.(enumerate_simple_cycles(L, len = len))) """ mode_simple_cycle_length(L::AbstractLDPCCode; len::Int = 16) @@ -414,8 +477,8 @@ of `L`. If `len` is `-1`, then all simple cycles will be enumerated. - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -mode_simple_cycle_length(L::AbstractLDPCCode; len::Int = 16) = StatsBase.mode(length.( - enumerate_simple_cycles(L, len = len))) +mode_simple_cycle_length(L::AbstractLDPCCode; len::Int = 16) = + StatsBase.mode(length.(enumerate_simple_cycles(L, len = len))) # TODO: there are ways to compute this without enumerating all of the cycles, but they are complicated and perhaps not worth the effort unless explicitly requested by a user """ @@ -429,8 +492,8 @@ of `L`. If `len` is `-1`, then all simple cycles will be enumerated. - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -count_simple_cycles(L::AbstractLDPCCode; len::Int = 16) = length(enumerate_simple_cycles(L, - len = len)) +count_simple_cycles(L::AbstractLDPCCode; len::Int = 16) = + length(enumerate_simple_cycles(L, len = len)) """ simple_cycle_distribution_by_variable_node(L::AbstractLDPCCode; len::Int = 16) @@ -445,7 +508,9 @@ dictionary is returned when there are no cycles. already cached. """ simple_cycle_distribution_by_variable_node(L::AbstractLDPCCode; len::Int = 16) = - StatsBase.countmap(filter(x -> x ≤ L.n, reduce(vcat, enumerate_simple_cycles(L, len = len)))) + StatsBase.countmap( + filter(x -> x ≤ L.n, reduce(vcat, enumerate_simple_cycles(L, len = len))), + ) # this works by removing the check nodes and then counting how many times each var node appears # not the most efficient since it makes several lists repeatedly but fine for now @@ -465,7 +530,7 @@ empty figure and dictionary are returned when there are no cycles. function simple_cycle_distribution_by_variable_node_plot end ############################# - # short cycles +# short cycles ############################# # TODO: time this versus calling girth and then doing the upper bound function @@ -484,8 +549,8 @@ is returned when there is no short cycles. - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -enumerate_short_cycles(L::AbstractLDPCCode; len::Int = 16) = filter(x -> length(x) <= - 2 * girth(L) - 2, _enumerate_cycles(L, len)) +enumerate_short_cycles(L::AbstractLDPCCode; len::Int = 16) = + filter(x -> length(x) <= 2 * girth(L) - 2, _enumerate_cycles(L, len)) """ short_cycle_length_distribution(L::AbstractLDPCCode; len::Int = 16) @@ -500,8 +565,8 @@ dictionary is returned when there are no cycles. - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -short_cycle_length_distribution(L::AbstractLDPCCode; len::Int = 16) = StatsBase.countmap(length.( - enumerate_short_cycles(L, len = len))) +short_cycle_length_distribution(L::AbstractLDPCCode; len::Int = 16) = + StatsBase.countmap(length.(enumerate_short_cycles(L, len = len))) """ short_cycle_length_distribution_plot(L::AbstractLDPCCode; len::Int = 16) @@ -531,8 +596,8 @@ Return the average cycle length of unique short cycles up to length `len` of the - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -average_short_cycle_length(L::AbstractLDPCCode; len::Int = 16) = mean(length.( - enumerate_short_cycles(L, len = len))) +average_short_cycle_length(L::AbstractLDPCCode; len::Int = 16) = + mean(length.(enumerate_short_cycles(L, len = len))) """ median_short_cycle_length(L::AbstractLDPCCode; len::Int = 16) @@ -546,8 +611,8 @@ Return the median cycle length of unique short cycles up to length `len` of the - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -median_short_cycle_length(L::AbstractLDPCCode; len::Int = 16) = median(length.( - enumerate_short_cycles(L, len = len))) +median_short_cycle_length(L::AbstractLDPCCode; len::Int = 16) = + median(length.(enumerate_short_cycles(L, len = len))) """ mode_short_cycle_length(L::AbstractLDPCCode; len::Int = 16) @@ -561,10 +626,10 @@ of `L`. If `len` is `-1`, then all short cycles will be enumerated. - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -mode_short_cycle_length(L::AbstractLDPCCode; len::Int = 16) = StatsBase.mode(length.( - enumerate_short_cycles(L, len = len))) +mode_short_cycle_length(L::AbstractLDPCCode; len::Int = 16) = + StatsBase.mode(length.(enumerate_short_cycles(L, len = len))) - """ +""" count_short_cycles(L::AbstractLDPCCode; len::Int = 16) Return the total number of unique short cycles up to length `len` of the Tanner graph @@ -576,8 +641,8 @@ of `L`. If `len` is `-1`, then all short cycles will be enumerated. - This function calls `enumerate_simple_cycles(L, len = len)`, which could be expensive if not already cached. """ -count_short_cycles(L::AbstractLDPCCode; len::Int = 16) = length(enumerate_short_cycles(L, - len = len)) +count_short_cycles(L::AbstractLDPCCode; len::Int = 16) = + length(enumerate_short_cycles(L, len = len)) """ short_cycle_distribution_by_variable_node(L::AbstractLDPCCode; len::Int = 16) @@ -593,7 +658,9 @@ dictionary is returned when there are no cycles. already cached. """ short_cycle_distribution_by_variable_node(L::AbstractLDPCCode; len::Int = 16) = - StatsBase.countmap(filter(x -> x ≤ L.n, reduce(vcat, enumerate_short_cycles(L, len = len)))) + StatsBase.countmap( + filter(x -> x ≤ L.n, reduce(vcat, enumerate_short_cycles(L, len = len))), + ) """ short_cycle_distribution_by_variable_node_plot(L::AbstractLDPCCode; len::Int = 16) @@ -612,7 +679,7 @@ empty figure and dictionary are returned when there are no cycles. function short_cycle_distribution_by_variable_node_plot end ############################# - # lollipops +# lollipops ############################# @@ -624,7 +691,7 @@ function short_cycle_distribution_by_variable_node_plot end ############################# - # ACE +# ACE ############################# mutable struct _ACEVarNode @@ -656,28 +723,31 @@ cn -- vn` is returned in the format `[(v1, c1), (c1, v2), ..., (cn, vn)]`. """ function shortest_cycle_ACE(C::AbstractLDPCCode, vs::Vector{Int}) isempty(vs) && throw(ArgumentError("Input variable node list cannot be empty")) - all(x -> 1 <= x <= C.n, vs) || throw(DomainError("Variable node indices must be between 1 and length(C)")) + all(x -> 1 <= x <= C.n, vs) || + throw(DomainError("Variable node indices must be between 1 and length(C)")) # might not be efficient to have the or here - vs_to_do = [x for x in vs if isempty(C.ACEs_per_var_node[x]) || isempty(C.shortest_cycles[x])] + vs_to_do = + [x for x in vs if isempty(C.ACEs_per_var_node[x]) || isempty(C.shortest_cycles[x])] processed = false if !isempty(vs_to_do) processed = true check_adj_list, var_adj_list = _node_adjacencies(C.H) - - Threads.@threads for i in 1:length(vs_to_do) + + Threads.@threads for i = 1:length(vs_to_do) # moving this inside allocates more but allows for multi-threading - check_nodes = [_ACECheckNode(j, -1, -1, -1) for j in 1:length(check_adj_list)] - var_nodes = [_ACEVarNode(j, -1, -1, -1, length(var_adj_list[j]) - 2) for j in 1:C.n] + check_nodes = [_ACECheckNode(j, -1, -1, -1) for j = 1:length(check_adj_list)] + var_nodes = + [_ACEVarNode(j, -1, -1, -1, length(var_adj_list[j]) - 2) for j = 1:C.n] ACEs = Vector{Int}() cycle_lens = Vector{Int}() - cycles = Vector{Vector{Tuple{Int, Int}}}() + cycles = Vector{Vector{Tuple{Int,Int}}}() not_emptied = true root = var_nodes[vs_to_do[i]] root.lvl = 0 root.cum_ACE = root.local_ACE - queue = Deque{Union{_ACECheckNode, _ACEVarNode}}() + queue = Deque{Union{_ACECheckNode,_ACEVarNode}}() push!(queue, root) while length(queue) > 0 curr = first(queue) @@ -692,7 +762,7 @@ function shortest_cycle_ACE(C::AbstractLDPCCode, vs::Vector{Int}) push!(cycle_lens, curr.lvl + cn_node.lvl + 1) # trace the cycle from curr to root and cn_node to root - temp = Vector{Tuple{Int, Int}}() + temp = Vector{Tuple{Int,Int}}() node = cn_node while node.lvl != 0 push!(temp, (node.parent_id, node.id)) @@ -746,7 +816,7 @@ function shortest_cycle_ACE(C::AbstractLDPCCode, vs::Vector{Int}) push!(cycle_lens, curr.lvl + vn_node.lvl + 1) # trace the cycle from curr to root and cn_node to root - temp = Vector{Tuple{Int, Int}}() + temp = Vector{Tuple{Int,Int}}() node = vn_node while node.lvl != 0 push!(temp, (node.parent_id, node.id)) @@ -800,8 +870,8 @@ function shortest_cycle_ACE(C::AbstractLDPCCode, vs::Vector{Int}) end vs_ACE = zeros(Int, length(vs)) - cycles_vs = [Vector{Tuple{Int, Int}}() for _ in 1:length(vs)] - for i in 1:length(vs) + cycles_vs = [Vector{Tuple{Int,Int}}() for _ = 1:length(vs)] + for i = 1:length(vs) min, index = findmin(C.ACEs_per_var_node[vs[i]]) vs_ACE[i] = min cycles_vs[i] = C.shortest_cycles[vs[i]][index] @@ -809,7 +879,7 @@ function shortest_cycle_ACE(C::AbstractLDPCCode, vs::Vector{Int}) if processed if all(!isempty, C.cycle_lens) - girth = minimum([minimum(C.cycle_lens[i]) for i in 1:C.n]) + girth = minimum([minimum(C.cycle_lens[i]) for i = 1:C.n]) if ismissing(C.girth) C.girth = girth else @@ -856,25 +926,27 @@ function ACE_distribution(C::AbstractLDPCCode, vs::Vector{Int}) # using the original DFS approach constructs a significantly larger tree than this truncated BFS approach isempty(vs) && throw(ArgumentError("Input node list cannot be empty")) - all(x -> 1 <= x <= C.n, vs) || throw(DomainError("Variable node index must be between 1 and length(C)")) + all(x -> 1 <= x <= C.n, vs) || + throw(DomainError("Variable node index must be between 1 and length(C)")) vs_to_do = [x for x in vs if isempty(C.ACEs_per_var_node[x])] processed = false if !isempty(vs_to_do) processed = true check_adj_list, var_adj_list = _node_adjacencies(C.H) - - Threads.@threads for i in 1:length(vs_to_do) + + Threads.@threads for i = 1:length(vs_to_do) # moving this inside allocates more but allows for multi-threading - check_nodes = [_ACECheckNode(i, -1, -1, -1) for i in 1:length(check_adj_list)] - var_nodes = [_ACEVarNode(i, -1, -1, -1, length(var_adj_list[i]) - 2) for i in 1:C.n] + check_nodes = [_ACECheckNode(i, -1, -1, -1) for i = 1:length(check_adj_list)] + var_nodes = + [_ACEVarNode(i, -1, -1, -1, length(var_adj_list[i]) - 2) for i = 1:C.n] ACEs = Vector{Int}() cycle_lens = Vector{Int}() root = var_nodes[vs[i]] root.lvl = 0 root.cum_ACE = root.local_ACE - queue = Queue{Union{_ACECheckNode, _ACEVarNode}}() + queue = Queue{Union{_ACECheckNode,_ACEVarNode}}() enqueue!(queue, root) while length(queue) > 0 curr = first(queue) @@ -1019,11 +1091,11 @@ function ACE_spectrum(C::AbstractLDPCCode) end end - counts = [Dict{Int, Int}() for _ in 1:length(girth:2:2 * girth - 2)] - for (k, l) in enumerate(girth:2:2 * girth - 2) - for i in 1:length(shortest_lens) + counts = [Dict{Int,Int}() for _ = 1:length(girth:2:(2*girth-2))] + for (k, l) in enumerate(girth:2:(2*girth-2)) + for i = 1:length(shortest_lens) if shortest_lens[i] == l - for j in 1:length(lengths[i]) + for j = 1:length(lengths[i]) if lengths[i][j] == l if vs_ACEs[i][j] ∈ keys(counts[k]) counts[k][vs_ACEs[i][j]] += 1 diff --git a/src/LDPC/decoders.jl b/src/LDPC/decoders.jl index 7409bab6..233fb152 100644 --- a/src/LDPC/decoders.jl +++ b/src/LDPC/decoders.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # MP Decoders +# MP Decoders ############################# # Example of using Gallager A and B (out should end up [1 1 1 0 0 0 0] @@ -18,8 +18,8 @@ struct MPNoiseModel type::Symbol - cross_over_prob::Union{Float64, Missing} - sigma::Union{Float64, Missing} + cross_over_prob::Union{Float64,Missing} + sigma::Union{Float64,Missing} end function MPNoiseModel(type::Symbol, x::Float64) @@ -32,72 +32,151 @@ function MPNoiseModel(type::Symbol, x::Float64) end end -function Gallager_A(H::T, v::T, max_iter::Int = 100) where T <: CTMatrixTypes - H_Int, w, var_adj_list, check_adj_list = _message_passing_init(H, v, missing, max_iter, :A, 2) - return _message_passing(H_Int, w, missing, _Gallager_A_check_node_message, var_adj_list, - check_adj_list, max_iter, :A) +function Gallager_A(H::T, v::T, max_iter::Int = 100) where {T<:CTMatrixTypes} + H_Int, w, var_adj_list, check_adj_list = + _message_passing_init(H, v, missing, max_iter, :A, 2) + return _message_passing( + H_Int, + w, + missing, + _Gallager_A_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :A, + ) end -function Gallager_B(H::T, v::T, max_iter::Int = 100, threshold::Int=2) where T <: CTMatrixTypes - H_Int, w, var_adj_list, check_adj_list = _message_passing_init(H, v, missing, max_iter, :B, - threshold) - return _message_passing(H_Int, w, missing, _Gallager_B_check_node_message, var_adj_list, - check_adj_list, max_iter, :B, threshold) +function Gallager_B( + H::T, + v::T, + max_iter::Int = 100, + threshold::Int = 2, +) where {T<:CTMatrixTypes} + H_Int, w, var_adj_list, check_adj_list = + _message_passing_init(H, v, missing, max_iter, :B, threshold) + return _message_passing( + H_Int, + w, + missing, + _Gallager_B_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :B, + threshold, + ) end -function sum_product(H::S, v::T, chn::MPNoiseModel, max_iter::Int = 100) where {S <: CTMatrixTypes, - T <: Union{Vector{<:Real}, CTMatrixTypes}} - - H_Int, w, var_adj_list, check_adj_list = _message_passing_init(H, v, chn, max_iter, :SP, 2) - return _message_passing(H_Int, w, chn, _SP_check_node_message, var_adj_list, check_adj_list, - max_iter, :SP) +function sum_product( + H::S, + v::T, + chn::MPNoiseModel, + max_iter::Int = 100, +) where {S<:CTMatrixTypes,T<:Union{Vector{<:Real},CTMatrixTypes}} + + H_Int, w, var_adj_list, check_adj_list = + _message_passing_init(H, v, chn, max_iter, :SP, 2) + return _message_passing( + H_Int, + w, + chn, + _SP_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :SP, + ) end -function sum_product_box_plus(H::S, v::T, chn::MPNoiseModel, max_iter::Int = 100) where {S <: - CTMatrixTypes, T <: Union{Vector{<:Real}, CTMatrixTypes}} - - H_Int, w, var_adj_list, check_adj_list = _message_passing_init(H, v, chn, max_iter, :SP, 2) - return _message_passing(H_Int, w, chn, _SP_check_node_message_box_plus, var_adj_list, - check_adj_list, max_iter, :SP) +function sum_product_box_plus( + H::S, + v::T, + chn::MPNoiseModel, + max_iter::Int = 100, +) where {S<:CTMatrixTypes,T<:Union{Vector{<:Real},CTMatrixTypes}} + + H_Int, w, var_adj_list, check_adj_list = + _message_passing_init(H, v, chn, max_iter, :SP, 2) + return _message_passing( + H_Int, + w, + chn, + _SP_check_node_message_box_plus, + var_adj_list, + check_adj_list, + max_iter, + :SP, + ) end -function min_sum(H::T, v::T, chn::MPNoiseModel, max_iter::Int = 100, attenuation::Float64 = - 0.5) where T <: CTMatrixTypes - - H_Int, w, var_adj_list, check_adj_list = _message_passing_init(H, v, chn, max_iter, :MS, 2) - return _message_passing(H_Int, w, chn, _MS_check_node_message, var_adj_list, check_adj_list, - max_iter, :MS, 0, attenuation) +function min_sum( + H::T, + v::T, + chn::MPNoiseModel, + max_iter::Int = 100, + attenuation::Float64 = 0.5, +) where {T<:CTMatrixTypes} + + H_Int, w, var_adj_list, check_adj_list = + _message_passing_init(H, v, chn, max_iter, :MS, 2) + return _message_passing( + H_Int, + w, + chn, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :MS, + 0, + attenuation, + ) end -function _message_passing_init(H::S, v::T, chn::Union{Missing, MPNoiseModel}, max_iter::Int, - kind::Symbol, Bt::Int) where {S <: CTMatrixTypes, T <: Union{Vector{<:Real}, CTMatrixTypes}} +function _message_passing_init( + H::S, + v::T, + chn::Union{Missing,MPNoiseModel}, + max_iter::Int, + kind::Symbol, + Bt::Int, +) where {S<:CTMatrixTypes,T<:Union{Vector{<:Real},CTMatrixTypes}} kind ∈ (:SP, :MS, :A, :B) || throw(ArgumentError("Unknown value for parameter kind")) - kind ∈ (:SP, :MS) && ismissing(chn) && throw(ArgumentError(":SP and :MS require a noise model")) + kind ∈ (:SP, :MS) && + ismissing(chn) && + throw(ArgumentError(":SP and :MS require a noise model")) Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) num_check, num_var = size(H) - num_check > 0 && num_var > 0 || throw(ArgumentError("Input matrix of improper dimension")) + num_check > 0 && num_var > 0 || + throw(ArgumentError("Input matrix of improper dimension")) length(v) == num_var || throw(ArgumentError("Vector has incorrect dimension")) (kind == :B && !(1 <= Bt <= num_check)) && throw(DomainError("Improper threshold for Gallager B")) 2 <= max_iter || throw(DomainError("Number of maximum iterations must be at least two")) - kind ∈ (:SP, :MS) && chn.type == :BAWGNC && !isa(v, Vector{<:AbstractFloat}) && + kind ∈ (:SP, :MS) && + chn.type == :BAWGNC && + !isa(v, Vector{<:AbstractFloat}) && throw(DomainError("Received message should be a vector of floats for BAWGNC.")) - kind ∈ (:SP, :MS) && chn.type == :BSC && !isa(v, Vector{Int}) && !isa(v, CTMatrixTypes) && + kind ∈ (:SP, :MS) && + chn.type == :BSC && + !isa(v, Vector{Int}) && + !isa(v, CTMatrixTypes) && throw(DomainError("Received message should be a vector of Ints for BSC.")) - + H_Int = FpmattoJulia(H) w = if T <: CTMatrixTypes Int.(data.(v)[:]) else copy(v) end - check_adj_list = [[] for _ in 1:num_check] - var_adj_list = [[] for _ in 1:num_var] + check_adj_list = [[] for _ = 1:num_check] + var_adj_list = [[] for _ = 1:num_var] - for r in 1:num_check - for c in 1:num_var + for r = 1:num_check + for c = 1:num_var if !iszero(H_Int[r, c]) push!(check_adj_list[r], c) push!(var_adj_list[c], r) @@ -113,10 +192,18 @@ function _message_passing_init(H::S, v::T, chn::Union{Missing, MPNoiseModel}, ma end # TODO: scheduling -function _message_passing(H::Matrix{UInt64}, w::Vector{T}, chn::Union{Missing, MPNoiseModel}, - c_to_v_mess::Function, var_adj_list::Vector{Vector{Any}}, check_adj_list::Vector{Vector{Any}}, - max_iter::Int, kind::Symbol, Bt::Int = 2, attenuation::Float64 = 0.5) where T <: Union{Int, - AbstractFloat} +function _message_passing( + H::Matrix{UInt64}, + w::Vector{T}, + chn::Union{Missing,MPNoiseModel}, + c_to_v_mess::Function, + var_adj_list::Vector{Vector{Any}}, + check_adj_list::Vector{Vector{Any}}, + max_iter::Int, + kind::Symbol, + Bt::Int = 2, + attenuation::Float64 = 0.5, +) where {T<:Union{Int,AbstractFloat}} num_check, num_var = size(H) S = kind ∈ (:A, :B) ? Int : Float64 @@ -128,7 +215,7 @@ function _message_passing(H::Matrix{UInt64}, w::Vector{T}, chn::Union{Missing, M max_iter += 1 # probably should copy this check_to_var_messages = zeros(S, num_check, num_var, max_iter) var_to_check_messages = zeros(S, num_var, num_check, max_iter) - + iter = 1 if kind in (:SP, :MS) chn_inits = if chn.type == :BSC @@ -138,25 +225,31 @@ function _message_passing(H::Matrix{UInt64}, w::Vector{T}, chn::Union{Missing, M elseif chn.type == :BAWGNC && kind == :MS _channel_init_BAWGNC_MS(w) end - for vn in 1:num_var + for vn = 1:num_var var_to_check_messages[vn, var_adj_list[vn], 1] .= chn_inits[vn] end elseif kind in (:A, :B) - for vn in 1:num_var + for vn = 1:num_var var_to_check_messages[vn, var_adj_list[vn], :] .= w[vn] end end while iter < max_iter - for cn in 1:num_check + for cn = 1:num_check for v1 in check_adj_list[cn] - check_to_var_messages[cn, v1, iter] = c_to_v_mess(cn, v1, iter, check_adj_list, - var_to_check_messages, attenuation) + check_to_var_messages[cn, v1, iter] = c_to_v_mess( + cn, + v1, + iter, + check_adj_list, + var_to_check_messages, + attenuation, + ) end end if kind in (:SP, :MS) - for vn in 1:num_var + for vn = 1:num_var totals[vn] = chn_inits[vn] for c in var_adj_list[vn] totals[vn] += check_to_var_messages[c, vn, iter] @@ -165,13 +258,14 @@ function _message_passing(H::Matrix{UInt64}, w::Vector{T}, chn::Union{Missing, M end if kind in (:SP, :MS) - @simd for i in 1:num_var + @simd for i = 1:num_var curr[i] = totals[i] >= 0 ? 0 : 1 end elseif kind in (:A, :B) - @simd for i in 1:num_var + @simd for i = 1:num_var len = length(var_adj_list[i]) - one_count = count(isone, view(check_to_var_messages, var_adj_list[i], i, iter)) + one_count = + count(isone, view(check_to_var_messages, var_adj_list[i], i, iter)) d = fld(len, 2) curr[i] = one_count + (isone(w[i]) && iseven(len)) > d end @@ -180,26 +274,33 @@ function _message_passing(H::Matrix{UInt64}, w::Vector{T}, chn::Union{Missing, M LinearAlgebra.mul!(syn, H, curr) # @show curr # @show syn .% 2 - iszero(syn .% 2) && return true, curr, iter, var_to_check_messages, check_to_var_messages + iszero(syn .% 2) && + return true, curr, iter, var_to_check_messages, check_to_var_messages iter += 1 if iter <= max_iter - for vn in 1:num_var + for vn = 1:num_var for c1 in var_adj_list[vn] if kind in (:SP, :MS) - var_to_check_messages[vn, c1, iter] = totals[vn] - - check_to_var_messages[c1, vn, iter - 1] + var_to_check_messages[vn, c1, iter] = + totals[vn] - check_to_var_messages[c1, vn, iter-1] elseif kind == :A && length(var_adj_list[vn]) > 1 - if all(!Base.isequal(w[vn]), check_to_var_messages[c2, vn, iter - 1] for c2 - in var_adj_list[vn] if c1 != c2) + if all( + !Base.isequal(w[vn]), + check_to_var_messages[c2, vn, iter-1] for + c2 in var_adj_list[vn] if c1 != c2 + ) - var_to_check_messages[vn, c1, iter] ⊻= 1 + var_to_check_messages[vn, c1, iter] ⊻= 1 end elseif kind == :B && length(var_adj_list[vn]) >= Bt - if count(!Base.isequal(w[vn]), check_to_var_messages[c2, vn, iter - 1] for - c2 in var_adj_list[vn] if c1 != c2) >= Bt + if count( + !Base.isequal(w[vn]), + check_to_var_messages[c2, vn, iter-1] for + c2 in var_adj_list[vn] if c1 != c2 + ) >= Bt - var_to_check_messages[vn, c1, iter] ⊻= 1 + var_to_check_messages[vn, c1, iter] ⊻= 1 end end end @@ -210,7 +311,7 @@ function _message_passing(H::Matrix{UInt64}, w::Vector{T}, chn::Union{Missing, M return false, curr, iter, var_to_check_messages, check_to_var_messages end -function _channel_init_BSC(v::Vector{T}, p::Float64) where T <: Integer +function _channel_init_BSC(v::Vector{T}, p::Float64) where {T<:Integer} temp = log((1 - p) / p) chn_init = zeros(Float64, length(v)) for i in eachindex(v) @@ -219,7 +320,7 @@ function _channel_init_BSC(v::Vector{T}, p::Float64) where T <: Integer return chn_init end -function _channel_init_BAWGNC_SP(v::Vector{T}, σ::Float64) where T <: AbstractFloat +function _channel_init_BAWGNC_SP(v::Vector{T}, σ::Float64) where {T<:AbstractFloat} temp = 2 / σ^2 chn_init = zeros(Float64, length(v)) for i in eachindex(v) @@ -228,10 +329,16 @@ function _channel_init_BAWGNC_SP(v::Vector{T}, σ::Float64) where T <: AbstractF return chn_init end -_channel_init_BAWGNC_MS(v::Vector{T}) where T <: AbstractFloat = v +_channel_init_BAWGNC_MS(v::Vector{T}) where {T<:AbstractFloat} = v -function _SP_check_node_message(cn::Int, v1::Int, iter, check_adj_list, var_to_check_messages, - atten = missing) +function _SP_check_node_message( + cn::Int, + v1::Int, + iter, + check_adj_list, + var_to_check_messages, + atten = missing, +) phi(x) = -log(tanh(0.5 * x)) temp = 0.0 @@ -255,14 +362,26 @@ end ⊞(a, b) = log((1 + exp(a + b)) / (exp(a) + exp(b))) ⊞(a...) = reduce(⊞, a...) -function _SP_check_node_message_box_plus(cn::Int, v1::Int, iter, check_adj_list, - var_to_check_messages, atten = missing) +function _SP_check_node_message_box_plus( + cn::Int, + v1::Int, + iter, + check_adj_list, + var_to_check_messages, + atten = missing, +) ⊞(var_to_check_messages[v2, cn, iter] for v2 in check_adj_list[cn] if v2 != v1) end -function _MS_check_node_message(cn::Int, v1::Int, iter, check_adj_list, var_to_check_messages, - attenuation::Float64 = 0.5) +function _MS_check_node_message( + cn::Int, + v1::Int, + iter, + check_adj_list, + var_to_check_messages, + attenuation::Float64 = 0.5, +) temp = var_to_check_messages[check_adj_list[cn][1], cn, iter] s = 1 @@ -281,47 +400,66 @@ function _MS_check_node_message(cn::Int, v1::Int, iter, check_adj_list, var_to_c return s * attenuation * temp end -function _Gallager_A_check_node_message(cn::Int, v1::Int, iter::Int, check_adj_list, - var_to_check_messages, atten = missing) +function _Gallager_A_check_node_message( + cn::Int, + v1::Int, + iter::Int, + check_adj_list, + var_to_check_messages, + atten = missing, +) reduce(⊻, var_to_check_messages[v, cn, iter] for v in check_adj_list[cn] if v != v1) end -_Gallager_B_check_node_message(cn::Int, v1::Int, iter::Int, check_adj_list, var_to_check_messages, - atten = missing) = _Gallager_A_check_node_message(cn, v1, iter, check_adj_list, - var_to_check_messages, atten) +_Gallager_B_check_node_message( + cn::Int, + v1::Int, + iter::Int, + check_adj_list, + var_to_check_messages, + atten = missing, +) = _Gallager_A_check_node_message( + cn, + v1, + iter, + check_adj_list, + var_to_check_messages, + atten, +) # Mansour, Shanbhag, "Turbo Decoder Architectures for Low-Density Parity-Check Codes" (2002) function find_MP_schedule(H::CodingTheory.CTMatrixTypes) num_check, num_var = size(H) - num_check > 0 && num_var > 0 || throw(ArgumentError("Input matrix of improper dimension")) + num_check > 0 && num_var > 0 || + throw(ArgumentError("Input matrix of improper dimension")) - check_adj_list = [[] for _ in 1:num_check] - for r in 1:num_check - for c in 1:num_var + check_adj_list = [[] for _ = 1:num_check] + for r = 1:num_check + for c = 1:num_var iszero(H[r, c]) || push!(check_adj_list[r], c) end end sched_list = [[1]] - for cn in 2:num_check + for cn = 2:num_check found = false for sched in sched_list if !any(x ∈ check_adj_list[y] for y in sched for x ∈ check_adj_list[cn]) push!(sched, cn) - sort!(sched_list, lt=(x, y) -> length(x) < length(y)) + sort!(sched_list, lt = (x, y) -> length(x) < length(y)) found = true break end end !found && push!(sched_list, [cn]) end - + return sched_list end ############################# - # LP Decoders +# LP Decoders ############################# # function _init_LP_decoder_LDPC end @@ -341,7 +479,7 @@ Return function LP_decoder_LDPC end ############################# - # Methods +# Methods ############################# function _channel_to_SNR(chn::MPNoiseModel) @@ -361,7 +499,7 @@ function _channel_to_SNR(type::Symbol, sigma::Real) end ############################# - # Simulations +# Simulations ############################# # function decodersimulation(H::CTMatrixTypes, decoder::Symbol, noisetype::Symbol, diff --git a/src/LDPC/simulations.jl b/src/LDPC/simulations.jl index f6a82eb2..3325d20d 100644 --- a/src/LDPC/simulations.jl +++ b/src/LDPC/simulations.jl @@ -5,13 +5,13 @@ # LICENSE file in the root directory of this source tree. ############################# - # Noise Model +# Noise Model ############################# struct MPNoiseModel type::Symbol - cross_over_prob::Union{Float64, Missing} - sigma::Union{Float64, Missing} + cross_over_prob::Union{Float64,Missing} + sigma::Union{Float64,Missing} end function MPNoiseModel(type::Symbol, x::Float64) @@ -25,15 +25,16 @@ function MPNoiseModel(type::Symbol, x::Float64) end ############################# - # Importance Sampling +# Importance Sampling ############################# -subset_probability(n::Int, wt::Int, p::Float64) = Float64(binomial(BigInt(n), BigInt(wt)) * - (BigFloat(p)^wt) * ((1 - BigFloat(p))^(n - wt))) +subset_probability(n::Int, wt::Int, p::Float64) = Float64( + binomial(BigInt(n), BigInt(wt)) * (BigFloat(p)^wt) * ((1 - BigFloat(p))^(n - wt)), +) function find_subsets(n::Int, p::Float64, tol::Float64) - subsets = Vector{Tuple{Int, Float64}}() - for i in 0:n + subsets = Vector{Tuple{Int,Float64}}() + for i = 0:n prob = subset_probability(n, i, p) if prob > tol push!(subsets, (i, prob)) @@ -66,7 +67,7 @@ function min_max_subsets(n::Int, p_arr::Vector{Float64}, tol::Float64) end ############################# - # Methods +# Methods ############################# function _channel_to_SNR(chn::MPNoiseModel) @@ -89,14 +90,14 @@ end # noise::Union{Vector{<:Real}, AbstractRange{<:Real}}, max_iter::Int = 100, num_runs::Union{Int, # Vector{Int}} = [100000 for n in noise], seed::Union{Int, Nothing} = nothing) - # decoder ∈ (:A, :B, :SP, :MS) || throw(ArgumentError("Unsupported decoder")) - # noise_type ∈ (:BSC, :BAWGNC) || throw(ArgumentError("Only supports BSC and BAWGNC")) - # decoder ∈ (:A, :B) && noise_type == :BAWGNC && throw(ArgumentError("BAWGNC not supported for Gallager decoders.")) - # 0 <= minimum(noise) || throw(ArgumentError("Must have non-negative noise")) - # maximum(noise) > 1 && noise_type == :BSC && throw(ArgumentError("Crossover probability must be in the range [0, 1]")) +# decoder ∈ (:A, :B, :SP, :MS) || throw(ArgumentError("Unsupported decoder")) +# noise_type ∈ (:BSC, :BAWGNC) || throw(ArgumentError("Only supports BSC and BAWGNC")) +# decoder ∈ (:A, :B) && noise_type == :BAWGNC && throw(ArgumentError("BAWGNC not supported for Gallager decoders.")) +# 0 <= minimum(noise) || throw(ArgumentError("Must have non-negative noise")) +# maximum(noise) > 1 && noise_type == :BSC && throw(ArgumentError("Crossover probability must be in the range [0, 1]")) function decoders_test(H::CTMatrixTypes; verbose::Bool = true) - # initial parameters + # initial parameters # noise is assumed to be sorted # noise = [5e-4, 0.001, 0.005, 0.01, 0.02, 0.03, 0.04, 0.05] left = 1e-4 @@ -120,7 +121,9 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) num_threads = Threads.nthreads() runs_per_thread = cld(num_runs, num_threads) new_num_runs = runs_per_thread * num_threads - verbose && println("Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs") + verbose && println( + "Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs", + ) # flooding # SP @@ -205,7 +208,7 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) # check which should be importance sampled imp_sam_ind = len_noise sort!(noise) - for i in 1:len_noise + for i = 1:len_noise # first probability where the expected value of the error weight under # direct sampling is nontrivial in a way that isn't going to severely # under estimate the FER @@ -219,36 +222,38 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) if imp_sam_ind ≠ 0 noise_impt = noise[1:imp_sam_ind] min_subset, max_subset = min_max_subsets(n, noise, tolerance) - subsets = [i for i in min_subset:max_subset] + subsets = [i for i = min_subset:max_subset] # flooding - subset_dic_SP = Dict{Int, Float64}() - subset_dic_SP_syn = Dict{Int, Float64}() - subset_dic_SP_dec = Dict{Int, Float64}() - subset_dic_MS = Dict{Int, Float64}() - subset_dic_MS_syn = Dict{Int, Float64}() - subset_dic_MS_dec = Dict{Int, Float64}() - subset_dic_MS_C = Dict{Int, Float64}() - subset_dic_MS_C_syn = Dict{Int, Float64}() - subset_dic_MS_C_dec = Dict{Int, Float64}() + subset_dic_SP = Dict{Int,Float64}() + subset_dic_SP_syn = Dict{Int,Float64}() + subset_dic_SP_dec = Dict{Int,Float64}() + subset_dic_MS = Dict{Int,Float64}() + subset_dic_MS_syn = Dict{Int,Float64}() + subset_dic_MS_dec = Dict{Int,Float64}() + subset_dic_MS_C = Dict{Int,Float64}() + subset_dic_MS_C_syn = Dict{Int,Float64}() + subset_dic_MS_C_dec = Dict{Int,Float64}() # serial - subset_dic_SP_s = Dict{Int, Float64}() - subset_dic_SP_syn_s = Dict{Int, Float64}() - subset_dic_SP_dec_s = Dict{Int, Float64}() - subset_dic_MS_s = Dict{Int, Float64}() - subset_dic_MS_syn_s = Dict{Int, Float64}() - subset_dic_MS_dec_s = Dict{Int, Float64}() - subset_dic_MS_C_s = Dict{Int, Float64}() - subset_dic_MS_C_syn_s = Dict{Int, Float64}() - subset_dic_MS_C_dec_s = Dict{Int, Float64}() + subset_dic_SP_s = Dict{Int,Float64}() + subset_dic_SP_syn_s = Dict{Int,Float64}() + subset_dic_SP_dec_s = Dict{Int,Float64}() + subset_dic_MS_s = Dict{Int,Float64}() + subset_dic_MS_syn_s = Dict{Int,Float64}() + subset_dic_MS_dec_s = Dict{Int,Float64}() + subset_dic_MS_C_s = Dict{Int,Float64}() + subset_dic_MS_C_syn_s = Dict{Int,Float64}() + subset_dic_MS_C_dec_s = Dict{Int,Float64}() first_fail_flag = false second_fail_flag = false if verbose println("Starting importance sampling on $(length(noise_impt)) noise values.") - println("Minimum subset: $min_subset, maximum subset: $max_subset, tolerance: $tolerance") + println( + "Minimum subset: $min_subset, maximum subset: $max_subset, tolerance: $tolerance", + ) end p = noise_impt[end] @@ -306,23 +311,56 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) subset_dic_MS_C_dec_s[s] = 1.0 else verbose && println("Subset $s") - Threads.@threads for th in 1:num_threads - # for th in 1:1 + Threads.@threads for th = 1:num_threads + # for th in 1:1 err = zeros(Int, n) err_locs = zeros(Int, s) syn_Int = zeros(Int, nr) erasures = Int[] chn_inits = zeros(Float64, n) # SP and MS for BSC - H_Int, _, var_adj_list, check_adj_list, chn_inits, check_to_var_messages_f, - var_to_check_messages_f, current_bits, totals, syn = _message_passing_init(H, v, chn, - max_iter, :SP, chn_inits, :flooding, erasures) - _, _, _, _, _, check_to_var_messages_s, var_to_check_messages_s, _, _, _ = - _message_passing_init(H, v, chn, max_iter, :SP, chn_inits, :serial, erasures) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits, + check_to_var_messages_f, + var_to_check_messages_f, + current_bits, + totals, + syn = _message_passing_init( + H, + v, + chn, + max_iter, + :SP, + chn_inits, + :flooding, + erasures, + ) + _, + _, + _, + _, + _, + check_to_var_messages_s, + var_to_check_messages_s, + _, + _, + _ = _message_passing_init( + H, + v, + chn, + max_iter, + :SP, + chn_inits, + :serial, + erasures, + ) # for syndrome-based we need to change the inits - chn_inits_syn = [log((1 - p) / p) for _ in 1:n] + chn_inits_syn = [log((1 - p) / p) for _ = 1:n] - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread # sample err[:] .= 0 chn_inits[:] .= init_0 @@ -332,7 +370,7 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) chn_inits[e] = init_1 end LinearAlgebra.mul!(syn_Int, H_Int, err) - @inbounds @simd for i in 1:nr + @inbounds @simd for i = 1:nr syn_Int[i] %= 2 end # pick a random bit to decimate @@ -340,137 +378,281 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) # decimated_bits = [bit] # # for now, setup as a genie-assisted decoder # decimated_values = [err[bit]] - + # flooding # run SP - flag, out, _ = _message_passing(H_Int, missing, chn_inits, - _SP_check_node_message_box_plus, var_adj_list, check_adj_list, - max_iter, :flooding, current_bits, totals, syn, - check_to_var_messages_f, var_to_check_messages_f, 0.0) + flag, out, _ = _message_passing( + H_Int, + missing, + chn_inits, + _SP_check_node_message_box_plus, + var_adj_list, + check_adj_list, + max_iter, + :flooding, + current_bits, + totals, + syn, + check_to_var_messages_f, + var_to_check_messages_f, + 0.0, + ) (!flag || !iszero(out)) && (local_counts_SP[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_f[:, :, :] .= 0.0 var_to_check_messages_f[:, :, :] .= 0.0 - + # run syndrome-based SP - flag, out, _, = _message_passing(H_Int, syn_Int, chn_inits_syn, - _SP_check_node_message_box_plus, var_adj_list, check_adj_list, - max_iter, :flooding, current_bits, totals, syn, - check_to_var_messages_f, var_to_check_messages_f, 0.0) + flag, out, _, = _message_passing( + H_Int, + syn_Int, + chn_inits_syn, + _SP_check_node_message_box_plus, + var_adj_list, + check_adj_list, + max_iter, + :flooding, + current_bits, + totals, + syn, + check_to_var_messages_f, + var_to_check_messages_f, + 0.0, + ) (!flag || out ≠ err) && (local_counts_SP_syn[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_f[:, :, :] .= 0.0 var_to_check_messages_f[:, :, :] .= 0.0 - + # run MS - flag, out, _ = _message_passing(H_Int, missing, chn_inits, - _MS_check_node_message, var_adj_list, check_adj_list, max_iter, - :flooding, current_bits, totals, syn, check_to_var_messages_f, - var_to_check_messages_f, attenuation) + flag, out, _ = _message_passing( + H_Int, + missing, + chn_inits, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :flooding, + current_bits, + totals, + syn, + check_to_var_messages_f, + var_to_check_messages_f, + attenuation, + ) (!flag && !iszero(out)) && (local_counts_MS[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_f[:, :, :] .= 0.0 var_to_check_messages_f[:, :, :] .= 0.0 - + # run syndrome-based MS - flag, out, _, = _message_passing(H_Int, syn_Int, chn_inits_syn, - _MS_check_node_message, var_adj_list, check_adj_list, max_iter, - :flooding, current_bits, totals, syn, check_to_var_messages_f, - var_to_check_messages_f, 0.0) + flag, out, _, = _message_passing( + H_Int, + syn_Int, + chn_inits_syn, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :flooding, + current_bits, + totals, + syn, + check_to_var_messages_f, + var_to_check_messages_f, + 0.0, + ) (!flag && out ≠ err) && (local_counts_MS_syn[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_f[:, :, :] .= 0.0 var_to_check_messages_f[:, :, :] .= 0.0 - + # run MS with correction - flag, out, _ = _message_passing(H_Int, missing, chn_inits, - _MS_correction_check_node_message, var_adj_list, check_adj_list, - max_iter, :flooding, current_bits, totals, syn, - check_to_var_messages_f, var_to_check_messages_f, attenuation) + flag, out, _ = _message_passing( + H_Int, + missing, + chn_inits, + _MS_correction_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :flooding, + current_bits, + totals, + syn, + check_to_var_messages_f, + var_to_check_messages_f, + attenuation, + ) (!flag || !iszero(out)) && (local_counts_MS_C[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_f[:, :, :] .= 0.0 var_to_check_messages_f[:, :, :] .= 0.0 - + # run syndrome-based MS with correction - flag, out, _, = _message_passing(H_Int, syn_Int, chn_inits_syn, - _MS_correction_check_node_message, var_adj_list, check_adj_list, - max_iter, :flooding, current_bits, totals, syn, - check_to_var_messages_f, var_to_check_messages_f, attenuation) + flag, out, _, = _message_passing( + H_Int, + syn_Int, + chn_inits_syn, + _MS_correction_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :flooding, + current_bits, + totals, + syn, + check_to_var_messages_f, + var_to_check_messages_f, + attenuation, + ) (!flag || out ≠ err) && (local_counts_MS_C_syn[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_f[:, :, :] .= 0.0 var_to_check_messages_f[:, :, :] .= 0.0 - + # serial # run SP - flag, out, _ = _message_passing(H_Int, missing, chn_inits, - _SP_check_node_message_box_plus, var_adj_list, check_adj_list, - max_iter, :serial, current_bits, totals, syn, check_to_var_messages_s, - var_to_check_messages_s, 0.0) + flag, out, _ = _message_passing( + H_Int, + missing, + chn_inits, + _SP_check_node_message_box_plus, + var_adj_list, + check_adj_list, + max_iter, + :serial, + current_bits, + totals, + syn, + check_to_var_messages_s, + var_to_check_messages_s, + 0.0, + ) (!flag || !iszero(out)) && (local_counts_SP_s[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_s[:, :, :] .= 0.0 var_to_check_messages_s[:, :, :] .= 0.0 - + # run syndrome-based SP - flag, out, _, = _message_passing(H_Int, syn_Int, chn_inits_syn, - _SP_check_node_message_box_plus, var_adj_list, check_adj_list, - max_iter, :serial, current_bits, totals, syn, check_to_var_messages_s, - var_to_check_messages_s, 0.0) + flag, out, _, = _message_passing( + H_Int, + syn_Int, + chn_inits_syn, + _SP_check_node_message_box_plus, + var_adj_list, + check_adj_list, + max_iter, + :serial, + current_bits, + totals, + syn, + check_to_var_messages_s, + var_to_check_messages_s, + 0.0, + ) (!flag || out ≠ err) && (local_counts_SP_syn_s[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_s[:, :, :] .= 0.0 var_to_check_messages_s[:, :, :] .= 0.0 - + # run MS - flag, out, _ = _message_passing(H_Int, missing, chn_inits, - _MS_check_node_message, var_adj_list, check_adj_list, max_iter, - :serial, current_bits, totals, syn, check_to_var_messages_s, - var_to_check_messages_s, attenuation) + flag, out, _ = _message_passing( + H_Int, + missing, + chn_inits, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :serial, + current_bits, + totals, + syn, + check_to_var_messages_s, + var_to_check_messages_s, + attenuation, + ) (!flag && !iszero(out)) && (local_counts_MS_s[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_s[:, :, :] .= 0.0 var_to_check_messages_s[:, :, :] .= 0.0 - + # run syndrome-based MS - flag, out, _, = _message_passing(H_Int, syn_Int, chn_inits_syn, - _MS_check_node_message, var_adj_list, check_adj_list, max_iter, - :serial, current_bits, totals, syn, check_to_var_messages_s, - var_to_check_messages_s, 0.0) + flag, out, _, = _message_passing( + H_Int, + syn_Int, + chn_inits_syn, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :serial, + current_bits, + totals, + syn, + check_to_var_messages_s, + var_to_check_messages_s, + 0.0, + ) (!flag && out ≠ err) && (local_counts_MS_syn_s[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_s[:, :, :] .= 0.0 var_to_check_messages_s[:, :, :] .= 0.0 - + # run MS with correction - flag, out, _ = _message_passing(H_Int, missing, chn_inits, - _MS_correction_check_node_message, var_adj_list, check_adj_list, - max_iter, :serial, current_bits, totals, syn, check_to_var_messages_s, - var_to_check_messages_s, attenuation) + flag, out, _ = _message_passing( + H_Int, + missing, + chn_inits, + _MS_correction_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :serial, + current_bits, + totals, + syn, + check_to_var_messages_s, + var_to_check_messages_s, + attenuation, + ) (!flag || !iszero(out)) && (local_counts_MS_C_s[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_s[:, :, :] .= 0.0 var_to_check_messages_s[:, :, :] .= 0.0 - + # run syndrome-based MS with correction - flag, out, _, = _message_passing(H_Int, syn_Int, chn_inits_syn, - _MS_correction_check_node_message, var_adj_list, check_adj_list, - max_iter, :serial, current_bits, totals, syn, check_to_var_messages_s, - var_to_check_messages_s, attenuation) + flag, out, _, = _message_passing( + H_Int, + syn_Int, + chn_inits_syn, + _MS_correction_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + :serial, + current_bits, + totals, + syn, + check_to_var_messages_s, + var_to_check_messages_s, + attenuation, + ) (!flag || out ≠ err) && (local_counts_MS_C_syn_s[th] += 1;) - + # reset inputs for next run, but don't re-allocate new memory check_to_var_messages_s[:, :, :] .= 0.0 var_to_check_messages_s[:, :, :] .= 0.0 @@ -506,7 +688,9 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) if !second_fail_flag second_fail_flag = true verbose && println("Second short circuit flag set at subset $s") - verbose && println("Short circuiting importance sampling after subset $s") + verbose && println( + "Short circuiting importance sampling after subset $s", + ) end else first_fail_flag = true @@ -537,7 +721,7 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) local_counts_MS_C_dec_s[:] .= 0 end end - + for (i, p) in enumerate(noise_impt) subsets = find_subsets(n, p, tolerance) for s in subsets @@ -594,7 +778,7 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) local_counts_MS_C_dec_s[:] .= 0 end - for i in imp_sam_ind + 1:len_noise + for i = (imp_sam_ind+1):len_noise p = noise[i] println("Starting p = $p") # initialize everything for p @@ -602,24 +786,58 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) init_0 = log((1 - p) / p) init_1 = log(p / (1 - p)) - Threads.@threads for th in 1:num_threads + Threads.@threads for th = 1:num_threads err_dir = zeros(Int, n) syn_Int_dir = zeros(Int, nr) erasures_dir = Int[] chn_inits_dir = zeros(Float64, n) # SP and MS - H_Int_dir, _, var_adj_list_dir, check_adj_list_dir, chn_inits_dir, check_to_var_messages_f_dir, - var_to_check_messages_f_dir, current_bits_dir, totals_dir, syn_dir = _message_passing_init(H, - v, chn, max_iter, :SP, chn_inits_dir, :flooding, erasures_dir) - _, _, _, _, _, check_to_var_messages_s_dir, var_to_check_messages_s_dir, _, _, _ = - _message_passing_init(H, v, chn, max_iter, :SP, chn_inits_dir, :serial, erasures_dir) + H_Int_dir, + _, + var_adj_list_dir, + check_adj_list_dir, + chn_inits_dir, + check_to_var_messages_f_dir, + var_to_check_messages_f_dir, + current_bits_dir, + totals_dir, + syn_dir = _message_passing_init( + H, + v, + chn, + max_iter, + :SP, + chn_inits_dir, + :flooding, + erasures_dir, + ) + _, + _, + _, + _, + _, + check_to_var_messages_s_dir, + var_to_check_messages_s_dir, + _, + _, + _ = _message_passing_init( + H, + v, + chn, + max_iter, + :SP, + chn_inits_dir, + :serial, + erasures_dir, + ) # for syndrome-based we need to change the inits - chn_inits_syn_dir = [init_0 for _ in 1:n] + chn_inits_syn_dir = [init_0 for _ = 1:n] - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread # sample - @inbounds for j in 1:n - rand(dist) ≤ p ? (err_dir[j] = 1; chn_inits_dir[j] = init_1;) : (err_dir[j] = 0; chn_inits_dir[j] = init_0;) + @inbounds for j = 1:n + rand(dist) ≤ p ? (err_dir[j] = 1; chn_inits_dir[j] = init_1;) : + (err_dir[j] = 0; chn_inits_dir[j] = init_0;) end # err = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] # chn_inits = [init_0 for _ in 1:n] @@ -627,7 +845,7 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) # th == 1 && println(err) # println("thread: $th, weight: $wt") LinearAlgebra.mul!(syn_Int_dir, H_Int_dir, err_dir) - @inbounds @simd for i in 1:nr + @inbounds @simd for i = 1:nr syn_Int_dir[i] %= 2 end # pick a random bit to decimate @@ -638,10 +856,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) # flooding # run SP - flag_dir, out_dir, _ = _message_passing(H_Int_dir, missing, chn_inits_dir, - _SP_check_node_message_box_plus, var_adj_list_dir, check_adj_list_dir, max_iter, - :flooding, current_bits_dir, totals_dir, syn_dir, check_to_var_messages_f_dir, - var_to_check_messages_f_dir, 0.0) + flag_dir, out_dir, _ = _message_passing( + H_Int_dir, + missing, + chn_inits_dir, + _SP_check_node_message_box_plus, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :flooding, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_f_dir, + var_to_check_messages_f_dir, + 0.0, + ) (!flag_dir || !iszero(out_dir)) && (local_counts_SP[th] += 1;) # if th == 1 && !iszero(out) # println("out = $out;") @@ -657,9 +887,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_f_dir[:, :, :] .= 0.0 # run syndrome-based SP - flag_dir, out_dir, _, = _message_passing(H_Int_dir, syn_Int_dir, chn_inits_syn_dir, - _SP_check_node_message_box_plus, var_adj_list_dir, check_adj_list_dir, max_iter, :flooding, - current_bits_dir, totals_dir, syn_dir, check_to_var_messages_f_dir, var_to_check_messages_f_dir, 0.0) + flag_dir, out_dir, _, = _message_passing( + H_Int_dir, + syn_Int_dir, + chn_inits_syn_dir, + _SP_check_node_message_box_plus, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :flooding, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_f_dir, + var_to_check_messages_f_dir, + 0.0, + ) (!flag_dir || out_dir ≠ err_dir) && (local_counts_SP_syn[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -667,9 +910,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_f_dir[:, :, :] .= 0.0 # run MS - flag_dir, out_dir, _ = _message_passing(H_Int_dir, missing, chn_inits_dir, _MS_check_node_message, - var_adj_list_dir, check_adj_list_dir, max_iter, :flooding, current_bits_dir, totals_dir, syn_dir, - check_to_var_messages_f_dir, var_to_check_messages_f_dir, attenuation) + flag_dir, out_dir, _ = _message_passing( + H_Int_dir, + missing, + chn_inits_dir, + _MS_check_node_message, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :flooding, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_f_dir, + var_to_check_messages_f_dir, + attenuation, + ) (!flag_dir && !iszero(out_dir)) && (local_counts_MS[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -677,9 +933,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_f_dir[:, :, :] .= 0.0 # run syndrome-based MS - flag_dir, out_dir, _, = _message_passing(H_Int_dir, syn_Int_dir, chn_inits_syn_dir, - _MS_check_node_message, var_adj_list_dir, check_adj_list_dir, max_iter, :flooding, - current_bits_dir, totals_dir, syn_dir, check_to_var_messages_f_dir, var_to_check_messages_f_dir, 0.0) + flag_dir, out_dir, _, = _message_passing( + H_Int_dir, + syn_Int_dir, + chn_inits_syn_dir, + _MS_check_node_message, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :flooding, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_f_dir, + var_to_check_messages_f_dir, + 0.0, + ) (!flag_dir && out_dir ≠ err_dir) && (local_counts_MS_syn[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -687,9 +956,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_f_dir[:, :, :] .= 0.0 # run MS with correction - flag_dir, out_dir, _ = _message_passing(H_Int_dir, missing, chn_inits_dir, _MS_correction_check_node_message, - var_adj_list_dir, check_adj_list_dir, max_iter, :flooding, current_bits_dir, totals_dir, syn_dir, - check_to_var_messages_f_dir, var_to_check_messages_f_dir, attenuation) + flag_dir, out_dir, _ = _message_passing( + H_Int_dir, + missing, + chn_inits_dir, + _MS_correction_check_node_message, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :flooding, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_f_dir, + var_to_check_messages_f_dir, + attenuation, + ) (!flag_dir || !iszero(out_dir)) && (local_counts_MS_C[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -697,9 +979,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_f_dir[:, :, :] .= 0.0 # run syndrome-based MS with correction - flag_dir, out_dir, _, = _message_passing(H_Int_dir, syn_Int_dir, chn_inits_syn_dir, - _MS_correction_check_node_message, var_adj_list_dir, check_adj_list_dir, max_iter, :flooding, - current_bits_dir, totals_dir, syn_dir, check_to_var_messages_f_dir, var_to_check_messages_f_dir, attenuation) + flag_dir, out_dir, _, = _message_passing( + H_Int_dir, + syn_Int_dir, + chn_inits_syn_dir, + _MS_correction_check_node_message, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :flooding, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_f_dir, + var_to_check_messages_f_dir, + attenuation, + ) (!flag_dir || out_dir ≠ err_dir) && (local_counts_MS_C_syn[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -708,9 +1003,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) # serial # run SP - flag_dir, out_dir, _ = _message_passing(H_Int_dir, missing, chn_inits_dir, _SP_check_node_message_box_plus, - var_adj_list_dir, check_adj_list_dir, max_iter, :serial, current_bits_dir, totals_dir, syn_dir, - check_to_var_messages_s_dir, var_to_check_messages_s_dir, 0.0) + flag_dir, out_dir, _ = _message_passing( + H_Int_dir, + missing, + chn_inits_dir, + _SP_check_node_message_box_plus, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :serial, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_s_dir, + var_to_check_messages_s_dir, + 0.0, + ) (!flag_dir || !iszero(out_dir)) && (local_counts_SP_s[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -718,9 +1026,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_s_dir[:, :, :] .= 0.0 # run syndrome-based SP - flag_dir, out_dir, _, = _message_passing(H_Int_dir, syn_Int_dir, chn_inits_syn_dir, - _SP_check_node_message_box_plus, var_adj_list_dir, check_adj_list_dir, max_iter, :serial, - current_bits_dir, totals_dir, syn_dir, check_to_var_messages_s_dir, var_to_check_messages_s_dir, 0.0) + flag_dir, out_dir, _, = _message_passing( + H_Int_dir, + syn_Int_dir, + chn_inits_syn_dir, + _SP_check_node_message_box_plus, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :serial, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_s_dir, + var_to_check_messages_s_dir, + 0.0, + ) (!flag_dir || out_dir ≠ err_dir) && (local_counts_SP_syn_s[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -728,9 +1049,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_s_dir[:, :, :] .= 0.0 # run MS - flag_dir, out_dir, _ = _message_passing(H_Int_dir, missing, chn_inits_dir, _MS_check_node_message, - var_adj_list_dir, check_adj_list_dir, max_iter, :serial, current_bits_dir, totals_dir, syn_dir, - check_to_var_messages_s_dir, var_to_check_messages_s_dir, attenuation) + flag_dir, out_dir, _ = _message_passing( + H_Int_dir, + missing, + chn_inits_dir, + _MS_check_node_message, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :serial, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_s_dir, + var_to_check_messages_s_dir, + attenuation, + ) (!flag_dir && !iszero(out_dir)) && (local_counts_MS_s[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -738,9 +1072,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_s_dir[:, :, :] .= 0.0 # run syndrome-based MS - flag_dir, out_dir, _, = _message_passing(H_Int_dir, syn_Int_dir, chn_inits_syn_dir, - _MS_check_node_message, var_adj_list_dir, check_adj_list_dir, max_iter, :serial, - current_bits_dir, totals_dir, syn_dir, check_to_var_messages_s_dir, var_to_check_messages_s_dir, 0.0) + flag_dir, out_dir, _, = _message_passing( + H_Int_dir, + syn_Int_dir, + chn_inits_syn_dir, + _MS_check_node_message, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :serial, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_s_dir, + var_to_check_messages_s_dir, + 0.0, + ) (!flag_dir && out_dir ≠ err_dir) && (local_counts_MS_syn_s[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -748,9 +1095,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_s_dir[:, :, :] .= 0.0 # run MS with correction - flag_dir, out_dir, _ = _message_passing(H_Int_dir, missing, chn_inits_dir, _MS_correction_check_node_message, - var_adj_list_dir, check_adj_list_dir, max_iter, :serial, current_bits_dir, totals_dir, syn_dir, - check_to_var_messages_s_dir, var_to_check_messages_s_dir, attenuation) + flag_dir, out_dir, _ = _message_passing( + H_Int_dir, + missing, + chn_inits_dir, + _MS_correction_check_node_message, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :serial, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_s_dir, + var_to_check_messages_s_dir, + attenuation, + ) (!flag_dir || !iszero(out_dir)) && (local_counts_MS_C_s[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -758,9 +1118,22 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) var_to_check_messages_s_dir[:, :, :] .= 0.0 # run syndrome-based MS with correction - flag_dir, out_dir, _, = _message_passing(H_Int_dir, syn_Int_dir, chn_inits_syn_dir, - _MS_correction_check_node_message, var_adj_list_dir, check_adj_list_dir, max_iter, :serial, - current_bits_dir, totals_dir, syn_dir, check_to_var_messages_s_dir, var_to_check_messages_s_dir, attenuation) + flag_dir, out_dir, _, = _message_passing( + H_Int_dir, + syn_Int_dir, + chn_inits_syn_dir, + _MS_correction_check_node_message, + var_adj_list_dir, + check_adj_list_dir, + max_iter, + :serial, + current_bits_dir, + totals_dir, + syn_dir, + check_to_var_messages_s_dir, + var_to_check_messages_s_dir, + attenuation, + ) (!flag_dir || out_dir ≠ err_dir) && (local_counts_MS_C_syn_s[th] += 1;) # reset inputs for next run, but don't re-allocate new memory @@ -814,13 +1187,46 @@ function decoders_test(H::CTMatrixTypes; verbose::Bool = true) local_counts_MS_C_s[:] .= 0 local_counts_MS_C_syn_s[:] .= 0 local_counts_MS_C_dec_s[:] .= 0 - + println("Finished p = $p") end end - return FER_SP, FER_SP_syn, FER_SP_dec, FER_MS, FER_MS_syn, FER_MS_dec, FER_MS_C, FER_MS_C_syn, - FER_MS_C_dec, FER_SP_s, FER_SP_syn_s, FER_SP_dec_s, FER_MS_s, FER_MS_syn_s, FER_MS_dec_s, - FER_MS_C_s, FER_MS_C_syn_s, FER_MS_C_dec_s, subset_dic_SP, subset_dic_SP_syn, subset_dic_SP_dec, subset_dic_MS, subset_dic_MS_syn, subset_dic_MS_dec, subset_dic_MS_C, subset_dic_MS_C_syn, subset_dic_MS_C_dec, subset_dic_SP_s, subset_dic_SP_syn_s, subset_dic_SP_dec_s, subset_dic_MS_s, subset_dic_MS_syn_s, subset_dic_MS_dec_s, subset_dic_MS_C_s, subset_dic_MS_C_syn_s, subset_dic_MS_C_dec_s + return FER_SP, + FER_SP_syn, + FER_SP_dec, + FER_MS, + FER_MS_syn, + FER_MS_dec, + FER_MS_C, + FER_MS_C_syn, + FER_MS_C_dec, + FER_SP_s, + FER_SP_syn_s, + FER_SP_dec_s, + FER_MS_s, + FER_MS_syn_s, + FER_MS_dec_s, + FER_MS_C_s, + FER_MS_C_syn_s, + FER_MS_C_dec_s, + subset_dic_SP, + subset_dic_SP_syn, + subset_dic_SP_dec, + subset_dic_MS, + subset_dic_MS_syn, + subset_dic_MS_dec, + subset_dic_MS_C, + subset_dic_MS_C_syn, + subset_dic_MS_C_dec, + subset_dic_SP_s, + subset_dic_SP_syn_s, + subset_dic_SP_dec_s, + subset_dic_MS_s, + subset_dic_MS_syn_s, + subset_dic_MS_dec_s, + subset_dic_MS_C_s, + subset_dic_MS_C_syn_s, + subset_dic_MS_C_dec_s end function single_decoder_test(H::CTMatrixTypes) @@ -857,24 +1263,295 @@ function single_decoder_test(H::CTMatrixTypes) init_0 = log((1 - p) / p) init_1 = log(p / (1 - p)) local_counts = zeros(Int, num_threads) - Threads.@threads for th in 1:num_threads + Threads.@threads for th = 1:num_threads err = zeros(Int, n) syn_Int = zeros(Int, nr) erasures = Int[] chn_inits = zeros(Float64, n) # SP/MS for BSC - H_Int, _, var_adj_list, check_adj_list, chn_inits, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, v, chn, - max_iter, :SP, chn_inits, schedule, erasures) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init( + H, + v, + chn, + max_iter, + :SP, + chn_inits, + schedule, + erasures, + ) # chn_inits_syn = [init_0 for _ in 1:n] - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread # sample # @inbounds for j in 1:n # rand(dist) ≤ p ? (err[j] = 1; chn_inits[j] = init_1;) : (err[j] = 0; chn_inits[j] = init_0;) # end - err = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] - chn_inits = [init_0 for _ in 1:n] + err = [ + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 1, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + ] + chn_inits = [init_0 for _ = 1:n] chn_inits[81] = init_1 # @inbounds for j in 1:n @@ -891,10 +1568,22 @@ function single_decoder_test(H::CTMatrixTypes) # decimated_values = [err[bit]] # SP - flag, out, _ = _message_passing(H_Int, missing, chn_inits, - _SP_check_node_message_box_plus, var_adj_list, check_adj_list, max_iter, - schedule, current_bits, totals, syn, check_to_var_messages, - var_to_check_messages, 0.0) + flag, out, _ = _message_passing( + H_Int, + missing, + chn_inits, + _SP_check_node_message_box_plus, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + 0.0, + ) (!flag || !iszero(out)) && (local_counts[th] += 1;) println(flag) println(out) diff --git a/src/LDPC/types.jl b/src/LDPC/types.jl index 54718d27..7842889d 100644 --- a/src/LDPC/types.jl +++ b/src/LDPC/types.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # abstract types +# abstract types ############################# abstract type AbstractLDPCCode <: AbstractLinearCode end @@ -17,18 +17,18 @@ abstract type AbstractBinarySymmetricChannel <: AbstractClassicalNoiseChannel en abstract type AbstractBAWGNChannel <: AbstractClassicalNoiseChannel end ############################# - # concrete types +# concrete types ############################# ############################# - # LDPC/codes.jl +# LDPC/codes.jl ############################# mutable struct LDPCCode <: AbstractLDPCCode F::CTFieldTypes # base field n::Int # length k::Int # dimension - d::Union{Int, Missing} # minimum distance + d::Union{Int,Missing} # minimum distance l_bound::Int # lower bound on d u_bound::Int # upper bound on d H::CTMatrixTypes @@ -43,14 +43,14 @@ mutable struct LDPCCode <: AbstractLDPCCode # Tanner_graph::Union{Figure, Missing} λ::QQPolyRingElem ρ::QQPolyRingElem - girth::Union{Int, Missing} + girth::Union{Int,Missing} ACEs_per_var_node::Vector{Vector{Int}} simple_cycles::Vector{Vector{Int}} max_cyc_len::Int end ############################# - # LDPC/channels.jl +# LDPC/channels.jl ############################# struct BinaryErasureChannel <: AbstractBinaryErasureChannel @@ -65,11 +65,11 @@ end mutable struct BAWGNChannel <: AbstractBAWGNChannel param::Float64 - capacity::Union{Float64, Missing} + capacity::Union{Float64,Missing} end ############################# - # LDPC/ensembles.jl +# LDPC/ensembles.jl ############################# mutable struct LDPCEnsemble @@ -80,6 +80,6 @@ mutable struct LDPCEnsemble l_avg::Float64 r_avg::Float64 design_rate::Float64 - density_evo::Dict{AbstractClassicalNoiseChannel, NTuple{2, Vector{Float64}}} - threshold::Dict{Type, Float64} + density_evo::Dict{AbstractClassicalNoiseChannel,NTuple{2,Vector{Float64}}} + threshold::Dict{Type,Float64} end diff --git a/src/Project.toml b/src/Project.toml new file mode 100644 index 00000000..81648c0b --- /dev/null +++ b/src/Project.toml @@ -0,0 +1 @@ +[deps] diff --git a/src/Quantum/GeneralizedToricCode.jl b/src/Quantum/GeneralizedToricCode.jl index 3f1a0fdd..d1ae1663 100644 --- a/src/Quantum/GeneralizedToricCode.jl +++ b/src/Quantum/GeneralizedToricCode.jl @@ -5,27 +5,39 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# function GeneralizedToricCode(f::CTLRPolyElem, g::CTLRPolyElem) LR = parent(f) LR == parent(g) || throw(ArgumentError("The polynomials must be over the same ring.")) - length(symbols(LR)) == 2 || throw(ArgumentError("The polynomials must be over a Laurent polynomial ring in two variables.")) + length(symbols(LR)) == 2 || throw( + ArgumentError( + "The polynomials must be over a Laurent polynomial ring in two variables.", + ), + ) return GeneralizedToricCode(LR, base_ring(LR), f, g) end -function FiniteGeneralizedToricCode(f::CTLRPolyElem, g::CTLRPolyElem, a1::Tuple{Int, Int}, - a2::Tuple{Int, Int}) +function FiniteGeneralizedToricCode( + f::CTLRPolyElem, + g::CTLRPolyElem, + a1::Tuple{Int,Int}, + a2::Tuple{Int,Int}, +) LR = parent(f) LR == parent(g) || throw(ArgumentError("The polynomials must be over the same ring.")) - length(symbols(LR)) == 2 || throw(ArgumentError("The polynomials must be over a Laurent polynomial ring in two variables.")) + length(symbols(LR)) == 2 || throw( + ArgumentError( + "The polynomials must be over a Laurent polynomial ring in two variables.", + ), + ) return FiniteGeneralizedToricCode(LR, base_ring(LR), f, g, a1, a2) end ############################# - # getter functions +# getter functions ############################# Laurent_polynomial_ring(S::AbstractGeneralizedToricCode) = S.LR @@ -37,11 +49,11 @@ defining_polynomials(S::AbstractGeneralizedToricCode) = S.f, S.g twist_vectors(S::FiniteGeneralizedToricCode) = S.a1, S.a2 ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# function maximum_dimension(S::AbstractGeneralizedToricCode) @@ -76,8 +88,8 @@ function CSSCode(S::FiniteGeneralizedToricCode) mono = monomial_basis(Q) len_mon = length(mono) n = 2 * len_mon - LR_edge_index = Dict{fpMPolyRingElem, Int}(mono[i] => i for i in 1:len_mon) - TB_edge_index = Dict{fpMPolyRingElem, Int}(mono[i] => i + len_mon for i in 1:len_mon) + LR_edge_index = Dict{fpMPolyRingElem,Int}(mono[i] => i for i = 1:len_mon) + TB_edge_index = Dict{fpMPolyRingElem,Int}(mono[i] => i + len_mon for i = 1:len_mon) Fone = S.F(1) row = 1 diff --git a/src/Quantum/decoders/OTF.jl b/src/Quantum/decoders/OTF.jl index 3a06aaf5..b335473c 100644 --- a/src/Quantum/decoders/OTF.jl +++ b/src/Quantum/decoders/OTF.jl @@ -4,26 +4,40 @@ # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. -function ordered_Tanner_forest(H::T, v::T, chn::AbstractClassicalNoiseChannel; BP_alg::Symbol = :SP, - max_iter::Int = 100, chn_inits::Union{Missing, Vector{Float64}} = missing, schedule::Symbol = - :parallel, rand_sched::Bool = false, erasures::Vector{Int} = Int[]) where T <: CTMatrixTypes +function ordered_Tanner_forest( + H::T, + v::T, + chn::AbstractClassicalNoiseChannel; + BP_alg::Symbol = :SP, + max_iter::Int = 100, + chn_inits::Union{Missing,Vector{Float64}} = missing, + schedule::Symbol = :parallel, + rand_sched::Bool = false, + erasures::Vector{Int} = Int[], +) where {T<:CTMatrixTypes} # TODO add MS_C # TODO decimation BP_alg ∈ (:SP, :MS) || throw(ArgumentError("`BP_alg` should be `:SP` or `:MS`")) - Int(order(base_ring(H))) == 2 || throw(ArgumentError("Currently only implemented for binary codes")) + Int(order(base_ring(H))) == 2 || + throw(ArgumentError("Currently only implemented for binary codes")) nr, nc = size(H) (nr ≥ 0 && nc ≥ 0) || throw(ArgumentError("H cannot have a zero dimension")) 2 <= max_iter || throw(DomainError("Number of maximum iterations must be at least two")) - schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || + schedule ∈ (:flooding, :parallel, :serial, :layered, :semiserial) || throw(ArgumentError("Unknown schedule algorithm")) schedule == :flooding && (schedule = :parallel;) schedule == :semiserial && (schedule = :layered;) # TODO search for wt 1 columns and add new row - H_Int, v_Int, syndrome_based, check_adj_list, check_to_var_messages, var_to_check_messages, - current_bits, syn = _message_passing_init_fast(H, v, chn, BP_alg, chn_inits, :serial, - erasures) + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn = _message_passing_init_fast(H, v, chn, BP_alg, chn_inits, :serial, erasures) if BP_alg == :SP # H_Int, v_Int, syndrome_based, check_adj_list, check_to_var_messages, var_to_check_messages, @@ -32,30 +46,71 @@ function ordered_Tanner_forest(H::T, v::T, chn::AbstractClassicalNoiseChannel; B if schedule == :layered layers = layered_schedule(H, schedule = schedule, random = rand_sched) - flag, e, _, posteriors = _message_passing_fast_layered(H_Int, v_Int, syndrome_based, - check_adj_list, check_to_var_messages, var_to_check_messages, current_bits, syn, - ϕ_test, ϕ_test, max_iter, layers) + flag, e, _, posteriors = _message_passing_fast_layered( + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn, + ϕ_test, + ϕ_test, + max_iter, + layers, + ) else - flag, e, _, posteriors = _message_passing_fast(H_Int, v_Int, syndrome_based, - check_adj_list, check_to_var_messages, var_to_check_messages, current_bits, syn, - ϕ_test, ϕ_test, max_iter) + flag, e, _, posteriors = _message_passing_fast( + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn, + ϕ_test, + ϕ_test, + max_iter, + ) end elseif BP_alg == :MS - H_Int, _, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, v, chn, - :MS, chn_inits, schedule, erasures) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init(H, v, chn, :MS, chn_inits, schedule, erasures) layers = layered_schedule(H, schedule = schedule, random = rand_sched) - flag, e, _, posteriors = _message_passing_layered(H_Int, missing, chn_inits_2, - _MS_check_node_message, var_adj_list, check_adj_list, max_iter, schedule, - current_bits, totals, syn, check_to_var_messages, var_to_check_messages, - attenuation, layers) + flag, e, _, posteriors = _message_passing_layered( + H_Int, + missing, + chn_inits_2, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + attenuation, + layers, + ) end if !flag # initial BP did not converge - var_adj_list = [Int[] for _ in 1:size(H_Int, 2)]; - for r in 1:size(H_Int, 1) - for c in 1:size(H_Int, 2) + var_adj_list = [Int[] for _ = 1:size(H_Int, 2)]; + for r = 1:size(H_Int, 1) + for c = 1:size(H_Int, 2) if !iszero(H_Int[r, c]) push!(var_adj_list[c], r) end @@ -69,13 +124,15 @@ function ordered_Tanner_forest(H::T, v::T, chn::AbstractClassicalNoiseChannel; B # since negative implies an error is more likely here, the selection process will allow BP to run on columns which are still positive while fixing columns which are more likely to have an error to have an error # this is similar to selecting a test pattern in OSD ordered_indices = sortperm(posteriors, rev = true) - erased_columns = _select_erased_columns(H_Int, ordered_indices, var_adj_list) + erased_columns = + _select_erased_columns(H_Int, ordered_indices, var_adj_list) for i in erased_columns posteriors[i] = -20.0 end else ordered_indices = sortperm(posteriors, by = abs) - erased_columns = _select_erased_columns(H_Int, ordered_indices, var_adj_list) + erased_columns = + _select_erased_columns(H_Int, ordered_indices, var_adj_list) for i in erased_columns if posteriors[i] < 0 posteriors[i] = -20.0 @@ -100,43 +157,95 @@ function ordered_Tanner_forest(H::T, v::T, chn::AbstractClassicalNoiseChannel; B println(posteriors) if BP_alg == :SP - H_Int, v_Int, syndrome_based, check_adj_list, check_to_var_messages, var_to_check_messages, - current_bits, syn = _message_passing_init_fast(H, v, chn, BP_alg, chn_inits, :serial, - erasures) - + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn = + _message_passing_init_fast(H, v, chn, BP_alg, chn_inits, :serial, erasures) + if schedule == :layered layers = layered_schedule(H, schedule = schedule, random = rand_sched) - flag, e, _, posteriors = _message_passing_fast_layered(H_Int, v_Int, syndrome_based, - check_adj_list, check_to_var_messages, var_to_check_messages, current_bits, syn, - ϕ_test, ϕ_test, max_iter, layers) + flag, e, _, posteriors = _message_passing_fast_layered( + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn, + ϕ_test, + ϕ_test, + max_iter, + layers, + ) else - flag, e, _, posteriors = _message_passing_fast(H_Int, v_Int, syndrome_based, - check_adj_list, check_to_var_messages, var_to_check_messages, current_bits, syn, - ϕ_test, ϕ_test, max_iter) + flag, e, _, posteriors = _message_passing_fast( + H_Int, + v_Int, + syndrome_based, + check_adj_list, + check_to_var_messages, + var_to_check_messages, + current_bits, + syn, + ϕ_test, + ϕ_test, + max_iter, + ) end elseif BP_alg == :MS - H_Int, _, var_adj_list, check_adj_list, chn_inits_2, check_to_var_messages, - var_to_check_messages, current_bits, totals, syn = _message_passing_init(H, v, chn, - :MS, chn_inits, schedule, erasures) + H_Int, + _, + var_adj_list, + check_adj_list, + chn_inits_2, + check_to_var_messages, + var_to_check_messages, + current_bits, + totals, + syn = _message_passing_init(H, v, chn, :MS, chn_inits, schedule, erasures) layers = layered_schedule(H, schedule = schedule, random = rand_sched) - flag, e, _, posteriors = _message_passing_layered(H_Int, missing, chn_inits_2, - _MS_check_node_message, var_adj_list, check_adj_list, max_iter, schedule, - current_bits, totals, syn, check_to_var_messages, var_to_check_messages, - attenuation, layers) + flag, e, _, posteriors = _message_passing_layered( + H_Int, + missing, + chn_inits_2, + _MS_check_node_message, + var_adj_list, + check_adj_list, + max_iter, + schedule, + current_bits, + totals, + syn, + check_to_var_messages, + var_to_check_messages, + attenuation, + layers, + ) end end return flag, e end -function _select_erased_columns(H::Matrix{UInt8}, ordered_indices::Vector{Int}, var_adj_list::Vector{Vector{Int}}) +function _select_erased_columns( + H::Matrix{UInt8}, + ordered_indices::Vector{Int}, + var_adj_list::Vector{Vector{Int}}, +) # this is using the disjoint-set data structure/union find algorithm for merging them nr = size(H, 1) parents = collect(1:nr) depths = ones(Int, nr) output_indices = Vector{Int}() - seen_roots_list = [[-1 for _ in 1:length(var_adj_list[c])] for c in 1:length(var_adj_list)] + seen_roots_list = + [[-1 for _ = 1:length(var_adj_list[c])] for c = 1:length(var_adj_list)] flag = false for col in ordered_indices # count = 0 @@ -149,7 +258,7 @@ function _select_erased_columns(H::Matrix{UInt8}, ordered_indices::Vector{Int}, break end end - + if !flag # Find maximum of depths[see_roots_list[col][count]], also, see if there are two or more roots of maximum depth. In which case we should grow. merged_root = -1 @@ -158,7 +267,7 @@ function _select_erased_columns(H::Matrix{UInt8}, ordered_indices::Vector{Int}, for row_root in seen_roots_list[col] if depths[row_root] > merged_depth merged_root = row_root - merged_depth = depths[row_root] + merged_depth = depths[row_root] growth = false elseif depths[row_root] == merged_depth growth = true @@ -177,7 +286,7 @@ function _select_erased_columns(H::Matrix{UInt8}, ordered_indices::Vector{Int}, # println(parents) # println(depths) end - + return output_indices end @@ -270,4 +379,3 @@ end # we are unable to assign an interpretation to 0's and 1's in the received vector # we could do standard reliability decoding where we take a parameter and look for test patterns inside the k least-reliable bits # or we could proceed as above with the BP picture - diff --git a/src/Quantum/graph_state.jl b/src/Quantum/graph_state.jl index c4335221..2aa50efd 100644 --- a/src/Quantum/graph_state.jl +++ b/src/Quantum/graph_state.jl @@ -13,17 +13,17 @@ function GraphState(G::SimpleGraph{Int}) # probably need some checks on G here but maybe the function args are good enough A = adjacency_matrix(G) _, nc = size(A) - for i in 1:nc + for i = 1:nc iszero(A[i, i]) || throw(ArgumentError("Graph cannot have self-loops.")) end # are there non-binary graph states? F = Oscar.Nemo.Native.GF(2) Fone = F(1) sym_stabs = zero_matrix(F, nc, 2 * nc) - for r in 1:nc + for r = 1:nc sym_stabs[r, r] = Fone - for c in 1:nc - isone(A[r, c]) && (sym_stabs[r, c + nc] = Fone;) + for c = 1:nc + isone(A[r, c]) && (sym_stabs[r, c+nc] = Fone;) end end # this should automatically compute everything for the GraphState constructor @@ -44,13 +44,13 @@ function ClusterState(w::Int, h::Int) Eone = E(1) A = zero_matrix(E, w * h, w * h) curr = 1 - for r in 1:h - for c in 1:w + for r = 1:h + for c = 1:w A[curr, curr] = Eone - c != 1 && (A[curr, curr - 1] = ω;) - c != w && (A[curr, curr + 1] = ω;) - r != 1 && (A[curr, curr - w] = ω;) - r != h && (A[curr, curr + w] = ω;) + c != 1 && (A[curr, curr-1] = ω;) + c != w && (A[curr, curr+1] = ω;) + r != 1 && (A[curr, curr-w] = ω;) + r != h && (A[curr, curr+w] = ω;) curr += 1 end end diff --git a/src/Quantum/homological_measurements.jl b/src/Quantum/homological_measurements.jl index f947ad9e..8c940433 100755 --- a/src/Quantum/homological_measurements.jl +++ b/src/Quantum/homological_measurements.jl @@ -5,13 +5,20 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# # TODO Check logicals are being used correctly throughout -function _thickened_cone(S::AbstractStabilizerCodeCSS, HX_A::CTMatrixTypes, HZ_A::CTMatrixTypes, - f1::CTMatrixTypes, f0::CTMatrixTypes, type::Symbol, r::Int = 1) +function _thickened_cone( + S::AbstractStabilizerCodeCSS, + HX_A::CTMatrixTypes, + HZ_A::CTMatrixTypes, + f1::CTMatrixTypes, + f0::CTMatrixTypes, + type::Symbol, + r::Int = 1, +) r > 0 || (r == 0 && (return S;)) || throw(DomainError(r, "Must be a positive integer.")) type in (:X, :Z) || throw(DomainError(type, "Must choose `type` to be `:X` or `:Z`.")) @@ -30,13 +37,27 @@ function _thickened_cone(S::AbstractStabilizerCodeCSS, HX_A::CTMatrixTypes, HZ_A @assert HZ_C * f1 == f0 * transpose(HX_A) # build stabilizers - HX = vcat(hcat(HX_C, zero_matrix(F, size(HX_C, 1), n - nC)), - hcat(vcat(transpose(f1), zero_matrix(F, (r - 1) * size(HX_A, 1), nC)), - identity_matrix(F, r) ⊗ HX_A, _rep_pcm_tr(F, r) ⊗ identity_matrix(F, size(HX_A, 1)))) - HZ = vcat(hcat(HZ_C, f0, zero_matrix(F, size(HZ_C, 1), (r - 1) * (nA + size(HX_A, 1)))), - hcat(zero_matrix(F, (r - 1) * nA, nC), _rep_pcm(F, r) ⊗ identity_matrix(F, nA), - identity_matrix(F, r - 1) ⊗ transpose(HX_A)), hcat(zero_matrix(F, size(HZ_A, 1), nC + - (r - 1) * nA), HZ_A, zero_matrix(F, size(HZ_A, 1), (r - 1) * size(HX_A, 1)))) + HX = vcat( + hcat(HX_C, zero_matrix(F, size(HX_C, 1), n - nC)), + hcat( + vcat(transpose(f1), zero_matrix(F, (r - 1) * size(HX_A, 1), nC)), + identity_matrix(F, r) ⊗ HX_A, + _rep_pcm_tr(F, r) ⊗ identity_matrix(F, size(HX_A, 1)), + ), + ) + HZ = vcat( + hcat(HZ_C, f0, zero_matrix(F, size(HZ_C, 1), (r - 1) * (nA + size(HX_A, 1)))), + hcat( + zero_matrix(F, (r - 1) * nA, nC), + _rep_pcm(F, r) ⊗ identity_matrix(F, nA), + identity_matrix(F, r - 1) ⊗ transpose(HX_A), + ), + hcat( + zero_matrix(F, size(HZ_A, 1), nC + (r - 1) * nA), + HZ_A, + zero_matrix(F, size(HZ_A, 1), (r - 1) * size(HX_A, 1)), + ), + ) stabs = type == :X ? direct_sum(HX, HZ) : direct_sum(HZ, HX) # build X logicals @@ -67,30 +88,43 @@ function _thickened_cone(S::AbstractStabilizerCodeCSS, HX_A::CTMatrixTypes, HZ_A temp = CSSCode(HX_A, vcat(HZ_A, implied_stabs)) if dimension(temp) > 0 # TODO can preallocate as above - _remove_empty(logicals_matrix(temp)[:, 1 + nA:2nA], :rows) + _remove_empty(logicals_matrix(temp)[:, (1+nA):2nA], :rows) else zero_matrix(F, 0, nA) end end # Z_gauges = hcat(zero_matrix(F, size(Z_gauges, 1), nC), Z_gauges) - Z_gauges = hcat(zero_matrix(F, size(Z_gauges, 1), nC + (r - 1) * nA), Z_gauges, - zero_matrix(F, size(Z_gauges, 1), (r - 1) * size(HX_A, 1))) + Z_gauges = hcat( + zero_matrix(F, size(Z_gauges, 1), nC + (r - 1) * nA), + Z_gauges, + zero_matrix(F, size(Z_gauges, 1), (r - 1) * size(HX_A, 1)), + ) # build full logs and gauges - new_X, new_Z, new_mixed, _ = _complete_pairs(stabs, type == :X ? direct_sum(X_logs, Z_gauges) : - direct_sum(Z_gauges, X_logs)) + new_X, new_Z, new_mixed, _ = _complete_pairs( + stabs, + type == :X ? direct_sum(X_logs, Z_gauges) : direct_sum(Z_gauges, X_logs), + ) isempty(new_mixed) || error() # TODO - logs = type == :X ? direct_sum(X_logs, new_Z[:, n + 1:2n]) : direct_sum(new_X[:, 1:n], X_logs) - gauges = type == :X ? direct_sum(new_X[:, 1:n], Z_gauges) : direct_sum(Z_gauges, new_Z[:, n + - 1:2n]) + logs = + type == :X ? direct_sum(X_logs, new_Z[:, (n+1):2n]) : + direct_sum(new_X[:, 1:n], X_logs) + gauges = + type == :X ? direct_sum(new_X[:, 1:n], Z_gauges) : + direct_sum(Z_gauges, new_Z[:, (n+1):2n]) # TODO why are logs not also passed in here? # TODO can we remove the type instability here? return isempty(gauges) ? StabilizerCode(stabs) : SubsystemCode(stabs, logs, gauges) end -_thickened_cone(S::AbstractStabilizerCodeCSS, A::AbstractStabilizerCodeCSS, f1::CTMatrixTypes, - f0::CTMatrixTypes, type::Symbol, r::Int = 1) = _thickened_cone(S, A.X_stabs, A.Z_stabs, f1, f0, - type, r) +_thickened_cone( + S::AbstractStabilizerCodeCSS, + A::AbstractStabilizerCodeCSS, + f1::CTMatrixTypes, + f0::CTMatrixTypes, + type::Symbol, + r::Int = 1, +) = _thickened_cone(S, A.X_stabs, A.Z_stabs, f1, f0, type, r) """ $TYPEDSIGNATURES @@ -106,31 +140,39 @@ All paramaters are aligned with their respective papers. - `improve_cycles` - used for `IBM` - `remove_and_improve_cycles` - used for `IBM`, supersedes previous parameter """ -function homological_measurement(S::AbstractStabilizerCodeCSS, L::CTMatrixTypes; style::Symbol = - :Xanadu, r::Int = 1, max_iters::Int = 50000, cellulate::Bool = false, improve_cycles::Bool = - true, remove_and_improve_cycles::Bool = false) +function homological_measurement( + S::AbstractStabilizerCodeCSS, + L::CTMatrixTypes; + style::Symbol = :Xanadu, + r::Int = 1, + max_iters::Int = 50000, + cellulate::Bool = false, + improve_cycles::Bool = true, + remove_and_improve_cycles::Bool = false, +) is_positive(r) || throw(DomainError(r, "Must be a positive integer.")) is_positive(max_iters) || throw(DomainError(max_iters, "Must be a positive integer.")) L_red = _remove_empty(L, :rows) nrows(L_red) == 1 || throw(ArgumentError("Requires a single logical of the code.")) - is_logical(S, L_red) || throw(ArgumentError("The input matrix is not a logical of the code.")) + is_logical(S, L_red) || + throw(ArgumentError("The input matrix is not a logical of the code.")) F = field(S) Int(order(F)) == 2 || throw(ArgumentError("Only defined for binary codes.")) n = length(S) # k = dimension(S) - type, stabs, log = if iszero(L_red[1:1, 1 + n:2n]) + type, stabs, log = if iszero(L_red[1:1, (1+n):2n]) :X, Z_stabilizers(S), L_red[1:1, 1:n] elseif iszero(L_red[1:1, 1:n]) - :Z, X_stabilizers(S), L_red[1:1, 1 + n:2n] + :Z, X_stabilizers(S), L_red[1:1, (1+n):2n] else throw(DomainError(L, "Only defined for pure X or Z logicals `L`.")) end Q = getindex.(findall(!iszero, log), 2) - f1 = matrix(F, Int[Q[j] == i for i in 1:n, j in 1:length(Q)]) - nonzero = findall(!iszero(stabs[i, Q]) for i in 1:size(stabs, 1)) + f1 = matrix(F, Int[Q[j] == i for i = 1:n, j = 1:length(Q)]) + nonzero = findall(!iszero(stabs[i, Q]) for i = 1:size(stabs, 1)) f0 = identity_matrix(F, size(stabs, 1))[:, nonzero] HX = transpose(stabs[nonzero, Q]) @@ -183,13 +225,13 @@ function homological_measurement(S::AbstractStabilizerCodeCSS, L::CTMatrixTypes; end ############################# - # general functions +# general functions ############################# -_rep_pcm_tr(F::CTFieldTypes, d::Int) = matrix(F, diagm(d, d - 1, 0 => ones(Int, d - 1), -1 => - ones(Int, d - 1))) -_rep_pcm(F::CTFieldTypes, d::Int) = matrix(F, diagm(d - 1, d, 0 => ones(Int, d - 1), 1 => ones(Int, - d - 1))) +_rep_pcm_tr(F::CTFieldTypes, d::Int) = + matrix(F, diagm(d, d - 1, 0 => ones(Int, d - 1), -1 => ones(Int, d - 1))) +_rep_pcm(F::CTFieldTypes, d::Int) = + matrix(F, diagm(d - 1, d, 0 => ones(Int, d - 1), 1 => ones(Int, d - 1))) function _complete_pairs(stabs::CTMatrixTypes, logs::CTMatrixTypes) # we can remove some of these assertions since it's a private function and we control the input @@ -199,12 +241,14 @@ function _complete_pairs(stabs::CTMatrixTypes, logs::CTMatrixTypes) @assert size(stabs, 2) == size(logs, 2) @assert rank(logs) == size(logs, 1) n = div(size(stabs, 2), 2) - Ω = vcat(hcat(zero_matrix(F, n, n), identity_matrix(F, n)), hcat(identity_matrix(F, n), - zero_matrix(F, n, n))) + Ω = vcat( + hcat(zero_matrix(F, n, n), identity_matrix(F, n)), + hcat(identity_matrix(F, n), zero_matrix(F, n, n)), + ) # @assert iszero(vcat(stabs, logs) * Ω * transpose(stabs)) find_pairs = logs * Ω * transpose(logs) - @assert all(count(!iszero, find_pairs[i:i, :]) in (0, 1) for i in 1:size(find_pairs, 1)) - needs_pair = findall(iszero(find_pairs[i:i, :]) for i in 1:size(find_pairs, 1)) + @assert all(count(!iszero, find_pairs[i:i, :]) in (0, 1) for i = 1:size(find_pairs, 1)) + needs_pair = findall(iszero(find_pairs[i:i, :]) for i = 1:size(find_pairs, 1)) new_X = zero_matrix(F, 0, 2n) new_Z = zero_matrix(F, 0, 2n) @@ -216,7 +260,7 @@ function _complete_pairs(stabs::CTMatrixTypes, logs::CTMatrixTypes) # try pure X # TODO don't understand this line - LHS = vcat(logs, stabs, Ω[n + 1:2n, :]) + LHS = vcat(logs, stabs, Ω[(n+1):2n, :]) flag, sol = can_solve_with_solution(LHS * Ω, RHS, side = :right) if flag logs = vcat(logs, transpose(sol)) @@ -225,7 +269,7 @@ function _complete_pairs(stabs::CTMatrixTypes, logs::CTMatrixTypes) end # try pure Z - LHS[size(logs, 1) + size(stabs, 1) + 1:end, :] = Ω[1:n, :] + LHS[(size(logs, 1)+size(stabs, 1)+1):end, :] = Ω[1:n, :] flag, sol = can_solve_with_solution(LHS * Ω, RHS, side = :right) if flag logs = vcat(logs, transpose(sol)) @@ -234,7 +278,7 @@ function _complete_pairs(stabs::CTMatrixTypes, logs::CTMatrixTypes) end # try mixed - LHS[size(logs, 1) + size(stabs, 1) + 1:end, :] = zero_matrix(F, n, 2n) + LHS[(size(logs, 1)+size(stabs, 1)+1):end, :] = zero_matrix(F, n, 2n) flag, sol = can_solve_with_solution(LHS * Ω, RHS) if flag logs = vcat(logs, transpose(sol)) @@ -251,7 +295,7 @@ $TYPEDSIGNATURES Return the Cheeger constant of the matrix `M` assuming `M` is a vertex-edge incidence matrix. """ -function Cheeger_constant(M::Matrix{T}) where T <: Integer +function Cheeger_constant(M::Matrix{T}) where {T<:Integer} m, n = size(M) # get one more bit in using an unsigned integer... U = UInt64 @@ -260,11 +304,11 @@ function Cheeger_constant(M::Matrix{T}) where T <: Integer end r = div(m, 2) h = Inf - for x in U(1):U(2)^U(m - 1) + for x = U(1):(U(2)^U(m-1)) v = digits(T, x, base = 2, pad = m) s = sum(v) s > r && continue - h = min(h, count(isodd, dot(v, M[:, c]) for c in 1:n) / s) + h = min(h, count(isodd, dot(v, M[:, c]) for c = 1:n) / s) end return h end @@ -281,23 +325,24 @@ function Cheeger_constant(S::AbstractSubsystemCode, L::CTMatrixTypes) L_red = _remove_empty(L, :rows) nrows(L_red) == 1 || throw(ArgumentError("Requires a single logical of the code.")) - is_logical(S, L_red) || throw(ArgumentError("The input matrix is not a logical of the code.")) + is_logical(S, L_red) || + throw(ArgumentError("The input matrix is not a logical of the code.")) n = length(S) - stabs, log = if iszero(L_red[1:1, 1 + n:2n]) + stabs, log = if iszero(L_red[1:1, (1+n):2n]) Z_stabilizers(S), L_red[1:1, 1:n] elseif iszero(L_red[1:1, 1:n]) - X_stabilizers(S), L_red[1:1, 1 + n:2n] + X_stabilizers(S), L_red[1:1, (1+n):2n] else throw(DomainError(L_red, "Only defined for pure `X` or `Z` logicals `L`.")) end Q = getindex.(findall(!iszero, log), 2) - nonzero = findall(!iszero(stabs[i:i, Q]) for i in 1:size(stabs, 1)) + nonzero = findall(!iszero(stabs[i:i, Q]) for i = 1:size(stabs, 1)) graph = transpose(stabs[nonzero, Q]) return Cheeger_constant(_Flint_matrix_to_Julia_int_matrix(graph)) end -function _sparsest_cut(M::Matrix{T}; rng = Xoshiro()) where T <: Integer +function _sparsest_cut(M::Matrix{T}; rng = Xoshiro()) where {T<:Integer} m, n = size(M) r = div(m, 2) h = Inf @@ -309,12 +354,12 @@ function _sparsest_cut(M::Matrix{T}; rng = Xoshiro()) where T <: Integer end # the shuffle allows different choices of the sparsest cuts to be chosen - for x in shuffle(rng, U(1):U(2)^U(m - 1)) + for x in shuffle(rng, U(1):(U(2)^U(m-1))) # v corresponds to a subset of the vertices v = digits(T, x, base = 2, pad = m) s = sum(v) s > r && continue - temp = count(isodd, dot(v, M[:, c]) for c in 1:n) / s + temp = count(isodd, dot(v, M[:, c]) for c = 1:n) / s if temp < h h = temp sparse_cut .= v @@ -324,7 +369,7 @@ function _sparsest_cut(M::Matrix{T}; rng = Xoshiro()) where T <: Integer return h, sparse_cut end -function _add_edges(M::Matrix{T}; rng = Xoshiro()) where T <: Integer +function _add_edges(M::Matrix{T}; rng = Xoshiro()) where {T<:Integer} M_new = copy(M) while true @@ -369,8 +414,12 @@ function _add_edges(M::Matrix{T}; rng = Xoshiro()) where T <: Integer return M_new end -function _find_low_weight_cycle_subspace(all_cycles::CTMatrixTypes, - already_covered_cycles::CTMatrixTypes, max_iters::Int, f::T = maximum) where T <: Function +function _find_low_weight_cycle_subspace( + all_cycles::CTMatrixTypes, + already_covered_cycles::CTMatrixTypes, + max_iters::Int, + f::T = maximum, +) where {T<:Function} @assert size(all_cycles, 2) == size(already_covered_cycles, 2) F = base_ring(all_cycles) @@ -392,7 +441,7 @@ function _find_low_weight_cycle_subspace(all_cycles::CTMatrixTypes, w = size(A, 2) + 1 C = zero_matrix(F, size(B, 1), size(B, 2)) - for i in 1:max_iters + for i = 1:max_iters x = _random_invertible_matrix(F, size(B, 1)) y = matrix(F, rand(F, size(B, 1), size(A, 1))) temp = x * B + y * A @@ -411,15 +460,18 @@ function _find_low_weight_cycle_subspace(all_cycles::CTMatrixTypes, return C end -function _find_low_weights_rand(M::CTMatrixTypes, max_iters::Int, f::T = maximum) where - T <: Function +function _find_low_weights_rand( + M::CTMatrixTypes, + max_iters::Int, + f::T = maximum, +) where {T<:Function} initial_w = f(count(!iszero(M[i, j]) for j in size(M, 2)) for i in size(M, 1)) A = _remove_empty(rref(M)[2], :rows) isempty(A) && (return A;) F = base_ring(A) w = size(A, 2) + 1 - for i in 1:max_iters + for i = 1:max_iters x = _random_invertible_matrix(F, size(A, 1)) temp = x * A temp_w = f(count(!iszero(temp[i, j]) for j in size(temp, 2)) for i in size(temp, 1)) @@ -436,14 +488,14 @@ function _random_invertible_matrix(n::Int) inds = collect(1:n) A = zeros(UInt8, n, n) T = zeros(UInt8, n, n) - for k in 1:n + for k = 1:n v = rand(0x00:0x01, n - k + 1) while iszero(v) v .= rand(0x00:0x01, n - k + 1) end r = findfirst(!iszero, v) A[k, inds[r]] = 0x01 - A[k + 1:end, inds[r]] .= rand(0x00:0x01, n - k) + A[(k+1):end, inds[r]] .= rand(0x00:0x01, n - k) T[inds[r], inds] .= v deleteat!(inds, r) end @@ -456,14 +508,14 @@ function _random_invertible_matrix(F::CTFieldTypes, n::Int) A = zero_matrix(F, n, n) T = zero_matrix(F, n, n) Fone = F(1) - for k in 1:n + for k = 1:n v = matrix(F, rand(F, 1, n - k + 1)) while iszero(v) v = matrix(F, rand(F, 1, n - k + 1)) end r = findfirst(!iszero, v)[2] A[k, inds[r]] = Fone - for i in k + 1:n + for i = (k+1):n A[i, inds[r]] = rand(F) end for i in eachindex(inds) diff --git a/src/Quantum/misc_known_codes.jl b/src/Quantum/misc_known_codes.jl index e2127a21..36f90595 100644 --- a/src/Quantum/misc_known_codes.jl +++ b/src/Quantum/misc_known_codes.jl @@ -5,15 +5,40 @@ # LICENSE file in the root directory of this source tree. ############################# - # Subsystem codes +# Subsystem codes ############################# +""" + GaugedShorCode + +Constructs the `[[9,1,4,3]]` subsystem code, an optimized version of +Shor's 9-qubit code that reduces stabilizer measurements through gauge symmetry. + +```jldoctest +julia> using CodingTheory + +julia> c = GaugedShorCode(); + +julia> c.n, c.k, c.r, c.d_dressed +(9, 1, 4, 3) +``` + +See: [`Poulin_2005`](@cite) +""" function GaugedShorCode() - # Poulin, "Stabilizer Formalism for Operator Quantum Error Correction", (2008) # [[9, 1, 4, 3]] gauged Shor code - S = ["XXXXXXIII", "XXXIIIXXX", "ZZIZZIZZI","IZZIZZIZZ"] + S = ["XXXXXXIII", "XXXIIIXXX", "ZZIZZIZZI", "IZZIZZIZZ"] # these are the {X, Z} pairings - Gops = ["IZZIIIIII", "IIXIIIIIX", "IIIIZZIII", "IIIIIXIIX", "ZZIIIIIII", "XIIIIIXII", "IIIZZIIII", "IIIXIIXII"] + Gops = [ + "IZZIIIIII", + "IIXIIIIIX", + "IIIIZZIII", + "IIIIIXIIX", + "ZZIIIIIII", + "XIIIIIXII", + "IIIZZIIII", + "IIIXIIXII", + ] # G = S ∪ Gops L = ["ZZZZZZZZZ", "XXXXXXXXX"] Q = SubsystemCode(S, L, Gops) @@ -27,6 +52,18 @@ Q9143() = GaugedShorCode() BaconShorCode(m::Int, n::Int) Return the Bacon-Shor subsystem code on a `m x n` lattice. + +# Example + +```jldoctest +julia> using CodingTheory: BaconShorCode + +julia> c = BaconShorCode(4,4); + +julia> c.n, c.k, c.r, c.d_dressed +(16, 1, 9, 4) + +``` """ function BaconShorCode(m::Int, n::Int) F = Oscar.Nemo.Native.GF(2) @@ -39,12 +76,12 @@ function BaconShorCode(m::Int, n::Int) X_gauges = zero_matrix(F, (m - 1) * n, num_qubits) curr_row = 1 curr_row_G = 1 - for r in 1:m - 1 - for c in 1:n - X_stabs[curr_row, (r - 1) * m + c] = F_one - X_stabs[curr_row, r * m + c] = F_one - X_gauges[curr_row_G, (r - 1) * m + c] = F_one - X_gauges[curr_row_G, r * m + c] = F_one + for r = 1:(m-1) + for c = 1:n + X_stabs[curr_row, (r-1)*m+c] = F_one + X_stabs[curr_row, r*m+c] = F_one + X_gauges[curr_row_G, (r-1)*m+c] = F_one + X_gauges[curr_row_G, r*m+c] = F_one curr_row_G += 1 end curr_row += 1 @@ -56,12 +93,12 @@ function BaconShorCode(m::Int, n::Int) Z_gauges = zero_matrix(F, (n - 1) * m, num_qubits) curr_row = 1 curr_row_G = 1 - for c in 1:n - 1 - for r in 1:m - Z_stabs[curr_row, (r - 1) * m + c] = F_one - Z_stabs[curr_row, (r - 1) * m + c + 1] = F_one - Z_gauges[curr_row_G, (r - 1) * m + c] = F_one - Z_gauges[curr_row_G, (r - 1) * m + c + 1] = F_one + for c = 1:(n-1) + for r = 1:m + Z_stabs[curr_row, (r-1)*m+c] = F_one + Z_stabs[curr_row, (r-1)*m+c+1] = F_one + Z_gauges[curr_row_G, (r-1)*m+c] = F_one + Z_gauges[curr_row_G, (r-1)*m+c+1] = F_one curr_row_G += 1 end curr_row += 1 @@ -70,17 +107,17 @@ function BaconShorCode(m::Int, n::Int) # X logical: X[1, :] = 1 X_logical = zero_matrix(F, 1, num_qubits) # TODO: consider @simd or @unroll here - for c in 1:n + for c = 1:n X_logical[1, c] = F_one end # Z logical: Z[:, 1] = 1 Z_logical = zero_matrix(F, 1, num_qubits) # TODO: consider @simd or @unroll here - for r in 1:m - Z_logical[1, (r - 1) * m + 1] = F_one + for r = 1:m + Z_logical[1, (r-1)*m+1] = F_one end - + stabs = X_stabs ⊕ Z_stabs logs = X_logical ⊕ Z_logical gauges = X_gauges ⊕ Z_gauges @@ -108,21 +145,40 @@ BaconShorCode(d::Int) = BaconShorCode(d, d) BravyiBaconShorCode(A::fqPolyRepMatrix) GeneralizedBaconShorCode(A::fqPolyRepMatrix) -Return the generalied Bacon-Shor code defined by Bravyi in "Subsystem Codes With Spatially Local -Generators", (2011). +Return the generalied Bacon-Shor code defined by Bravyi in [`Bravyi_2011`](@cite). + +# Example + +```jldoctest +julia> using CodingTheory: BravyiBaconShorCode + +julia> using Nemo; + +julia> F = Nemo.fpField(UInt(2)); + +julia> A = Nemo.matrix(F, [1 1 0; + 0 1 1; + 1 0 1]); + +julia> c = BravyiBaconShorCode(A); + +julia> c.n, c.k, c.r, c.d_dressed +(6, 2, 2, 2) +``` """ function BravyiBaconShorCode(A::CTMatrixTypes) iszero(A) && throw(ArgumentError("The input matrix cannot be zero.")) F = base_ring(A) - Int(order(F)) == 2 || throw(ArgumentError("Construction is only valid for binary martices.")) + Int(order(F)) == 2 || + throw(ArgumentError("Construction is only valid for binary martices.")) n = 0 nr, nc = size(A) row_wts = zeros(Int, 1, nr) col_wts = zeros(Int, 1, nc) - linear_index = Dict{Tuple{Int, Int}, Int}() - for r in 1:nr - for c in 1:nc + linear_index = Dict{Tuple{Int,Int},Int}() + for r = 1:nr + for c = 1:nc if !iszero(A[r, c]) n += 1 row_wts[r] += 1 @@ -132,25 +188,27 @@ function BravyiBaconShorCode(A::CTMatrixTypes) end end - for i in 1:nr - row_wts[i] == 1 && throw(ArgumentError("The input matrix cannot have a row of weight one.")) + for i = 1:nr + row_wts[i] == 1 && + throw(ArgumentError("The input matrix cannot have a row of weight one.")) end - for i in 1:nc - col_wts[i] == 1 && throw(ArgumentError("The input matrix cannot have a column of weight one.")) + for i = 1:nc + col_wts[i] == 1 && + throw(ArgumentError("The input matrix cannot have a column of weight one.")) end # the original paper appears to switch X and Z compared to Bacon-Shor # but this is corrected here to match # X - consequetive column pairs - X_gauges = zero_matrix(F, sum([col_wts[i] - 1 for i in 1:length(col_wts)]), n) + X_gauges = zero_matrix(F, sum([col_wts[i] - 1 for i = 1:length(col_wts)]), n) curr_row = 1 F_one = F(1) - for c in 1:nc + for c = 1:nc r1 = 1 while r1 < nr if !iszero(A[r1, c]) at_end = true - for r2 in r1 + 1:nr + for r2 = (r1+1):nr if !iszero(A[r2, c]) X_gauges[curr_row, linear_index[r1, c]] = F_one X_gauges[curr_row, linear_index[r2, c]] = F_one @@ -168,14 +226,14 @@ function BravyiBaconShorCode(A::CTMatrixTypes) end # Z - consequetive row pairs - Z_gauges = zero_matrix(F, sum([row_wts[i] - 1 for i in 1:length(row_wts)]), n) + Z_gauges = zero_matrix(F, sum([row_wts[i] - 1 for i = 1:length(row_wts)]), n) curr_row = 1 - for r in 1:nr + for r = 1:nr c1 = 1 while c1 < nc if !iszero(A[r, c1]) at_end = true - for c2 in c1 + 1:nc + for c2 = (c1+1):nc if !iszero(A[r, c2]) Z_gauges[curr_row, linear_index[r, c1]] = F_one Z_gauges[curr_row, linear_index[r, c2]] = F_one @@ -199,24 +257,47 @@ function BravyiBaconShorCode(A::CTMatrixTypes) end GeneralizedBaconShorCode(A::CTMatrixTypes) = BravyiSubsystemCode(A) +""" +```jldoctest +julia> using CodingTheory: LocalBravyiBaconShorCode + +julia> using Nemo; + +julia> F = Nemo.fpField(UInt(2)); + +julia> A = Nemo.matrix(F, [1 1 0; + 0 1 1; + 1 0 1]); + +julia> c = LocalBravyiBaconShorCode(A); + +julia> c.stabs +[1 1 0 1 1 1 1 1 0 0 0 0 0 0 0 0] +[0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 1] + +julia> c.n, c.k, c.r +(8, 2, 4) +``` +""" function LocalBravyiBaconShorCode(A::CTMatrixTypes) iszero(A) && throw(ArgumentError("The input matrix cannot be zero.")) F = base_ring(A) - Int(order(F)) == 2 || throw(ArgumentError("Construction is only valid for binary martices.")) + Int(order(F)) == 2 || + throw(ArgumentError("Construction is only valid for binary martices.")) nr, nc = size(A) row_firsts = zeros(Int, 1, nr) row_lasts = zeros(Int, 1, nr) - for r in 1:nr - for c in 1:nc + for r = 1:nr + for c = 1:nc if !iszero(A[r, c]) row_firsts[r] = c break end end end - for r in 1:nr - for c in nc:-1:1 + for r = 1:nr + for c = nc:-1:1 if !iszero(A[r, c]) row_lasts[r] = c break @@ -224,22 +305,23 @@ function LocalBravyiBaconShorCode(A::CTMatrixTypes) end end - for i in 1:nr - row_firsts[i] == row_lasts[i] && throw(ArgumentError("The input matrix cannot have a row of weight one.")) + for i = 1:nr + row_firsts[i] == row_lasts[i] && + throw(ArgumentError("The input matrix cannot have a row of weight one.")) end col_firsts = zeros(Int, 1, nc) col_lasts = zeros(Int, 1, nc) - for c in 1:nc - for r in 1:nr + for c = 1:nc + for r = 1:nr if !iszero(A[r, c]) col_firsts[c] = r break end end end - for c in 1:nc - for r in nr:-1:1 + for c = 1:nc + for r = nr:-1:1 if !iszero(A[r, c]) col_lasts[c] = r break @@ -247,16 +329,17 @@ function LocalBravyiBaconShorCode(A::CTMatrixTypes) end end - for i in 1:nc - col_firsts[i] == col_lasts[i] && throw(ArgumentError("The input matrix cannot have a column of weight one.")) + for i = 1:nc + col_firsts[i] == col_lasts[i] && + throw(ArgumentError("The input matrix cannot have a column of weight one.")) end n = 0 extra_Xs = 0 extra_Zs = 0 - linear_index = Dict{Tuple{Int, Int}, Int}() - for r in 1:nr - for c in 1:nc + linear_index = Dict{Tuple{Int,Int},Int}() + for r = 1:nr + for c = 1:nc if row_firsts[r] <= c <= row_lasts[r] || col_firsts[c] <= r <= col_lasts[c] n += 1 linear_index[(r, c)] = n @@ -269,20 +352,22 @@ function LocalBravyiBaconShorCode(A::CTMatrixTypes) end # X - consequetive column pairs + single qubit operators for each 0 in a row - X_gauges = zero_matrix(F, sum([row_lasts[i] - row_firsts[i] for i in 1:nr]) + extra_Xs, n) + X_gauges = + zero_matrix(F, sum([row_lasts[i] - row_firsts[i] for i = 1:nr]) + extra_Xs, n) # Z - consequetive row pairs + single qubit operators for each 0 in a column - Z_gauges = zero_matrix(F, sum([col_lasts[i] - col_firsts[i] for i in 1:nc]) + extra_Zs, n) + Z_gauges = + zero_matrix(F, sum([col_lasts[i] - col_firsts[i] for i = 1:nc]) + extra_Zs, n) curr_row_X = 1 curr_row_Z = 1 # the original paper appears to switch X and Z compared to Bacon-Shor # but this is corrected here to match F_one = F(1) - for c in 1:nc - for r in col_firsts[c]:col_lasts[c] + for c = 1:nc + for r = col_firsts[c]:col_lasts[c] if r != col_lasts[c] X_gauges[curr_row_X, linear_index[r, c]] = F_one - X_gauges[curr_row_X, linear_index[r + 1, c]] = F_one + X_gauges[curr_row_X, linear_index[r+1, c]] = F_one curr_row_X += 1 end if iszero(A[r, c]) @@ -292,11 +377,11 @@ function LocalBravyiBaconShorCode(A::CTMatrixTypes) end end - for r in 1:nr - for c in row_firsts[r]:row_lasts[r] + for r = 1:nr + for c = row_firsts[r]:row_lasts[r] if c != row_lasts[r] Z_gauges[curr_row_Z, linear_index[r, c]] = F_one - Z_gauges[curr_row_Z, linear_index[r, c + 1]] = F_one + Z_gauges[curr_row_Z, linear_index[r, c+1]] = F_one curr_row_Z += 1 end if iszero(A[r, c]) @@ -315,18 +400,39 @@ function LocalBravyiBaconShorCode(A::CTMatrixTypes) end AugmentedBravyiBaconShorCode(A::CTMatrixTypes) = LocalBravyiBaconShorCode(A) -# subsystem codes were described by Bacon and Casaccino in [19]. The construction of [19] starts from a pair of classical linear codes C1 = [n1, k1, d1] and C2 = [n2, k2, d2]. A quantum subsystem code is then defined by placing a physical qubit at every cell of a ma- trix A of size n1 × n2. The X-part of the gauge group is defined by replicating the parity checks of C1 in every col- umn of A (in the X-basis). Similarly, the Z-part of the gauge group is defined by replicating the parity checks of C2 in every row of A (in the Z-basis). The resulting subsystem code has parameters [n1n2, k1k2, min (d1, d2)]. - -# Napp & Preskill, "Optimal Bacon-Shor Codes", (2012) """ NappPreskill3DCode(m::Int, n::Int, k::Int) -Return the Napp and Preskill 3D, modifed Bacon-Shor code. +Return the Napp and Preskill 3D [`napp2012optimalbaconshorcodes`](@cite), modifed Bacon-Shor code. + +Constructs a Napp and Preskill `3D` [`napp2012optimalbaconshorcodes`](@cite), modifed Bacon-Shor code. +It generalizes the Bacon-Casaccino framework [`bacon2006qecsubsystem`](@cite), where physical qubits +are placed on a lattice. For their original `2D` construction, given classical codes `C₁ = [n₁,k₁,d₁]` and +`C₂ = [n₂,k₂,d₂]`, qubits occupy an `n₁ × n₂` matrix. The `X`-type gauge operators replicate `C₁`'s parity checks +vertically (acting on columns in `X`-basis), while `Z`-type gauges replicate `C₂`'s checks horizontally +(rows in `Z`-basis). This yields a subsystem code with parameters `[[n₁n₂, k₁k₂, min(d₁,d₂)]]`. The `3D` variant +extends this logic to cubic lattices with modified gauge groupings. + +```jldoctest +julia> using CodingTheory + +julia> c = NappPreskill3DCode(2,2,2); + +julia> c.stabs +[1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0] +[0 1 0 1 0 1 0 1 0 0 0 0 0 0 0 0] +[0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0] +[0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1] + +julia> c.n, c.k, c.r, c.d_dressed +(8, 1, 3, 2) +``` """ function NappPreskill3DCode(m::Int, n::Int, k::Int) - (2 <= m && 2 <= n && 2 <= k) || throw(DomainError("Lattice dimensions must be at least two")) + (2 <= m && 2 <= n && 2 <= k) || + throw(DomainError("Lattice dimensions must be at least two")) - linear_index = Dict{Tuple{Int, Int, Int}, Int}() + linear_index = Dict{Tuple{Int,Int,Int},Int}() for (i, tup) in enumerate(Base.Iterators.product(1:m, 1:n, 1:k)) linear_index[tup] = i end @@ -337,15 +443,17 @@ function NappPreskill3DCode(m::Int, n::Int, k::Int) gauges = zero_matrix(F, (m - 1) * n * k + m * (n - 1) * k + m * n * (k - 1), 2 * len) curr_row = 1 # X's - for l in 1:k - for i in 1:m - for j in 1:n + for l = 1:k + for i = 1:m + for j = 1:n if j != n - gauges[curr_row, linear_index[i, j, l]] = gauges[curr_row, linear_index[i, j + 1, l]] = F_one + gauges[curr_row, linear_index[i, j, l]] = + gauges[curr_row, linear_index[i, j+1, l]] = F_one curr_row += 1 end if i != m - gauges[curr_row, linear_index[i, j, l]] = gauges[curr_row, linear_index[i + 1, j, l]] = F_one + gauges[curr_row, linear_index[i, j, l]] = + gauges[curr_row, linear_index[i+1, j, l]] = F_one curr_row += 1 end end @@ -353,10 +461,11 @@ function NappPreskill3DCode(m::Int, n::Int, k::Int) end # Z's - for i in 1:m - for j in 1:n - for l in 1:k - 1 - gauges[curr_row, linear_index[i, j, l] + len] = gauges[curr_row, linear_index[i, j, l + 1] + len] = F_one + for i = 1:m + for j = 1:n + for l = 1:(k-1) + gauges[curr_row, linear_index[i, j, l]+len] = + gauges[curr_row, linear_index[i, j, l+1]+len] = F_one curr_row += 1 end end @@ -372,12 +481,22 @@ end """ NappPreskill4DCode(x::Int, y::Int, z::Int, w::Int) -Return the Napp and Preskill 4D, modifed Bacon-Shor code. +Return the Napp and Preskill `4D`, modifed Bacon-Shor code [`napp2012optimalbaconshorcodes`](@cite). + +```jldoctest +julia> using CodingTheory + +julia> c = NappPreskill4DCode(2,2,2,2); + +julia> c.n, c.k, c.r +(16, 1, 9) +``` """ function NappPreskill4DCode(x::Int, y::Int, z::Int, w::Int) - (2 <= x && 2 <= y && 2 <= z && 2 <= w) || throw(DomainError("Lattice dimensions must be at least two")) + (2 <= x && 2 <= y && 2 <= z && 2 <= w) || + throw(DomainError("Lattice dimensions must be at least two")) - linear_index = Dict{Tuple{Int, Int, Int, Int}, Int}() + linear_index = Dict{Tuple{Int,Int,Int,Int},Int}() for (i, tup) in enumerate(Base.Iterators.product(1:x, 1:y, 1:z, 1:w)) linear_index[tup] = i end @@ -385,22 +504,31 @@ function NappPreskill4DCode(x::Int, y::Int, z::Int, w::Int) len = x * y * z * w F = Oscar.Nemo.Native.GF(2) F_one = F(1) - gauges = zero_matrix(F, (x - 1) * y * z * w + x * (y - 1) * z * w + x * y * (z - 1) * w + x * y * z * (w - 1), 2 * len) + gauges = zero_matrix( + F, + (x - 1) * y * z * w + + x * (y - 1) * z * w + + x * y * (z - 1) * w + + x * y * z * (w - 1), + 2 * len, + ) curr_row = 1 ## XX acting on each neighboring qubits in each xy-plane with z, w fixed ## ZZ in zw-plane with x, y fixed # X's - for k in 1:z - for l in 1:w - for i in 1:x - for j in 1:y + for k = 1:z + for l = 1:w + for i = 1:x + for j = 1:y if i != x - gauges[curr_row, linear_index[i, j, k, l]] = gauges[curr_row, linear_index[i + 1, j, k, l]] = F_one + gauges[curr_row, linear_index[i, j, k, l]] = + gauges[curr_row, linear_index[i+1, j, k, l]] = F_one curr_row += 1 end if j != y - gauges[curr_row, linear_index[i, j, k, l]] = gauges[curr_row, linear_index[i, j + 1, k, l]] = F_one + gauges[curr_row, linear_index[i, j, k, l]] = + gauges[curr_row, linear_index[i, j+1, k, l]] = F_one curr_row += 1 end end @@ -409,16 +537,18 @@ function NappPreskill4DCode(x::Int, y::Int, z::Int, w::Int) end # Z's - for i in 1:x - for j in 1:y - for k in 1:z - for l in 1:w + for i = 1:x + for j = 1:y + for k = 1:z + for l = 1:w if k != z - gauges[curr_row, linear_index[i, j, k, l] + len] = gauges[curr_row, linear_index[i, j, k + 1, l] + len] = F_one + gauges[curr_row, linear_index[i, j, k, l]+len] = + gauges[curr_row, linear_index[i, j, k+1, l]+len] = F_one curr_row += 1 end if l != w - gauges[curr_row, linear_index[i, j, k, l] + len] = gauges[curr_row, linear_index[i, j, k, l + 1] + len] = F_one + gauges[curr_row, linear_index[i, j, k, l]+len] = + gauges[curr_row, linear_index[i, j, k, l+1]+len] = F_one curr_row += 1 end end @@ -429,12 +559,20 @@ function NappPreskill4DCode(x::Int, y::Int, z::Int, w::Int) return SubsystemCode(gauges, logs_alg = :VS) end -# Bravyi et al, "Subsystem surface codes with three-qubit check operators", (2013) """ SubsystemToricCode(m::Int, n::Int) Return the subsystem toric code on a rectangular lattice with `m` rows and `n` -columns of squares. +columns of squares [`bravyi2013subsystemsurfacecodesthreequbit`](@cite). + +```jldoctest +julia> using CodingTheory + +julia> c = SubsystemToricCode(2,2); + +julia> c.n, c.k, c.r +(12, 2, 4) +``` """ function SubsystemToricCode(m::Int, n::Int) (2 <= m && 2 <= n) || throw(DomainError("Lattice dimensions must be at least two")) @@ -446,118 +584,118 @@ function SubsystemToricCode(m::Int, n::Int) stabs = zero_matrix(F, 2 * m * n, 2 * len) curr_row_stab = 1 curr_row_gauge = 1 - for r in 1:m + for r = 1:m top_left = 3 * n * (r - 1) + 1 row_right = top_left + 2 * n - 1 - for c in 1:n + for c = 1:n # top left - Z - gauges[curr_row_gauge, top_left + len] = F_one - gauges[curr_row_gauge, top_left + 1 + len] = F_one - gauges[curr_row_gauge, row_right + c + len] = F_one + gauges[curr_row_gauge, top_left+len] = F_one + gauges[curr_row_gauge, top_left+1+len] = F_one + gauges[curr_row_gauge, row_right+c+len] = F_one curr_row_gauge += 1 # top right - X - gauges[curr_row_gauge, top_left + 1] = F_one + gauges[curr_row_gauge, top_left+1] = F_one if c != n - gauges[curr_row_gauge, top_left + 2] = F_one - gauges[curr_row_gauge, row_right + c + 1] = F_one + gauges[curr_row_gauge, top_left+2] = F_one + gauges[curr_row_gauge, row_right+c+1] = F_one else - gauges[curr_row_gauge, row_right - 2 * n + 1] = F_one - gauges[curr_row_gauge, row_right + 1] = F_one + gauges[curr_row_gauge, row_right-2*n+1] = F_one + gauges[curr_row_gauge, row_right+1] = F_one end curr_row_gauge += 1 # bottom left - X - gauges[curr_row_gauge, row_right + c] = F_one + gauges[curr_row_gauge, row_right+c] = F_one if r != m - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 1] = F_one - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 2] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+1] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+2] = F_one else - gauges[curr_row_gauge, 2 * (c - 1) + 1] = F_one - gauges[curr_row_gauge, 2 * (c - 1) + 2] = F_one + gauges[curr_row_gauge, 2*(c-1)+1] = F_one + gauges[curr_row_gauge, 2*(c-1)+2] = F_one end curr_row_gauge += 1 # bottom right - Z if r == m && c == n - gauges[curr_row_gauge, 1 + len] = F_one - gauges[curr_row_gauge, 2 * n + len] = F_one - gauges[curr_row_gauge, row_right + 1 + len] = F_one + gauges[curr_row_gauge, 1+len] = F_one + gauges[curr_row_gauge, 2*n+len] = F_one + gauges[curr_row_gauge, row_right+1+len] = F_one elseif r == m - gauges[curr_row_gauge, row_right + c + 1 + len] = F_one - gauges[curr_row_gauge, 2 * (c - 1) + 2 + len] = F_one - gauges[curr_row_gauge, 2 * (c - 1) + 3 + len] = F_one + gauges[curr_row_gauge, row_right+c+1+len] = F_one + gauges[curr_row_gauge, 2*(c-1)+2+len] = F_one + gauges[curr_row_gauge, 2*(c-1)+3+len] = F_one elseif c != n - gauges[curr_row_gauge, row_right + c + 1 + len] = F_one - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 2 + len] = F_one - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 3 + len] = F_one + gauges[curr_row_gauge, row_right+c+1+len] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+2+len] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+3+len] = F_one else - gauges[curr_row_gauge, row_right + 1 + len] = F_one - gauges[curr_row_gauge, row_right + n + 1 + len] = F_one - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 2 + len] = F_one + gauges[curr_row_gauge, row_right+1+len] = F_one + gauges[curr_row_gauge, row_right+n+1+len] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+2+len] = F_one end curr_row_gauge += 1 # X - stabs[curr_row_stab, top_left + 1] = F_one + stabs[curr_row_stab, top_left+1] = F_one if c != n - stabs[curr_row_stab, top_left + 2] = F_one - stabs[curr_row_stab, row_right + c + 1] = F_one + stabs[curr_row_stab, top_left+2] = F_one + stabs[curr_row_stab, row_right+c+1] = F_one else - stabs[curr_row_stab, row_right - 2 * n + 1] = F_one - stabs[curr_row_stab, row_right + 1] = F_one + stabs[curr_row_stab, row_right-2*n+1] = F_one + stabs[curr_row_stab, row_right+1] = F_one end - stabs[curr_row_stab, row_right + c] = F_one + stabs[curr_row_stab, row_right+c] = F_one if r != m - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 1] = F_one - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 2] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+1] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+2] = F_one else - stabs[curr_row_stab, 2 * (c - 1) + 1] = F_one - stabs[curr_row_stab, 2 * (c - 1) + 2] = F_one + stabs[curr_row_stab, 2*(c-1)+1] = F_one + stabs[curr_row_stab, 2*(c-1)+2] = F_one end curr_row_stab += 1 # Z - stabs[curr_row_stab, top_left + len] = F_one - stabs[curr_row_stab, top_left + 1 + len] = F_one - stabs[curr_row_stab, row_right + c + len] = F_one + stabs[curr_row_stab, top_left+len] = F_one + stabs[curr_row_stab, top_left+1+len] = F_one + stabs[curr_row_stab, row_right+c+len] = F_one if r == m && c == n - stabs[curr_row_stab, 1 + len] = F_one - stabs[curr_row_stab, 2 * n + len] = F_one - stabs[curr_row_stab, row_right + 1 + len] = F_one + stabs[curr_row_stab, 1+len] = F_one + stabs[curr_row_stab, 2*n+len] = F_one + stabs[curr_row_stab, row_right+1+len] = F_one elseif r == m - stabs[curr_row_stab, row_right + c + 1 + len] = F_one - stabs[curr_row_stab, 2 * (c - 1) + 2 + len] = F_one - stabs[curr_row_stab, 2 * (c - 1) + 3 + len] = F_one + stabs[curr_row_stab, row_right+c+1+len] = F_one + stabs[curr_row_stab, 2*(c-1)+2+len] = F_one + stabs[curr_row_stab, 2*(c-1)+3+len] = F_one elseif c != n - stabs[curr_row_stab, row_right + c + 1 + len] = F_one - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 2 + len] = F_one - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 3 + len] = F_one + stabs[curr_row_stab, row_right+c+1+len] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+2+len] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+3+len] = F_one else - stabs[curr_row_stab, row_right + 1 + len] = F_one - stabs[curr_row_stab, row_right + n + 1 + len] = F_one - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 2 + len] = F_one + stabs[curr_row_stab, row_right+1+len] = F_one + stabs[curr_row_stab, row_right+n+1+len] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+2+len] = F_one end curr_row_stab += 1 top_left += 2 end end - + logs = zero_matrix(F, 4, 2 * len) # top row is an X for pair one and a Z for pair two - for c in 1:2 * n + for c = 1:(2*n) logs[1, c] = F_one - logs[4, c + len] = F_one + logs[4, c+len] = F_one end # left column is a Z for pair one and an X for pair two - for r in 1:m + for r = 1:m top_left = 3 * n * (r - 1) + 1 - logs[2, top_left + len] = F_one - logs[2, top_left + 2 * n + len] = F_one + logs[2, top_left+len] = F_one + logs[2, top_left+2*n+len] = F_one logs[3, top_left] = F_one - logs[3, top_left + 2 * n] = F_one + logs[3, top_left+2*n] = F_one end - + S = SubsystemCode(gauges, logs_alg = :VS) S.k == 2 || error("Got wrong dimension for periodic case.") set_stabilizers!(S, stabs) @@ -573,7 +711,7 @@ end SubsystemToricCode(d::Int) Return the subsystem toric code on a square lattice with `d` rows and `d` -columns of squares. +columns of squares [`bravyi2013subsystemsurfacecodesthreequbit`](@cite). """ SubsystemToricCode(d::Int) = SubsystemToricCode(d, d) @@ -594,115 +732,115 @@ function SubsystemSurfaceCode(m::Int, n::Int) stabs = zero_matrix(F, 2 * m * n + 2 * n + 2 * m, 2 * len) curr_row_stab = 1 curr_row_gauge = 1 - for r in 1:m + for r = 1:m top_left = (3 * n + 2) * (r - 1) + 1 row_right = top_left + 2 * n - for c in 1:n + for c = 1:n # top left - Z - gauges[curr_row_gauge, top_left + len] = F_one - gauges[curr_row_gauge, top_left + 1 + len] = F_one - gauges[curr_row_gauge, row_right + c + len] = F_one + gauges[curr_row_gauge, top_left+len] = F_one + gauges[curr_row_gauge, top_left+1+len] = F_one + gauges[curr_row_gauge, row_right+c+len] = F_one curr_row_gauge += 1 # top right - X - gauges[curr_row_gauge, top_left + 1] = F_one - gauges[curr_row_gauge, top_left + 2] = F_one - gauges[curr_row_gauge, row_right + c + 1] = F_one + gauges[curr_row_gauge, top_left+1] = F_one + gauges[curr_row_gauge, top_left+2] = F_one + gauges[curr_row_gauge, row_right+c+1] = F_one curr_row_gauge += 1 # bottom left - X - gauges[curr_row_gauge, row_right + c] = F_one - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 2] = F_one - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 3] = F_one + gauges[curr_row_gauge, row_right+c] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+2] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+3] = F_one curr_row_gauge += 1 # bottom right - Z - gauges[curr_row_gauge, row_right + c + 1 + len] = F_one - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 3 + len] = F_one - gauges[curr_row_gauge, row_right + n + 2 * (c - 1) + 4 + len] = F_one + gauges[curr_row_gauge, row_right+c+1+len] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+3+len] = F_one + gauges[curr_row_gauge, row_right+n+2*(c-1)+4+len] = F_one curr_row_gauge += 1 # X - stabs[curr_row_stab, top_left + 1] = F_one - stabs[curr_row_stab, top_left + 2] = F_one - stabs[curr_row_stab, row_right + c + 1] = F_one - stabs[curr_row_stab, row_right + c] = F_one - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 2] = F_one - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 3] = F_one + stabs[curr_row_stab, top_left+1] = F_one + stabs[curr_row_stab, top_left+2] = F_one + stabs[curr_row_stab, row_right+c+1] = F_one + stabs[curr_row_stab, row_right+c] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+2] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+3] = F_one curr_row_stab += 1 # Z - stabs[curr_row_stab, top_left + len] = F_one - stabs[curr_row_stab, top_left + 1 + len] = F_one - stabs[curr_row_stab, row_right + c + len] = F_one - stabs[curr_row_stab, row_right + c + 1 + len] = F_one - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 3 + len] = F_one - stabs[curr_row_stab, row_right + n + 2 * (c - 1) + 4 + len] = F_one + stabs[curr_row_stab, top_left+len] = F_one + stabs[curr_row_stab, top_left+1+len] = F_one + stabs[curr_row_stab, row_right+c+len] = F_one + stabs[curr_row_stab, row_right+c+1+len] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+3+len] = F_one + stabs[curr_row_stab, row_right+n+2*(c-1)+4+len] = F_one curr_row_stab += 1 top_left += 2 end end # left - X - for r in 1:m + for r = 1:m top_left = (3 * n + 2) * (r - 1) + 1 shift = 2 * n + 1 stabs[curr_row_stab, top_left] = F_one - stabs[curr_row_stab, top_left + shift] = F_one + stabs[curr_row_stab, top_left+shift] = F_one curr_row_stab += 1 gauges[curr_row_gauge, top_left] = F_one - gauges[curr_row_gauge, top_left + shift] = F_one + gauges[curr_row_gauge, top_left+shift] = F_one curr_row_gauge += 1 end # right - X - for r in 1:m + for r = 1:m top_left = (3 * n + 2) * (r - 1) + 1 row_right = top_left + 2 * n - stabs[curr_row_stab, row_right + n + 1] = F_one - stabs[curr_row_stab, row_right + 3 * n + 2] = F_one + stabs[curr_row_stab, row_right+n+1] = F_one + stabs[curr_row_stab, row_right+3*n+2] = F_one curr_row_stab += 1 - gauges[curr_row_gauge, row_right + n + 1] = F_one - gauges[curr_row_gauge, row_right + 3 * n + 2] = F_one + gauges[curr_row_gauge, row_right+n+1] = F_one + gauges[curr_row_gauge, row_right+3*n+2] = F_one curr_row_gauge += 1 end # top - Z top_left = 1 - for c in 1:n - stabs[curr_row_stab, top_left + 1 + len] = F_one - stabs[curr_row_stab, top_left + 2 + len] = F_one + for c = 1:n + stabs[curr_row_stab, top_left+1+len] = F_one + stabs[curr_row_stab, top_left+2+len] = F_one curr_row_stab += 1 - gauges[curr_row_gauge, top_left + 1 + len] = F_one - gauges[curr_row_gauge, top_left + 2 + len] = F_one + gauges[curr_row_gauge, top_left+1+len] = F_one + gauges[curr_row_gauge, top_left+2+len] = F_one curr_row_gauge += 1 top_left += 2 end # bottom - Z bottom_left = len - 2 * n - for c in 1:n - stabs[curr_row_stab, bottom_left + len] = F_one - stabs[curr_row_stab, bottom_left + 1 + len] = F_one + for c = 1:n + stabs[curr_row_stab, bottom_left+len] = F_one + stabs[curr_row_stab, bottom_left+1+len] = F_one curr_row_stab += 1 - gauges[curr_row_gauge, bottom_left + len] = F_one - gauges[curr_row_gauge, bottom_left + 1 + len] = F_one + gauges[curr_row_gauge, bottom_left+len] = F_one + gauges[curr_row_gauge, bottom_left+1+len] = F_one curr_row_gauge += 1 bottom_left += 2 end logs = zero_matrix(F, 2, 2 * len) # top row is a logical X - for c in 1:2 * n + 1 + for c = 1:(2*n+1) logs[1, c] = F_one end # left column is a logical Z - for r in 1:m - logs[2, (3 * n + 2) * (r - 1) + 1 + len] = F_one - logs[2, (3 * n + 2) * (r - 1) + 2 * n + 2 + len] = F_one + for r = 1:m + logs[2, (3*n+2)*(r-1)+1+len] = F_one + logs[2, (3*n+2)*(r-1)+2*n+2+len] = F_one end - logs[2, 2 * len - 2 * n] = F_one - + logs[2, 2*len-2*n] = F_one + S = SubsystemCode(gauges, logs_alg = :VS) S.k == 1 || error("Got wrong dimension for non-periodic case.") set_stabilizers!(S, stabs) @@ -725,11 +863,11 @@ SubsystemSurfaceCode(d::Int) = SubsystemSurfaceCode(d, d) # TODO: charvec in all of these ############################# - # Stabilizer codes +# Stabilizer codes ############################# ############################# - # Misc codes +# Misc codes ############################# """ @@ -781,8 +919,16 @@ Q713() = SteaneCode() Return the `[[9, 1, 3]]` Shor code. """ function ShorCode() - S = CSSCode(["ZZIIIIIII", "IZZIIIIII", "IIIZZIIII", "IIIIZZIII", "IIIIIIZZI", "IIIIIIIZZ", - "XXXXXXIII", "IIIXXXXXX"]) + S = CSSCode([ + "ZZIIIIIII", + "IZZIIIIII", + "IIIZZIIII", + "IIIIZZIII", + "IIIIIIZZI", + "IIIIIIIZZ", + "XXXXXXIII", + "IIIXXXXXX", + ]) set_minimum_distance!(S, 3) return S end @@ -815,12 +961,17 @@ end function Q823() F = Oscar.Nemo.Native.GF(2) - stabs = matrix(F, [1 0 0 0 1 0 0 0 1 1 1 1 0 0 0 0; - 0 0 0 1 0 1 0 0 1 0 0 0 0 1 0 0; - 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 0; - 0 0 1 0 1 1 1 0 0 1 1 0 1 1 0 0; - 0 0 1 1 1 0 1 0 0 0 0 1 0 1 1 1; - 0 0 0 0 0 0 1 1 0 0 1 0 0 0 1 0]); + stabs = matrix( + F, + [ + 1 0 0 0 1 0 0 0 1 1 1 1 0 0 0 0; + 0 0 0 1 0 1 0 0 1 0 0 0 0 1 0 0; + 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 0; + 0 0 1 0 1 1 1 0 0 1 1 0 1 1 0 0; + 0 0 1 1 1 0 1 0 0 0 0 1 0 1 1 1; + 0 0 0 0 0 0 1 1 0 0 1 0 0 0 1 0 + ], + ); S = StabilizerCode(stabs) set_minimum_distance!(S, 3) return S @@ -840,9 +991,22 @@ SmallestInterestingColorCode() = Q832() Return the `[[15, 1, 3]]` quantum Reed-Muller code. """ function Q15RM() - S = StabilizerCode(["ZIZIZIZIZIZIZIZ", "IZZIIZZIIZZIIZZ", "IIIZZZZIIIIZZZZ", "IIIIIIIZZZZZZZZ", - "IIZIIIZIIIZIIIZ", "IIIIZIZIIIIIZIZ", "IIIIIZZIIIIIIZZ", "IIIIIIIIIZZIIZZ", "IIIIIIIIIIIZZZZ", - "IIIIIIIIZIZIZIZ", "XIXIXIXIXIXIXIX", "IXXIIXXIIXXIIXX", "IIIXXXXIIIIXXXX", "IIIIIIIXXXXXXXX"]) + S = StabilizerCode([ + "ZIZIZIZIZIZIZIZ", + "IZZIIZZIIZZIIZZ", + "IIIZZZZIIIIZZZZ", + "IIIIIIIZZZZZZZZ", + "IIZIIIZIIIZIIIZ", + "IIIIZIZIIIIIZIZ", + "IIIIIZZIIIIIIZZ", + "IIIIIIIIIZZIIZZ", + "IIIIIIIIIIIZZZZ", + "IIIIIIIIZIZIZIZ", + "XIXIXIXIXIXIXIX", + "IXXIIXXIIXXIIXX", + "IIIXXXXIIIIXXXX", + "IIIIIIIXXXXXXXX", + ]) set_minimum_distance!(S, 3) return S end @@ -854,8 +1018,16 @@ Q1513() = Q15RM() Return the `[[15, 7, 3]]` quantum Hamming code. """ function Q1573() - S = StabilizerCode(["IIIIIIIXXXXXXXX", "IIIXXXXIIIIXXXX", "IXXIIXXIIXXIIXX", "XIXIXIXIXIXIXIX", - "IIIIIIIZZZZZZZZ", "IIIZZZZIIIIZZZZ", "IZZIIZZIIZZIIZZ", "ZIZIZIZIZIZIZIZ"]) + S = StabilizerCode([ + "IIIIIIIXXXXXXXX", + "IIIXXXXIIIIXXXX", + "IXXIIXXIIXXIIXX", + "XIXIXIXIXIXIXIX", + "IIIIIIIZZZZZZZZ", + "IIIZZZZIIIIZZZZ", + "IZZIIZZIIZZIIZZ", + "ZIZIZIZIZIZIZIZ", + ]) # one can use a basis for this such that the first logical pair is transversal X, Z set_minimum_distance!(S, 3) return S @@ -879,7 +1051,7 @@ function GrossCode() end ############################# - # Triangular Surface Codes +# Triangular Surface Codes ############################# function _triangular_lattice(L::Int) @@ -888,9 +1060,9 @@ function _triangular_lattice(L::Int) # 2 - diagonal numbering = zeros(Int, L, L, 3) num = 1 - for i in 1:L - for j in 1:L - for k in 1:3 + for i = 1:L + for j = 1:L + for k = 1:3 numbering[i, j, k] = num num += 1 end @@ -899,33 +1071,33 @@ function _triangular_lattice(L::Int) return numbering end -function _triangular_lattice_X_stabilizers(L::Int, numbering::Array{Int64, 3}) +function _triangular_lattice_X_stabilizers(L::Int, numbering::Array{Int64,3}) F = Oscar.Nemo.Native.GF(2) stabilizers = zero_matrix(F, L^2, 3 * L^2) r = 1 - for i in 1:L - for j in 1:L + for i = 1:L + for j = 1:L stabilizers[r, numbering[i, j, 1]] = 1 stabilizers[r, numbering[i, j, 2]] = 1 stabilizers[r, numbering[i, j, 3]] = 1 if i == 1 stabilizers[r, numbering[end, j, 1]] = 1 else - stabilizers[r, numbering[i - 1, j, 1]] = 1 + stabilizers[r, numbering[i-1, j, 1]] = 1 end if j == 1 stabilizers[r, numbering[i, end, 2]] = 1 else - stabilizers[r, numbering[i, j - 1, 2]] = 1 + stabilizers[r, numbering[i, j-1, 2]] = 1 end if i == 1 && j == 1 stabilizers[r, numbering[end, end, 3]] = 1 elseif i != 1 && j == 1 - stabilizers[r, numbering[i - 1, end, 3]] = 1 + stabilizers[r, numbering[i-1, end, 3]] = 1 elseif i == 1 && j != 1 - stabilizers[r, numbering[end, j - 1, 3]] = 1 + stabilizers[r, numbering[end, j-1, 3]] = 1 else - stabilizers[r, numbering[i - 1, j - 1, 3]] = 1 + stabilizers[r, numbering[i-1, j-1, 3]] = 1 end r += 1 end @@ -933,18 +1105,18 @@ function _triangular_lattice_X_stabilizers(L::Int, numbering::Array{Int64, 3}) return hcat(stabilizers, zero_matrix(F, L^2, 3 * L^2)) end -function _triangular_lattice_Z_stabilizers(L::Int, numbering::Array{Int64, 3}) +function _triangular_lattice_Z_stabilizers(L::Int, numbering::Array{Int64,3}) F = Oscar.Nemo.Native.GF(2) stabilizers = zero_matrix(F, 2 * L^2, 3 * L^2) r = 1 - for i in 1:L - for j in 1:L + for i = 1:L + for j = 1:L stabilizers[r, numbering[i, j, 2]] = 1 stabilizers[r, numbering[i, j, 3]] = 1 if j == L stabilizers[r, numbering[i, 1, 1]] = 1 else - stabilizers[r, numbering[i, j + 1, 1]] = 1 + stabilizers[r, numbering[i, j+1, 1]] = 1 end r += 1 @@ -953,7 +1125,7 @@ function _triangular_lattice_Z_stabilizers(L::Int, numbering::Array{Int64, 3}) if i == L stabilizers[r, numbering[1, j, 2]] = 1 else - stabilizers[r, numbering[i + 1, j, 2]] = 1 + stabilizers[r, numbering[i+1, j, 2]] = 1 end r += 1 end @@ -961,32 +1133,32 @@ function _triangular_lattice_Z_stabilizers(L::Int, numbering::Array{Int64, 3}) return hcat(zero_matrix(F, 2 * L^2, 3 * L^2), stabilizers) end -function _triangular_lattice_X_logicals(L::Int, numbering::Array{Int64, 3}) +function _triangular_lattice_X_logicals(L::Int, numbering::Array{Int64,3}) # should be 0110110110 z = zeros(UInt8, 3 * L^2) logical1 = zeros(UInt8, 3 * L^2) - for j in 0:L - 1 - for k in 0:2 + for j = 0:(L-1) + for k = 0:2 if k == 0 - logical1[3 * j + k + 1] = 0x01 + logical1[3*j+k+1] = 0x01 elseif k == 1 - logical1[3 * j + k + 1] = 0x00 + logical1[3*j+k+1] = 0x00 else - logical1[3 * j + k + 1] = 0x01 + logical1[3*j+k+1] = 0x01 end end end logical1 = [logical1; z] logical2 = zeros(UInt8, 3 * L^2) - for j in 1:L - for k in 0:2 + for j = 1:L + for k = 0:2 if k == 0 - logical2[3 * j + k + 1] = 0x01 + logical2[3*j+k+1] = 0x01 elseif k == 1 - logical2[3 * j + k + 1] = 0x00 + logical2[3*j+k+1] = 0x00 else - logical2[3 * j + k + 1] = 0x01 + logical2[3*j+k+1] = 0x01 end end end @@ -994,32 +1166,36 @@ function _triangular_lattice_X_logicals(L::Int, numbering::Array{Int64, 3}) return [logical1, logical2] end -function _triangular_lattice_Z_logicals(L::Int, numbering::Array{Int64, 3}, symp::Bool=true) +function _triangular_lattice_Z_logicals( + L::Int, + numbering::Array{Int64,3}, + symp::Bool = true, +) # should be 1001001001 x = zeros(UInt8, 3 * L^2) logical1 = zeros(UInt8, 3 * L^2) - for j in 0:L - 1 - for k in 0:2 + for j = 0:(L-1) + for k = 0:2 if k == 0 - logical1[3 * j + k + 1] = 0x01 + logical1[3*j+k+1] = 0x01 elseif k == 1 - logical1[3 * j + k + 1] = 0x00 + logical1[3*j+k+1] = 0x00 else - logical1[3 * j + k + 1] = 0x01 + logical1[3*j+k+1] = 0x01 end end end logical1 = [z; logical1] logical2 = zeros(UInt8, 3 * L^2) - for j in 1:L - for k in 0:2 + for j = 1:L + for k = 0:2 if k == 0 - logical2[3 * j + k + 1] = 0x01 + logical2[3*j+k+1] = 0x01 elseif k == 1 - logical2[3 * j + k + 1] = 0x00 + logical2[3*j+k+1] = 0x00 else - logical2[3 * j + k + 1] = 0x01 + logical2[3*j+k+1] = 0x01 end end end @@ -1027,6 +1203,16 @@ function _triangular_lattice_Z_logicals(L::Int, numbering::Array{Int64, 3}, symp return [logical1, logical2] end +""" +```jldoctest +julia> using CodingTheory + +julia> c = TriangularSurfaceCode(2); + +julia> c.n, c.k +(24, 14) +``` +""" function TriangularSurfaceCode(L::Int) numbering = _triangular_lattice(L) X_stabs = _triangular_lattice_X_stabilizers(L, numbering) @@ -1035,11 +1221,11 @@ function TriangularSurfaceCode(L::Int) # println(Z_stabs) # logicals = [_triangular_lattice_X_logicals(L, numbering), _triangular_lattice_Z_logicals(L, numbering)] # TODO distances - return CSSCode(X_stabs[1:end - 1, :], Z_stabs[1:end - 1, :]) + return CSSCode(X_stabs[1:(end-1), :], Z_stabs[1:(end-1), :]) end ############################# - # Rotated Surface Codes +# Rotated Surface Codes ############################# function _R_Surf_stabs(d::Int) @@ -1053,9 +1239,9 @@ function _R_Surf_stabs(d::Int) i = 1 while i <= n - d S[row, i] = F_one - S[row, i + 1] = F_one - S[row, i + d] = F_one - S[row, i + d + 1] = F_one + S[row, i+1] = F_one + S[row, i+d] = F_one + S[row, i+d+1] = F_one row += 1 if (i + 2) % d == 0 i += 4 @@ -1068,7 +1254,7 @@ function _R_Surf_stabs(d::Int) i = 2 while i <= d - 1 S[row, i] = F_one - S[row, i + 1] = F_one + S[row, i+1] = F_one row += 1 i += 2 end @@ -1077,7 +1263,7 @@ function _R_Surf_stabs(d::Int) i = d * (d - 1) + 1 while i <= d * d - 2 S[row, i] = F_one - S[row, i + 1] = F_one + S[row, i+1] = F_one row += 1 i += 2 end @@ -1085,10 +1271,10 @@ function _R_Surf_stabs(d::Int) # Z's i = 2 while i < n - d - S[row, i + n] = F_one - S[row, i + 1 + n] = F_one - S[row, i + d + n] = F_one - S[row, i + d + 1 + n] = F_one + S[row, i+n] = F_one + S[row, i+1+n] = F_one + S[row, i+d+n] = F_one + S[row, i+d+1+n] = F_one row += 1 if (i + 2) % d == 0 i += 4 @@ -1100,8 +1286,8 @@ function _R_Surf_stabs(d::Int) # left Z's i = 1 while i < d * (d - 1) - S[row, i + n] = F_one - S[row, i + d + n] = F_one + S[row, i+n] = F_one + S[row, i+d+n] = F_one row += 1 i += 2 * d end @@ -1109,8 +1295,8 @@ function _R_Surf_stabs(d::Int) # right Z's i = 2 * d while i < d * d - S[row, i + n] = F_one - S[row, i + d + n] = F_one + S[row, i+n] = F_one + S[row, i+d+n] = F_one row += 1 i += 2 * d end @@ -1129,7 +1315,7 @@ function _R_Surf_logs(F::CTFieldTypes, d::Int) end i = 1 while i <= d - logs[2, i + n] = F_one + logs[2, i+n] = F_one i += 1 end @@ -1141,9 +1327,20 @@ end Return the `[[d^2, 1, d]]` rotated surface code. -This is the surface-13/17 configuration found in "Low-distance surface codes under realistic quantum noise" -by Tomita and Svore. The standard planar surface code is equivalent to their surface-25 configuration, which +This is the surface-`13/17` configuration by Tomita and Svore [`Tomita_2014`](@cite). The +standard planar surface code is equivalent to their surface-`25` configuration, which can be seen by viewing the stabilizers of PlanarSurfaceCode as an adjacency matrix. + +# Example + +```jldoctest +julia> using CodingTheory + +julia> c = RotatedSurfaceCode(3); + +julia> c.n, c.k, c.d +(9, 1, 3) +``` """ # BUG: doesn't work for even distances function RotatedSurfaceCode(d::Int) @@ -1157,7 +1354,7 @@ function RotatedSurfaceCode(d::Int) end ############################# - # XZZX Surface Codes +# XZZX Surface Codes ############################# function _XZZX_stabs_logs(d::Int) @@ -1168,12 +1365,12 @@ function _XZZX_stabs_logs(d::Int) F_one = F(1) i = 1 - for i in 1:n - d + for i = 1:(n-d) if i % d != 0 S[row, i] = F_one - S[row, i + 1 + n] = F_one - S[row, i + d + n] = F_one - S[row, i + d + 1] = F_one + S[row, i+1+n] = F_one + S[row, i+d+n] = F_one + S[row, i+d+1] = F_one row += 1; end end @@ -1181,8 +1378,8 @@ function _XZZX_stabs_logs(d::Int) # top row ZX's i = 2 while i <= d - 1 - S[row, i + n] = F_one - S[row, i + 1] = F_one + S[row, i+n] = F_one + S[row, i+1] = F_one row += 1 i += 2 end @@ -1191,7 +1388,7 @@ function _XZZX_stabs_logs(d::Int) i = d * (d - 1) + 1 while i <= d * d - 2 S[row, i] = F_one - S[row, i + 1 + n] = F_one + S[row, i+1+n] = F_one row += 1 i += 2 end @@ -1199,8 +1396,8 @@ function _XZZX_stabs_logs(d::Int) # left ZX's i = 1 while i < d * (d - 1) - S[row, i + n] = F_one - S[row, i + d] = F_one + S[row, i+n] = F_one + S[row, i+d] = F_one row += 1 i += 2 * d end @@ -1209,7 +1406,7 @@ function _XZZX_stabs_logs(d::Int) i = 2 * d while i < d * d S[row, i] = F_one - S[row, i + d + n] = F_one + S[row, i+d+n] = F_one row += 1 i += 2 * d end @@ -1221,7 +1418,7 @@ function _XZZX_stabs_logs(d::Int) if count % 2 == 1 logs[1, i] = F_one else - logs[1, i + n] = F_one + logs[1, i+n] = F_one end i += d count += 1 @@ -1230,7 +1427,7 @@ function _XZZX_stabs_logs(d::Int) count = 1 while i <= d if count % 2 == 1 - logs[2, i + n] = F_one + logs[2, i+n] = F_one else logs[2, i] = F_one end @@ -1245,6 +1442,15 @@ end XZZXSurfaceCode(d::Int) Return the `[[d^2, 1, d]]` XZZX surface code. + +```jldoctest +julia> using CodingTheory: XZZXSurfaceCode + +julia> c = XZZXSurfaceCode(3); + +julia> c.n, c.k, c.d +(9, 1, 3) +``` """ function XZZXSurfaceCode(d::Int) d >= 3 || throw(DomainError("Current implementation requires d ≥ 3.")) @@ -1257,7 +1463,7 @@ function XZZXSurfaceCode(d::Int) end ################################ - # Triangular Color Codes 4.8.8 +# Triangular Color Codes 4.8.8 ################################ """ @@ -1271,7 +1477,7 @@ Return the 4.8.8 triangular color code of distance `d` with trellis numbering. function TriangularColorCode488 end ################################ - # Triangular Color Codes 6.6.6 +# Triangular Color Codes 6.6.6 ################################ """ @@ -1285,7 +1491,7 @@ Return the 6.6.6 triangular color code of distance `d` with trellis numbering. function TriangularColorCode666 end ################################ - # Toric Codes +# Toric Codes ################################ """ @@ -1293,6 +1499,15 @@ function TriangularColorCode666 end Return the `[[2d^2, 2, d]]` toric code. +```jldoctest +julia> using CodingTheory + +julia> c = ToricCode(2); + +julia> c.n, c.k, c.d +(8, 2, 2) +``` + The lattice orientation used here follows the picture at https://errorcorrectionzoo.org/c/surface. """ function ToricCode(d::Int) @@ -1305,37 +1520,50 @@ function ToricCode(d::Int) qubit = 1 row_A = 1 row_B = 1 - for r in 1:2 * d + for r = 1:(2*d) if isodd(r) - for c in 1:d + for c = 1:d # println("r = $r, c = $c, row_A = $row_A") if r != 2 * d - 1 && c != d - A[row_A, qubit] = A[row_A, qubit + d] = A[row_A, qubit + d + 1] = A[row_A, qubit + 2 * d] = F_one + A[row_A, qubit] = + A[row_A, qubit+d] = + A[row_A, qubit+d+1] = A[row_A, qubit+2*d] = F_one elseif r == 2 * d - 1 && c != d - A[row_A, qubit] = A[row_A, qubit + d] = A[row_A, qubit + d + 1] = A[row_A, c] = F_one + A[row_A, qubit] = + A[row_A, qubit+d] = A[row_A, qubit+d+1] = A[row_A, c] = F_one elseif r != 2 * d - 1 && c == d - A[row_A, qubit] = A[row_A, qubit + d] = A[row_A, qubit + 1] = A[row_A, qubit + 2 * d] = F_one + A[row_A, qubit] = + A[row_A, qubit+d] = A[row_A, qubit+1] = A[row_A, qubit+2*d] = F_one elseif r == 2 * d - 1 && c == d - A[row_A, qubit] = A[row_A, qubit + d] = A[row_A, qubit + 1] = A[row_A, c] = F_one + A[row_A, qubit] = + A[row_A, qubit+d] = A[row_A, qubit+1] = A[row_A, c] = F_one else - error("Ran into unaccounted for case in creating the toric code lattice.") + error( + "Ran into unaccounted for case in creating the toric code lattice.", + ) end row_A += 1 qubit += 1 end else - for c in 1:d + for c = 1:d # println("r = $r, c = $c, row_B = $row_B") if r != 2 * d && c == 1 - B[row_B, qubit] = B[row_B, qubit + d] = B[row_B, qubit + 2 * d] = B[row_B, qubit + 2 * d - 1] = F_one + B[row_B, qubit] = + B[row_B, qubit+d] = + B[row_B, qubit+2*d] = B[row_B, qubit+2*d-1] = F_one elseif r != 2 * d && c != 1 - B[row_B, qubit] = B[row_B, qubit + d - 1] = B[row_B, qubit + d] = B[row_B, qubit + 2 * d] = F_one + B[row_B, qubit] = + B[row_B, qubit+d-1] = + B[row_B, qubit+d] = B[row_B, qubit+2*d] = F_one elseif r == 2 * d && c == 1 - B[row_B, qubit] = B[row_B, d] = B[row_B, d + 1] = B[row_B, 1] = F_one + B[row_B, qubit] = B[row_B, d] = B[row_B, d+1] = B[row_B, 1] = F_one elseif r == 2 * d && c != 1 - B[row_B, qubit] = B[row_B, c - 1] = B[row_B, c] = B[row_B, c + d] = F_one + B[row_B, qubit] = B[row_B, c-1] = B[row_B, c] = B[row_B, c+d] = F_one else - error("Ran into unaccounted for case in creating the toric code lattice.") + error( + "Ran into unaccounted for case in creating the toric code lattice.", + ) end row_B += 1 qubit += 1 @@ -1345,19 +1573,19 @@ function ToricCode(d::Int) S = CSSCode(A, B) Z1 = zero_matrix(S.F, 1, 4 * d^2) - for c in 1:d - Z1[1, c + d + S.n] = F_one + for c = 1:d + Z1[1, c+d+S.n] = F_one end X1 = zero_matrix(S.F, 1, 4 * d^2) - for r in 1:2:2 * d - X1[1, r * d + 1] = F_one + for r = 1:2:(2*d) + X1[1, r*d+1] = F_one end Z2 = zero_matrix(S.F, 1, 4 * d^2) - for r in 1:2:2 * d - Z2[1, (r - 1) * d + 1 + S.n] = F_one + for r = 1:2:(2*d) + Z2[1, (r-1)*d+1+S.n] = F_one end X2 = zero_matrix(S.F, 1, 4 * d^2) - for c in 1:d + for c = 1:d X2[1, c] = F_one end set_logicals!(S, vcat(X1, Z1, X2, Z2)) @@ -1367,7 +1595,7 @@ function ToricCode(d::Int) end ################################ - # Planar Surface Codes +# Planar Surface Codes ################################ """ @@ -1389,30 +1617,35 @@ function PlanarSurfaceCode(d_x::Int, d_z::Int) qubit = 1 row_A = 1 row_B = 1 - for r in 1:d_z - for c in 1:d_x + for r = 1:d_z + for c = 1:d_x if r != d_z if c == 1 - B[row_B, qubit] = B[row_B, qubit + d_x] = B[row_B, qubit + 2 * d_x - 1] = F_one + B[row_B, qubit] = B[row_B, qubit+d_x] = B[row_B, qubit+2*d_x-1] = F_one row_B += 1 elseif c == d_x - B[row_B, qubit] = B[row_B, qubit + d_x - 1] = B[row_B, qubit + 2 * d_x - 1] = F_one + B[row_B, qubit] = + B[row_B, qubit+d_x-1] = B[row_B, qubit+2*d_x-1] = F_one row_B += 1 else - B[row_B, qubit] = B[row_B, qubit + d_x - 1] = B[row_B, qubit + d_x] = B[row_B, qubit + 2 * d_x - 1] = F_one + B[row_B, qubit] = + B[row_B, qubit+d_x-1] = + B[row_B, qubit+d_x] = B[row_B, qubit+2*d_x-1] = F_one row_B += 1 end end if c != d_x if r == 1 - A[row_A, qubit] = A[row_A, qubit + 1] = A[row_A, qubit + d_x] = F_one + A[row_A, qubit] = A[row_A, qubit+1] = A[row_A, qubit+d_x] = F_one row_A += 1 elseif r == d_z - A[row_A, qubit] = A[row_A, qubit + 1] = A[row_A, qubit - d_x + 1] = F_one + A[row_A, qubit] = A[row_A, qubit+1] = A[row_A, qubit-d_x+1] = F_one row_A += 1 else - A[row_A, qubit] = A[row_A, qubit + 1] = A[row_A, qubit + d_x] = A[row_A, qubit - d_x + 1] = F_one + A[row_A, qubit] = + A[row_A, qubit+1] = + A[row_A, qubit+d_x] = A[row_A, qubit-d_x+1] = F_one row_A += 1 end end @@ -1423,12 +1656,12 @@ function PlanarSurfaceCode(d_x::Int, d_z::Int) S = CSSCode(A, B) X1 = zero_matrix(S.F, 1, 2 * S.n) - for r in 1:2:d_x - X1[1, d_z * (r - 1) + (d_z - 1) * (r - 1) + 1] = F_one + for r = 1:2:d_x + X1[1, d_z*(r-1)+(d_z-1)*(r-1)+1] = F_one end Z1 = zero_matrix(S.F, 1, 2 * S.n) - for c in 1:d_z - Z1[1, c + S.n] = F_one + for c = 1:d_z + Z1[1, c+S.n] = F_one end set_logicals!(S, vcat(X1, Z1)) set_dressed_X_minimum_distance!(S, d_x) @@ -1438,7 +1671,7 @@ end PlanarSurfaceCode(d::Int) = PlanarSurfaceCode(d, d) ################################ - # 3D PlanarSurfaceCode +# 3D PlanarSurfaceCode ################################ """ @@ -1454,12 +1687,12 @@ Return the 3D planar surface code of distance `d`. function PlanarSurfaceCode3D_X end ################################ - # XY Surface Codes +# XY Surface Codes ################################ # TODO remove quadratic """ - XYSurfaceCode(d_x::Int, d_z::Int) + XYSurfaceCode(d_x::Int, d_y::Int) XYSurfaceCode(d::Int) Return the `[[d_x * d_y + (d_x - 1) * (d_y - 1), 1, d_x/d_y]]` XY surface code of @@ -1476,33 +1709,40 @@ function XYSurfaceCode(d_x::Int, d_y::Int) M = zero_matrix(F, num_V - 1, 2 * num_V) qubit = 1 row = 1 - for r in 1:d_y - for c in 1:d_x - if r != d_z + for r = 1:d_y + for c = 1:d_x + if r != d_y if c == 1 - M[row, qubit] = M[row, qubit + d_x] = M[row, qubit + 2 * d_x - 1] = F_one - M[row, qubit + num_V] = M[row, qubit + d_x + num_V] = M[row, qubit + 2 * d_x - 1 + num_V] = F_one + M[row, qubit] = M[row, qubit+d_x] = M[row, qubit+2*d_x-1] = F_one + M[row, qubit+num_V] = + M[row, qubit+d_x+num_V] = M[row, qubit+2*d_x-1+num_V] = F_one row += 1 elseif c == d_x - M[row, qubit] = M[row, qubit + d_x - 1] = M[row, qubit + 2 * d_x - 1] = F_one - M[row, qubit + num_V] = M[row, qubit + d_x - 1 + num_V] = M[row, qubit + 2 * d_x - 1 + num_V] = F_one + M[row, qubit] = M[row, qubit+d_x-1] = M[row, qubit+2*d_x-1] = F_one + M[row, qubit+num_V] = + M[row, qubit+d_x-1+num_V] = M[row, qubit+2*d_x-1+num_V] = F_one row += 1 else - M[row, qubit] = M[row, qubit + d_x - 1] = M[row, qubit + d_x] = M[row, qubit + 2 * d_x - 1] = F_one - M[row, qubit + num_V] = M[row, qubit + d_x - 1 + num_V] = M[row, qubit + d_x + num_V] = M[row, qubit + 2 * d_x - 1 + num_V] = F_one + M[row, qubit] = + M[row, qubit+d_x-1] = + M[row, qubit+d_x] = M[row, qubit+2*d_x-1] = F_one + M[row, qubit+num_V] = + M[row, qubit+d_x-1+num_V] = + M[row, qubit+d_x+num_V] = M[row, qubit+2*d_x-1+num_V] = F_one row += 1 end end if c != d_x if r == 1 - M[row, qubit] = M[row, qubit + 1] = M[row, qubit + d_x] = F_one + M[row, qubit] = M[row, qubit+1] = M[row, qubit+d_x] = F_one row += 1 - elseif r == d_z - M[row, qubit] = M[row, qubit + 1] = M[row, qubit - d_x + 1] = F_one + elseif r == d_y + M[row, qubit] = M[row, qubit+1] = M[row, qubit-d_x+1] = F_one row += 1 else - M[row, qubit] = M[row, qubit + 1] = M[row, qubit + d_x] = M[row, qubit - d_x + 1] = F_one + M[row, qubit] = + M[row, qubit+1] = M[row, qubit+d_x] = M[row, qubit-d_x+1] = F_one row += 1 end end @@ -1582,21 +1822,30 @@ XYSurfaceCode(d::Int) = XYSurfaceCode(d, d) # display(M) # return # # Y distance is also 2 * d^2 - # set_dressed_X_minimum_distance!(S, d) - # set_dressed_Z_minimum_distance!(S, 2 * d^2) +# set_dressed_X_minimum_distance!(S, d) +# set_dressed_Z_minimum_distance!(S, 2 * d^2) # end ################################ - # H Codes +# H Codes ################################ """ HCode(k::Int) Return the `[[k + 4, k, 2]]` H code from `https://errorcorrectionzoo.org/c/quantum_h`. + +```jldoctest +julia> using CodingTheory + +julia> c = HCode(4); + +julia> c.n, c.k, c.d +(8, 4, 2) +``` """ function HCode(k::Int) - (2 <= k && iseven(k)) || throw(DomainError("Input must be >= 2 and even.")) + (2 <= k && iseven(k)) || throw(DomainError("Input must be >= 2 and even.")) F = Oscar.Nemo.Native.GF(2) F_one = F(1) @@ -1606,9 +1855,9 @@ function HCode(k::Int) Z[1, 1] = Z[1, 2] = Z[1, 3] = Z[1, 4] = F_one X[2, 1] = X[2, 2] = F_one Z[2, 1] = Z[2, 2] = F_one - for c in 5:k + 3 - X[2, c] = X[2, c + 1] = F_one - Z[2, c] = Z[2, c + 1] = F_one + for c = 5:(k+3) + X[2, c] = X[2, c+1] = F_one + Z[2, c] = Z[2, c+1] = F_one end S = CSSCode(X, Z) set_minimum_distance!(S, 2) @@ -1616,7 +1865,7 @@ function HCode(k::Int) end ################################# - # 3D Toric codes +# 3D Toric codes ################################# """ @@ -1632,7 +1881,7 @@ Return the 3D toric code of distance `d`. function ToricCode3D_X end ################################# - # 4D Toric codes +# 4D Toric codes ################################# @auto_hash_equals struct _Vertex @@ -1647,13 +1896,13 @@ end Compute the n-cells of a periodic d-dimensional hypercubic lattice with linear size l. """ function _compute_cells_periodic(l::Int, n::Int, d::Int = 4) - cells = Set{_Cell}() + cells = Set{_Cell}() coords_to_change = collect(combinations(1:d, n)) - for coord in Iterators.product([0:l - 1 for i in 1:d]...) + for coord in Iterators.product([0:(l-1) for i = 1:d]...) for directions in coords_to_change coord = collect(coord) - new_coords = Vector([copy(coord) for _ in 1:2^n - 1]) - for i in 1:2^n - 1, j in 1:n + new_coords = Vector([copy(coord) for _ = 1:(2^n-1)]) + for i = 1:(2^n-1), j = 1:n # TODO: convert to binary operator (i >> (j - 1)) & 1 == 1 ? new_coords[i][directions[j]] += 1 : nothing end @@ -1664,7 +1913,7 @@ function _compute_cells_periodic(l::Int, n::Int, d::Int = 4) push!(vertices, _Vertex(new_coord)) end - push!(cells, _Cell(vertices) ) + push!(cells, _Cell(vertices)) end end return cells @@ -1675,12 +1924,14 @@ end where n is the dimension of the sub_cells, and l the linear size of the system. """ function _contains(cells::Set{_Cell}, sub_cells::Set{_Cell}, n::Int, l::Int) - cell_dict = Dict{_Cell, Set{_Cell}}() + cell_dict = Dict{_Cell,Set{_Cell}}() for cell in cells - for sub_cell in combinations(collect(cell.vertices), 2^n) - l == 2 ? new_cell = _Cell(Set(_identify_cells(sub_cell))) : new_cell = _Cell(Set(sub_cell)) + for sub_cell in Combinatorics.combinations(collect(cell.vertices), 2^n) + l == 2 ? new_cell = _Cell(Set(_identify_cells(sub_cell))) : + new_cell = _Cell(Set(sub_cell)) !(new_cell in sub_cells) && continue - haskey(cell_dict, cell) ? push!(cell_dict[cell], new_cell) : cell_dict[cell] = Set([new_cell]) + haskey(cell_dict, cell) ? push!(cell_dict[cell], new_cell) : + cell_dict[cell] = Set([new_cell]) end end return cell_dict @@ -1690,7 +1941,7 @@ end Inverts a dictionary. """ function _inverse_dict(d::Dict) - d_inv = Dict{_Cell, Set{_Cell}}() + d_inv = Dict{_Cell,Set{_Cell}}() for (k, v) in d, c in v haskey(d_inv, c) ? push!(d_inv[c], k) : d_inv[c] = Set([k]) end @@ -1703,7 +1954,7 @@ end function _identify_cells(c::Vector{_Vertex}) new_c = deepcopy(c) l = length(c[1].coordinates) - for i in 1:l + for i = 1:l fix_boundary::Bool = true for v in c v.coordinates[i] < 2 ? fix_boundary = false : nothing @@ -1721,8 +1972,8 @@ end Create and fills check_matrices. """ function _compute_check_matrices(X_dict, Z_dict, q_dict, edge_dict, volume_dict) - X_stabs = spzeros(Bool, length(X_dict), length(q_dict) ) - Z_stabs = spzeros(Bool, length(Z_dict), length(q_dict) ) + X_stabs = spzeros(Bool, length(X_dict), length(q_dict)) + Z_stabs = spzeros(Bool, length(Z_dict), length(q_dict)) for (e, v) in X_dict for c in v @@ -1768,12 +2019,12 @@ end Build qubit dictionary. """ function _build_q_dict(faces::Set{_Cell}) - q_dict = Dict{_Cell, Int}() + q_dict = Dict{_Cell,Int}() n = 0 for f in faces n += 1 q_dict[f] = n - end + end return q_dict end @@ -1781,20 +2032,20 @@ end Compute logical operators. """ function _compute_logicals(l::Int, n::Int = 2, d::Int = 4) - Z_logicals = Dict{Vector{Int}, Set{_Cell}}() - X_logicals = Dict{Vector{Int}, Set{_Cell}}() + Z_logicals = Dict{Vector{Int},Set{_Cell}}() + X_logicals = Dict{Vector{Int},Set{_Cell}}() dirs = collect(1:d) coords_to_change = collect(combinations(1:d, n)) for directions in coords_to_change original_face = [] - for c in Iterators.product([0:l - 1 for i in 1:2]...) + for c in Iterators.product([0:(l-1) for i = 1:2]...) z_coord = [0, 0, 0, 0] - for i in 1:length(directions) + for i = 1:length(directions) z_coord[directions[i]] = c[i] end other_directions = setdiff(dirs, directions) - z_new_coords = Vector([copy(z_coord) for _ in 1:2^n - 1]) - for i in 1:2^n - 1, j in 1:n + z_new_coords = Vector([copy(z_coord) for _ = 1:(2^n-1)]) + for i = 1:(2^n-1), j = 1:n (i >> (j - 1)) & 1 == 1 ? z_new_coords[i][directions[j]] += 1 : nothing end vertices = Set{_Vertex}() @@ -1803,22 +2054,26 @@ function _compute_logicals(l::Int, n::Int = 2, d::Int = 4) l > 2 ? new_coord .%= l : nothing push!(vertices, _Vertex(new_coord)) end - haskey(Z_logicals, directions) ? push!(Z_logicals[directions], _Cell(vertices)) : Z_logicals[directions] = Set([_Cell(vertices)]) + haskey(Z_logicals, directions) ? + push!(Z_logicals[directions], _Cell(vertices)) : + Z_logicals[directions] = Set([_Cell(vertices)]) if isempty(original_face) original_face = copy(z_new_coords) push!(original_face, z_coord) end vertices = Set{_Vertex}() new_face = deepcopy(original_face) - for pt in new_face, i in 1:length(other_directions) + for pt in new_face, i = 1:length(other_directions) pt[other_directions[i]] = c[i] end vertices = Set{_Vertex}() for new_coord in new_face l > 2 ? new_coord .%= l : nothing - push!(vertices, _Vertex(new_coord)) + push!(vertices, _Vertex(new_coord)) end - haskey(X_logicals, directions) ? push!(X_logicals[directions], _Cell(vertices)) : X_logicals[directions] = Set([_Cell(vertices)]) + haskey(X_logicals, directions) ? + push!(X_logicals[directions], _Cell(vertices)) : + X_logicals[directions] = Set([_Cell(vertices)]) end end return X_logicals, Z_logicals @@ -1827,7 +2082,7 @@ end """ Get the indices of the redundant stabilizers. """ -function _compute_redundant(redundancy::Dict{_Cell, Set{_Cell}}, re_dict::Dict{_Cell, Int}) +function _compute_redundant(redundancy::Dict{_Cell,Set{_Cell}}, re_dict::Dict{_Cell,Int}) redundant = Vector{Vector{Int}}() for (_, stabs) in redundancy new_v = Vector{Int}() @@ -1862,7 +2117,8 @@ function ToricCode4D(l::Int) volume_dict = _build_q_dict(volumes) edge_dict = _build_q_dict(edges) - X_stabs, Z_stabs = _compute_check_matrices(X_dict, Z_dict, q_dict, edge_dict, volume_dict) + X_stabs, Z_stabs = + _compute_check_matrices(X_dict, Z_dict, q_dict, edge_dict, volume_dict) Z_redundant = _compute_redundant(Z_redundancy, volume_dict) X_redundant = _compute_redundant(X_redundancy, edge_dict) @@ -1877,11 +2133,11 @@ function ToricCode4D(l::Int) Z = zero_matrix(F, size(Z_stabs)[1], size(Z_stabs)[2]) I, J, _ = findnz(X_stabs) - for i in 1:length(I) + for i = 1:length(I) X[I[i], J[i]] = F_one end I, J, _ = findnz(Z_stabs) - for i in 1:length(I) + for i = 1:length(I) Z[I[i], J[i]] = F_one end diff --git a/src/Quantum/product_codes.jl b/src/Quantum/product_codes.jl index bda0bd03..14d0348f 100644 --- a/src/Quantum/product_codes.jl +++ b/src/Quantum/product_codes.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -36,10 +36,15 @@ julia> length(code), dimension(code) (1922, 50) ``` """ -function HypergraphProductCode(A::CTMatrixTypes, B::CTMatrixTypes; char_vec::Union{Vector{zzModRingElem}, - Missing} = missing, logs_alg::Symbol = :stnd_frm) - - logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || throw(ArgumentError("Unrecognized logicals algorithm")) +function HypergraphProductCode( + A::CTMatrixTypes, + B::CTMatrixTypes; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) + + logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || + throw(ArgumentError("Unrecognized logicals algorithm")) F = base_ring(A) F == base_ring(B) || throw(ArgumentError("Matrices need to be over the same base ring")) @@ -52,7 +57,8 @@ function HypergraphProductCode(A::CTMatrixTypes, B::CTMatrixTypes; char_vec::Uni if Int(order(F)) == 2 H_X = hcat(A ⊗ identity_matrix(F, ncols(B)), identity_matrix(F, ncols(A_tr)) ⊗ B_tr) else - H_X = hcat(A ⊗ identity_matrix(F, ncols(B)), -identity_matrix(F, ncols(A_tr)) ⊗ B_tr) + H_X = + hcat(A ⊗ identity_matrix(F, ncols(B)), -identity_matrix(F, ncols(A_tr)) ⊗ B_tr) end H_Z = hcat(identity_matrix(F, ncols(A)) ⊗ B, A_tr ⊗ identity_matrix(F, ncols(B_tr))) n = ncols(H_X) @@ -60,18 +66,20 @@ function HypergraphProductCode(A::CTMatrixTypes, B::CTMatrixTypes; char_vec::Uni stabs_stand, P_stand, stand_r, stand_k, rnk = _standard_form_stabilizer(stabs) if !iszero(stand_k) if logs_alg == :stnd_frm - logs = _make_pairs(_logicals_standard_form(stabs_stand, n, stand_k, stand_r, P_stand)) - logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i in 1:length(logs)]) + logs = _make_pairs( + _logicals_standard_form(stabs_stand, n, stand_k, stand_r, P_stand), + ) + logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i = 1:length(logs)]) else - rnk_H, H = right_kernel(hcat(stabs[:, n + 1:end], -stabs[:, 1:n])) + rnk_H, H = right_kernel(hcat(stabs[:, (n+1):end], -stabs[:, 1:n])) if ncols(H) == rnk_H H_tr = transpose(H) else # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(H) H_tr = zero_matrix(base_ring(H), rnk_H, nr) - for r in 1:nr - for c in 1:rnk_H + for r = 1:nr + for c = 1:rnk_H !iszero(H[r, c]) && (H_tr[c, r] = H[r, c];) end end @@ -94,17 +102,49 @@ function HypergraphProductCode(A::CTMatrixTypes, B::CTMatrixTypes; char_vec::Uni # TODO is this distance formula not correct? # (ismissing(C1.d) || ismissing(C2.d)) ? d = missing : d = minimum([C1.d, C2.d]) X_logs = reduce(vcat, [log[1][:, 1:n] for log in logs]) - Z_logs = reduce(vcat, [log[2][:, n + 1:end] for log in logs]) + Z_logs = reduce(vcat, [log[2][:, (n+1):end] for log in logs]) _, mat = rref(vcat(H_X, X_logs)) anti = _remove_empty(mat, :rows) * transpose(Z_logs) - u_bound_dx, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dx, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) _, mat = rref(vcat(H_Z, Z_logs)) anti = _remove_empty(mat, :rows) * transpose(X_logs) - u_bound_dz, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - return HypergraphProductCode(F, n, k, missing, missing, missing, 1, min(u_bound_dx, - u_bound_dz), 1, u_bound_dx, 1, u_bound_dz, stabs, H_X, H_Z, missing, missing, signs, - X_signs, Z_signs, logs, logs_mat, char_vec, over_comp, stabs_stand, stand_r, stand_k, - P_stand, missing, missing, missing, missing) + u_bound_dz, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + return HypergraphProductCode( + F, + n, + k, + missing, + missing, + missing, + 1, + min(u_bound_dx, u_bound_dz), + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + H_X, + H_Z, + missing, + missing, + signs, + X_signs, + Z_signs, + logs, + logs_mat, + char_vec, + over_comp, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + missing, + missing, + ) end """ @@ -112,10 +152,18 @@ end Return the (symmetric) hypergraph product code of `C`. """ -function HypergraphProductCode(C::AbstractLinearCode; char_vec::Union{Vector{zzModRingElem}, Missing} = - missing, logs_alg::Symbol = :stnd_frm) - - S = HypergraphProductCode(parity_check_matrix(C), parity_check_matrix(C), char_vec = char_vec, logs_alg = logs_alg) +function HypergraphProductCode( + C::AbstractLinearCode; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) + + S = HypergraphProductCode( + parity_check_matrix(C), + parity_check_matrix(C), + char_vec = char_vec, + logs_alg = logs_alg, + ) S.C1 = C S.C2 = C ismissing(C.d) || set_minimum_distance!(S, C.d) @@ -127,15 +175,23 @@ end Return the hypergraph product code of `C1` and `C2`. """ -function HypergraphProductCode(C1::AbstractLinearCode, C2::AbstractLinearCode; - char_vec::Union{Vector{zzModRingElem}, Missing} = missing, logs_alg::Symbol = :stnd_frm) - - S = HypergraphProductCode(parity_check_matrix(C1), parity_check_matrix(C2), char_vec = - char_vec, logs_alg = logs_alg) +function HypergraphProductCode( + C1::AbstractLinearCode, + C2::AbstractLinearCode; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) + + S = HypergraphProductCode( + parity_check_matrix(C1), + parity_check_matrix(C2), + char_vec = char_vec, + logs_alg = logs_alg, + ) S.C1 = C1 S.C2 = C2 (ismissing(C1.d) || ismissing(C2.d)) ? (S.d = missing;) : - (set_minimum_distance!(S, min(C1.d, C2.d));) + (set_minimum_distance!(S, min(C1.d, C2.d));) return S end @@ -146,25 +202,37 @@ end Return the generalized Shor code of `C1` and `C2` with `C1⟂ ⊆ C2`. """ -function GeneralizedShorCode(C1::AbstractLinearCode, C2::AbstractLinearCode; - char_vec::Union{Vector{zzModRingElem}, Missing} = missing, logs_alg::Symbol = :stnd_frm) - - logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || throw(ArgumentError("Unrecognized logicals algorithm")) - Int(order(C1.F)) == 2 || error("Generalized Shor codes are only defined for binary codes.") - Int(order(C2.F)) == 2 || error("Generalized Shor codes are only defined for binary codes.") - dual(C1) ⊆ C2 || error("Generalized Shor codes require the dual of the first code is a subset of the second.") +function GeneralizedShorCode( + C1::AbstractLinearCode, + C2::AbstractLinearCode; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) + + logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || + throw(ArgumentError("Unrecognized logicals algorithm")) + Int(order(C1.F)) == 2 || + error("Generalized Shor codes are only defined for binary codes.") + Int(order(C2.F)) == 2 || + error("Generalized Shor codes are only defined for binary codes.") + dual(C1) ⊆ C2 || error( + "Generalized Shor codes require the dual of the first code is a subset of the second.", + ) # H_X stays sparse if H1 is but H_Z does not if C1.d is large H_X = parity_check_matrix(C1) ⊗ identity_matrix(C2.F, C2.n) H_Z = generator_matrix(C1) ⊗ parity_check_matrix(C2) S = CSSCode(H_X, H_Z, char_vec = char_vec, logs_alg = logs_alg) (ismissing(C1.d) || ismissing(C2.d)) ? (S.d = missing;) : - (set_minimum_distance!(S, min(C1.d, C2.d));) + (set_minimum_distance!(S, min(C1.d, C2.d));) return S end -BaconCasaccinoConstruction(C1::AbstractLinearCode, C2::AbstractLinearCode, - char_vec::Union{Vector{zzModRingElem}, Missing} = missing, logs_alg::Symbol = :stnd_frm) = - GeneralizedShorCode(C1, C2, char_vec = char_vec, logs_alg = logs_alg) +BaconCasaccinoConstruction( + C1::AbstractLinearCode, + C2::AbstractLinearCode, + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) = GeneralizedShorCode(C1, C2, char_vec = char_vec, logs_alg = logs_alg) """ HyperBicycleCodeCSS(a::Vector{CTMatrixTypes}, b::Vector{CTMatrixTypes}, χ::Int; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, logs_alg::Symbol = :stnd_frm) @@ -182,6 +250,8 @@ Return the hyperbicycle CSS code of `a` and `b` given `χ`. [[900, 50, 14]] CSS Hyperbicycle Code from Example 6 of [Kovalev_2013](@cite). ```jldoctest +julia> using CodingTheory, Oscar; + julia> S, x = polynomial_ring(Oscar.Nemo.Native.GF(2), :x); julia> l = 30; χ = 1; @@ -202,23 +272,35 @@ julia> length(code), dimension(code) (900, 50) ``` """ -function HyperBicycleCodeCSS(a::Vector{T}, b::Vector{T}, χ::Int; char_vec::Union{Vector{zzModRingElem}, - Missing} = missing, logs_alg::Symbol = :stnd_frm) where T <: CTMatrixTypes - - logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || throw(ArgumentError("Unrecognized logicals algorithm")) +function HyperBicycleCodeCSS( + a::Vector{T}, + b::Vector{T}, + χ::Int; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:CTMatrixTypes} + + logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || + throw(ArgumentError("Unrecognized logicals algorithm")) χ > 0 || throw(ArgumentError("Required χ > 0.")) c = length(a) - gcd(c, χ) == 1 || throw(ArgumentError("The length of the input vectors must be coprime with χ.")) + gcd(c, χ) == 1 || + throw(ArgumentError("The length of the input vectors must be coprime with χ.")) c == length(b) || throw(ArgumentError("Input vectors must have same length.")) k1, n1 = size(a[1]) k2, n2 = size(b[1]) F = base_ring(a[1]) Int(order(F)) == 2 || throw(ArgumentError("Hyperbicycle codes require binary inputs.")) - for i in 1:c - F == base_ring(a[i]) || throw(ArgumentError("Inputs must share the same base ring.")) - (k1, n1) == size(a[i]) || throw(ArgumentError("First set of matrices must all have the same dimensions.")) - F == base_ring(b[i]) || throw(ArgumentError("Inputs must share the same base ring.")) - (k2, n2) == size(b[i]) || throw(ArgumentError("Second set of matrices must all have the same dimensions.")) + for i = 1:c + F == base_ring(a[i]) || + throw(ArgumentError("Inputs must share the same base ring.")) + (k1, n1) == size(a[i]) || + throw(ArgumentError("First set of matrices must all have the same dimensions.")) + F == base_ring(b[i]) || + throw(ArgumentError("Inputs must share the same base ring.")) + (k2, n2) == size(b[i]) || throw( + ArgumentError("Second set of matrices must all have the same dimensions."), + ) end H1 = zero_matrix(F, c * k1, c * n1) @@ -226,9 +308,9 @@ function HyperBicycleCodeCSS(a::Vector{T}, b::Vector{T}, χ::Int; char_vec::Unio HT1 = zero_matrix(F, c * n1, c * k1) HT2 = zero_matrix(F, c * n2, c * k2) Ic = identity_matrix(F, c) - Sχ = Ic[mod1.(1:χ:c * χ, c), :] - for i in 1:c - Ii = vcat(Ic[i:end, :], Ic[1:i - 1, :]) + Sχ = Ic[mod1.(1:χ:(c*χ), c), :] + for i = 1:c + Ii = vcat(Ic[i:end, :], Ic[1:(i-1), :]) Iχi = Sχ * Ii ITχi = transpose(Sχ) * transpose(Ii) H1 += Iχi ⊗ a[i] @@ -281,23 +363,35 @@ julia> length(code), dimension(code) (289, 81) ``` """ -function HyperBicycleCode(a::Vector{T}, b::Vector{T}, χ::Int, char_vec::Union{Vector{zzModRingElem}, - Missing} = missing, logs_alg::Symbol = :stnd_frm) where T <: CTMatrixTypes - - logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || throw(ArgumentError("Unrecognized logicals algorithm")) +function HyperBicycleCode( + a::Vector{T}, + b::Vector{T}, + χ::Int, + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:CTMatrixTypes} + + logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || + throw(ArgumentError("Unrecognized logicals algorithm")) χ > 0 || throw(ArgumentError("Required χ > 0.")) c = length(a) - gcd(c, χ) == 1 || throw(ArgumentError("The length of the input vectors must be coprime with χ.")) + gcd(c, χ) == 1 || + throw(ArgumentError("The length of the input vectors must be coprime with χ.")) c == length(b) || throw(ArgumentError("Input vectors must have same length.")) k1, n1 = size(a[1]) k2, n2 = size(b[1]) F = base_ring(a[1]) Int(order(F)) == 2 || throw(ArgumentError("Hyperbicycle codes require binary inputs.")) - for i in 1:c - F == base_ring(a[i]) || throw(ArgumentError("Inputs must share the same base ring.")) - (k1, n1) == size(a[i]) || throw(ArgumentError("First set of matrices must all have the same dimensions.")) - F == base_ring(b[i]) || throw(ArgumentError("Inputs must share the same base ring.")) - (k2, n2) == size(b[i]) || throw(ArgumentError("Second set of matrices must all have the same dimensions.")) + for i = 1:c + F == base_ring(a[i]) || + throw(ArgumentError("Inputs must share the same base ring.")) + (k1, n1) == size(a[i]) || + throw(ArgumentError("First set of matrices must all have the same dimensions.")) + F == base_ring(b[i]) || + throw(ArgumentError("Inputs must share the same base ring.")) + (k2, n2) == size(b[i]) || throw( + ArgumentError("Second set of matrices must all have the same dimensions."), + ) end H1 = zero_matrix(F, c * k1, c * n1) @@ -305,9 +399,9 @@ function HyperBicycleCode(a::Vector{T}, b::Vector{T}, χ::Int, char_vec::Union{V HT1 = zero_matrix(F, c * n1, c * k1) HT2 = zero_matrix(F, c * n2, c * k2) Ic = identity_matrix(F, c) - Sχ = Ic[mod1.(1:χ:c * χ, c), :] - for i in 1:c - Ii = vcat(Ic[i:end, :], Ic[1:i - 1, :]) + Sχ = Ic[mod1.(1:χ:(c*χ), c), :] + for i = 1:c + Ii = vcat(Ic[i:end, :], Ic[1:(i-1), :]) Iχi = Sχ * Ii ITχi = transpose(Sχ) * transpose(Ii) H1 += Iχi ⊗ a[i] @@ -355,10 +449,15 @@ julia> length(code), dimension(code) (254, 28) ``` """ -function GeneralizedBicycleCode(A::T, B::T; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) where T <: CTMatrixTypes - - logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || throw(ArgumentError("Unrecognized logicals algorithm")) +function GeneralizedBicycleCode( + A::T, + B::T; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:CTMatrixTypes} + + logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || + throw(ArgumentError("Unrecognized logicals algorithm")) F = base_ring(A) F == base_ring(B) || throw(ArgumentError("Arguments must be over the same base ring.")) (iszero(A) || iszero(B)) && throw(ArgumentError("Arguments should not be zero.")) @@ -367,7 +466,9 @@ function GeneralizedBicycleCode(A::T, B::T; char_vec::Union{Vector{zzModRingElem H_X = hcat(A, B) # branch for speedup - H_Z = Int(order(F)) == 2 ? hcat(transpose(B), transpose(A)) : hcat(transpose(B), -transpose(A)) + H_Z = + Int(order(F)) == 2 ? hcat(transpose(B), transpose(A)) : + hcat(transpose(B), -transpose(A)) return CSSCode(H_X, H_Z, char_vec = char_vec, logs_alg = logs_alg) end @@ -380,14 +481,24 @@ Return the generealized bicycle code determined by `a` and `b`. - `l x l` circulant matrices are constructed using the coefficients of the polynomials `a` and `b` in `F_q[x]/(x^l - 1)` (`gcd(q, l) = 1`) as the first column """ -function GeneralizedBicycleCode(a::T, b::T; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) where T <: ResElem - - logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || throw(ArgumentError("Unrecognized logicals algorithm")) - parent(a) == parent(b) || throw(ArgumentError("Both objects must be defined over the same residue ring.")) - - return GeneralizedBicycleCode(residue_polynomial_to_circulant_matrix(a), - residue_polynomial_to_circulant_matrix(b), char_vec = char_vec, logs_alg = logs_alg) +function GeneralizedBicycleCode( + a::T, + b::T; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:ResElem} + + logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || + throw(ArgumentError("Unrecognized logicals algorithm")) + parent(a) == parent(b) || + throw(ArgumentError("Both objects must be defined over the same residue ring.")) + + return GeneralizedBicycleCode( + residue_polynomial_to_circulant_matrix(a), + residue_polynomial_to_circulant_matrix(b), + char_vec = char_vec, + logs_alg = logs_alg, + ) end """ @@ -398,14 +509,24 @@ Return the generealized bicycle code determined by `a` and `b`. # Notes - `|G| x |G|` circulant matrices are constructed using the coefficients of the elements in the group algebra `FG` as` the first column """ -function GeneralizedBicycleCode(a::T, b::T; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) where T <: CTGroupAlgebra - - logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || throw(ArgumentError("Unrecognized logicals algorithm")) - parent(a) == parent(b) || throw(ArgumentError("Both objects must be defined over the same residue ring.")) - - return GeneralizedBicycleCode(group_algebra_element_to_circulant_matrix(a), - group_algebra_element_to_circulant_matrix(b), char_vec = char_vec, logs_alg = logs_alg) +function GeneralizedBicycleCode( + a::T, + b::T; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:CTGroupAlgebra} + + logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || + throw(ArgumentError("Unrecognized logicals algorithm")) + parent(a) == parent(b) || + throw(ArgumentError("Both objects must be defined over the same residue ring.")) + + return GeneralizedBicycleCode( + group_algebra_element_to_circulant_matrix(a), + group_algebra_element_to_circulant_matrix(b), + char_vec = char_vec, + logs_alg = logs_alg, + ) end # function BicycleCode(A::fq_nmot_mat) @@ -416,7 +537,7 @@ end # H = hcat(A, transpose(A)) # return CSSCode(H, H) # end - + """ generalized_hypergraph_product_matrices(A::MatElem{T}, b::T) where T <: ResElem GHGP_matrices(A::MatElem{T}, b::T) where T <: ResElem @@ -424,6 +545,9 @@ end Return the pre-lifted matrices `H_X` and `H_Z` of the generalized hypergraph product code of `A` and `b`. +!!! note + Commutativity of `A` and `B` required but not yet enforced. + # Arguments - `A` - an `m x n` matrix with elements in `F_2[x]/(x^m - 1)` - `b` - a polynomial over the same residue ring @@ -431,21 +555,20 @@ Return the pre-lifted matrices `H_X` and `H_Z` of the generalized hypergraph pro # Notes - Use `LiftedProductCode` to return a quantum code over the base ring directly. """ -function generalized_hypergraph_product_matrices(A::MatElem{T}, b::T) where T <: ResElem - - @warn "Commutativity of A and b required but not yet enforced." +function generalized_hypergraph_product_matrices(A::MatElem{T}, b::T) where {T<:ResElem} S = base_ring(b) F = base_ring(S) # Int(order(F)) == 2 || throw(ArgumentError("The generalized hypergraph product is only defined over GF(2).")) R = parent(A[1, 1]) - R == parent(b) || throw(ArgumentError("Both objects must be defined over the same residue ring.")) + R == parent(b) || + throw(ArgumentError("Both objects must be defined over the same residue ring.")) m, n = size(A) (m != 1 && n != 1) || throw(ArgumentError("First input matrix must not be a vector.")) f = modulus(R) l = degree(f) f == gen(S)^l - 1 || throw(ArgumentError("Residue ring not of the form x^l - 1.")) # gcd(l, Int(characteristic(F))) == 1 || throw(ArgumentError("Residue ring over F_q[x] must be defined by x^l - 1 with gcd(l, q) = 1.")) - + A_tr = _CT_adjoint(A) # b_coeffs = collect(coefficients(Nemo.lift(b))) # for _ in 1:l - length(b_coeffs) @@ -466,9 +589,9 @@ function generalized_hypergraph_product_matrices(A::MatElem{T}, b::T) where T <: end return H_X, H_Z end -GHGP_matrices(A::MatElem{T}, b::T) where T <: ResElem = +GHGP_matrices(A::MatElem{T}, b::T) where {T<:ResElem} = generalized_hypergraph_product_matrices(A, b) -lifted_product_matrices(A::MatElem{T}, b::T) where T <: ResElem = +lifted_product_matrices(A::MatElem{T}, b::T) where {T<:ResElem} = generalized_hypergraph_product_matrices(A, b) """ @@ -485,7 +608,10 @@ Return the pre-lifted matrices `H_X` and `H_Z` of the generalized hypergraph pro # Notes - Use `LiftedProductCode` to return a quantum code over the base ring directly. """ -function generalized_hypergraph_product_matrices(A::MatElem{T}, b::T) where T <: CTGroupAlgebra +function generalized_hypergraph_product_matrices( + A::MatElem{T}, + b::T, +) where {T<:CTGroupAlgebra} FG = parent(A[1, 1]) parent(b) == FG || throw(ArgumentError("Inputs must be over the same group algebra")) @@ -505,9 +631,9 @@ function generalized_hypergraph_product_matrices(A::MatElem{T}, b::T) where T <: end return H_X, H_Z end -GHGP_matrices(A::MatElem{T}, b::T) where T <: CTGroupAlgebra = +GHGP_matrices(A::MatElem{T}, b::T) where {T<:CTGroupAlgebra} = generalized_hypergraph_product_matrices(A, b) -lifted_product_matrices(A::MatElem{T}, b::T) where T <: CTGroupAlgebra = +lifted_product_matrices(A::MatElem{T}, b::T) where {T<:CTGroupAlgebra} = generalized_hypergraph_product_matrices(A, b) """ @@ -521,14 +647,22 @@ Return the lifted (generalized hypergraph) product code of `A` and `b`. - `A` - either an `m x n` matrix with elements in `F_2[x]/(x^m - 1)` or a group algebra - `b` - a polynomial over the same residue ring or group algebra """ -function GeneralizedHypergraphProductCode(A::MatElem{T}, b::T; char_vec::Union{Vector{zzModRingElem}, - Missing} = missing, logs_alg::Symbol = :stnd_frm) where T <: Union{ResElem, CTGroupAlgebra} +function GeneralizedHypergraphProductCode( + A::MatElem{T}, + b::T; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:Union{ResElem,CTGroupAlgebra}} H_X, H_Z = generalized_hypergraph_product_matrices(A, b) return CSSCode(lift(H_X), lift(H_Z), char_vec = char_vec, logs_alg = logs_alg) end -LiftedProductCode(A::MatElem{T}, b::T; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) where T <: ResElem = +LiftedProductCode( + A::MatElem{T}, + b::T; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:ResElem} = GeneralizedHypergraphProductCode(A, b, char_vec = char_vec, logs_alg = logs_alg) """ @@ -536,6 +670,8 @@ LiftedProductCode(A::MatElem{T}, b::T; char_vec::Union{Vector{zzModRingElem}, Mi Return the pre-lifted matrices `H_X` and `H_Z` for the lifted quasi-cyclic lifted product code. +!!! note + Commutativity of `A` and `B` required but not yet enforced. # Arguments - `A` - an `m x n1` matrix with elements in `F_2[x]/(x^m - 1)` - `B` - an `m x n2` matrix with elements in the same residue ring @@ -543,17 +679,18 @@ Return the pre-lifted matrices `H_X` and `H_Z` for the lifted quasi-cyclic lifte # Notes - Use `LiftedProductCode` to return a quantum code over the base ring directly. """ -function lifted_product_matrices(A::MatElem{T}, B::MatElem{T}) where T <: ResElem - @warn "Commutativity of A and b required but not yet enforced." +function lifted_product_matrices(A::MatElem{T}, B::MatElem{T}) where {T<:ResElem} S = base_ring(A[1, 1]) F = base_ring(S) - Int(order(F)) == 2 || throw(ArgumentError("The quasi-cyclic lifted product is only defined over GF(2).")) + Int(order(F)) == 2 || + throw(ArgumentError("The quasi-cyclic lifted product is only defined over GF(2).")) R = parent(A[1, 1]) - R == parent(B[1, 1]) || throw(ArgumentError("Both objects must be defined over the same residue ring.")) + R == parent(B[1, 1]) || + throw(ArgumentError("Both objects must be defined over the same residue ring.")) f = modulus(R) l = degree(f) f == gen(S)^l - 1 || throw(ArgumentError("Residue ring not of the form x^l - 1.")) - + A_tr = _CT_adjoint(A) B_tr = _CT_adjoint(B) @@ -581,9 +718,10 @@ Return the pre-lifted matrices `H_X` and `H_Z` for the lifted quasi-cyclic lifte # Notes - Use `LiftedProductCode` to return a quantum code over the base ring directly. """ -function lifted_product_matrices(A::MatElem{T}, B::MatElem{T}) where T <: CTGroupAlgebra +function lifted_product_matrices(A::MatElem{T}, B::MatElem{T}) where {T<:CTGroupAlgebra} FG = parent(A[1, 1]) - parent(B[1, 1]) == FG || throw(ArgumentError("Inputs must be over the same group algebra")) + parent(B[1, 1]) == FG || + throw(ArgumentError("Inputs must be over the same group algebra")) A_tr = _CT_adjoint(A) B_tr = _CT_adjoint(B) @@ -632,15 +770,17 @@ julia> A = matrix(R, 7, 7, julia> b = R(1 + x + x^6); julia> code = LiftedProductCode(A, b); -┌ Warning: Commutativity of A and b required but not yet enforced. -└ @ CodingTheory ~/Documents/GitHub/CodingTheory/src/Quantum/product_codes.jl:340 julia> length(code), dimension(code) (882, 24) ``` """ -function LiftedProductCode(A::MatElem{T}, B::MatElem{T}; char_vec::Union{Vector{zzModRingElem}, Missing} = - missing, logs_alg::Symbol = :stnd_frm) where T <: Union{ResElem, CTGroupAlgebra} +function LiftedProductCode( + A::MatElem{T}, + B::MatElem{T}; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:Union{ResElem,CTGroupAlgebra}} H_X, H_Z = lifted_product_matrices(A, B) return CSSCode(lift(H_X), lift(H_Z), char_vec = char_vec, logs_alg = logs_alg) @@ -651,6 +791,9 @@ end Return the pre-lifted stabilizer matrix for bias-tailored lifted product code of `A` and `B`. + +!!! note + Commutativity of `A` and `B` required but not yet enforced. # Arguments - `A` - an `m x n1` matrix with elements in `F_2[x]/(x^m - 1)` - `B` - an `m x n2` matrix with elements in the same residue ring @@ -658,17 +801,21 @@ Return the pre-lifted stabilizer matrix for bias-tailored lifted product code of # Notes - Use `BiasTailoredLiftedProductCode` to return a quantum code over the base ring directly. """ -function bias_tailored_lifted_product_matrices(A::MatElem{T}, B::MatElem{T}) where T <: ResElem - @warn "Commutativity of A and b required but not yet enforced." +function bias_tailored_lifted_product_matrices( + A::MatElem{T}, + B::MatElem{T}, +) where {T<:ResElem} S = base_ring(A[1, 1]) F = base_ring(S) - Int(order(F)) == 2 || throw(ArgumentError("The quasi-cyclic lifted product is only defined over GF(2).")) + Int(order(F)) == 2 || + throw(ArgumentError("The quasi-cyclic lifted product is only defined over GF(2).")) R = parent(A[1, 1]) - R == parent(B[1, 1]) || throw(ArgumentError("Both objects must be defined over the same residue ring.")) + R == parent(B[1, 1]) || + throw(ArgumentError("Both objects must be defined over the same residue ring.")) f = modulus(R) l = degree(f) f == gen(S)^l - 1 || throw(ArgumentError("Residue ring not of the form x^l - 1.")) - + A_tr = _CT_adjoint(A) B_tr = _CT_adjoint(B) @@ -725,17 +872,19 @@ julia> A2 = matrix(R, 7, 7, 0 , 0 , 0 , 0 , 1 , x^9 , x^36]); julia> code = BiasTailoredLiftedProductCode(A1, A2); -┌ Warning: Commutativity of A and b required but not yet enforced. -└ @ CodingTheory ~/Documents/GitHub/CodingTheory/src/Quantum/product_codes.jl:60 julia> length(code), dimension(code) (882, 24) ``` """ -function bias_tailored_lifted_product_matrices(A::MatElem{T}, B::MatElem{T}) where T <: CTGroupAlgebra +function bias_tailored_lifted_product_matrices( + A::MatElem{T}, + B::MatElem{T}, +) where {T<:CTGroupAlgebra} FG = parent(A[1, 1]) - parent(B[1, 1]) == FG || throw(ArgumentError("Inputs must be over the same group algebra")) + parent(B[1, 1]) == FG || + throw(ArgumentError("Inputs must be over the same group algebra")) A_tr = _CT_adjoint(A) B_tr = _CT_adjoint(B) @@ -763,8 +912,12 @@ Return the bias-tailored lifted product code of `A` and `B`. - `A` - either an `m x n` matrix with elements in `F_2[x]/(x^m - 1)` or a group algebra - `B` - an `m x n2` matrix with elements in the same parent as `A` """ -function BiasTailoredLiftedProductCode(A::MatElem{T}, B::MatElem{T}; char_vec::Union{Vector{zzModRingElem}, - Missing} = missing, logs_alg::Symbol = :stnd_frm) where T <: Union{ResElem, CTGroupAlgebra} +function BiasTailoredLiftedProductCode( + A::MatElem{T}, + B::MatElem{T}; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:Union{ResElem,CTGroupAlgebra}} stabs = bias_tailored_lifted_product_matrices(A, B) return StabilizerCode(lift(stabs), char_vec = char_vec, logs_alg = logs_alg) @@ -810,8 +963,8 @@ julia> length(code), dimension(code) """ function SPCDFoldProductCode(D::Int, s::Int = 1) vec_S = Vector{AbstractStabilizerCode}() - for i in 1:D - for l in 1:D + for i = 1:D + for l = 1:D if l == (i - 1) * D + i # RepetitionCode(2, x) is dual(SPCCode(2, x)) push!(vec_S, CSSCode(RepetitionCode(2, 2 * s))) @@ -820,7 +973,7 @@ function SPCDFoldProductCode(D::Int, s::Int = 1) end end end - + S = symmetric_product(vec_S) set_X_minimum_distance!(S, 2^D) set_Z_minimum_distance!(S, 2^D) @@ -831,15 +984,15 @@ end SingleParityCheckDFoldProductCode(D::Int, s::Int = 1) = SPCDFoldProductCode(D, s) ############################# - # getter functions +# getter functions ############################# ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# """ @@ -869,8 +1022,8 @@ function Quintavalle_basis(C::HypergraphProductCode) tr_ker_H2 = transpose(ker_H2) tr_ker_H1 = transpose(ker_H1) tr_im_H2_tr_c = transpose(im_H2_tr_c) - for i in 1:nrows(tr_ker_H1) - for h in 1:nrows(tr_ker_H2) + for i = 1:nrows(tr_ker_H1) + for h = 1:nrows(tr_ker_H2) lx[l:l, :] = hcat(tr_im_H1_tr_c[i:i, :] ⊗ tr_ker_H2[h:h, :], temp) lz[l:l, :] = hcat(tr_ker_H1[i:i, :] ⊗ tr_im_H2_tr_c[h:h, :], temp) l += 1 @@ -882,8 +1035,8 @@ function Quintavalle_basis(C::HypergraphProductCode) tr_im_H2_c = transpose(im_H2_c) tr_im_H1_c = transpose(im_H1_c) tr_ker_H2_tr = transpose(ker_H2_tr) - for i in 1:nrows(tr_ker_H1_tr) - for h in 1:nrows(tr_ker_H2_tr) + for i = 1:nrows(tr_ker_H1_tr) + for h = 1:nrows(tr_ker_H2_tr) lx[l:l, :] = hcat(temp, tr_ker_H1_tr[i:i, :] ⊗ tr_im_H2_c[h:h, :]) lz[l:l, :] = hcat(temp, tr_im_H1_c[i:i, :] ⊗ tr_ker_H2_tr[h:h, :]) l += 1 @@ -902,11 +1055,14 @@ Return the asymmetric 2-fold product quantum CSS code of the CSS codes `S1` and # Note - This is defined in https://arxiv.org/abs/2209.13474 """ -asymmetric_product(S1::T, S2::T) where {T <: AbstractSubsystemCode} = asymmetric_product( - CSSTrait(T), S1, S2) +asymmetric_product(S1::T, S2::T) where {T<:AbstractSubsystemCode} = + asymmetric_product(CSSTrait(T), S1, S2) function asymmetric_product(::IsCSS, S1::AbstractSubsystemCode, S2::AbstractSubsystemCode) # TODO: check fields are the same or convertable - H_X = vcat(S1.X_stabs ⊗ identity_matrix(S1.F, S2.n), identity_matrix(S1.F, S1.n) ⊗ S2.X_stabs) + H_X = vcat( + S1.X_stabs ⊗ identity_matrix(S1.F, S2.n), + identity_matrix(S1.F, S1.n) ⊗ S2.X_stabs, + ) H_Z = S1.Z_stabs ⊗ S2.Z_stabs return CSSCode(H_X, H_Z) end @@ -922,7 +1078,7 @@ the square-root of the length of the vector of CSS codes `vec_S`. # Note - This is defined in https://arxiv.org/abs/2209.13474 """ -function symmetric_product(vec_S::Vector{T}) where {T <: AbstractSubsystemCode} +function symmetric_product(vec_S::Vector{T}) where {T<:AbstractSubsystemCode} isempty(vec_S) && throw(ArgumentError("Input vector of CSS codes cannot be empty")) for S in vec_S if CSSTrait(typeof(S)) == IsNotCSS() @@ -931,20 +1087,22 @@ function symmetric_product(vec_S::Vector{T}) where {T <: AbstractSubsystemCode} end return symmetric_product(IsCSS(), vec_S) end -function symmetric_product(::IsCSS, vec_S::Vector{T}) where {T <: AbstractSubsystemCode} +function symmetric_product(::IsCSS, vec_S::Vector{T}) where {T<:AbstractSubsystemCode} # TODO: check fields are the same or convertable - length(vec_S) >= 4 || throw(DomainError("The length of the input vector must be at least 4")) + length(vec_S) >= 4 || + throw(DomainError("The length of the input vector must be at least 4")) D = sqrt(length(vec_S)) - isinteger(D) ? (D = Int(D);) : throw(ArgumentError("The number of CSS codes must be D^2")) + isinteger(D) ? (D = Int(D);) : + throw(ArgumentError("The number of CSS codes must be D^2")) # since the sizes of the identities are different for every entry, # there's not too much of a better way to do this F = vec_S[1].F # X stabilizers H_X = nothing - for j in 0:D - 1 + for j = 0:(D-1) temp_row = nothing - for l in 1:D^2 + for l = 1:(D^2) if j * D + 1 <= l <= (j + 1) * D if l == 1 temp_row = vec_S[l].X_stabs @@ -968,9 +1126,9 @@ function symmetric_product(::IsCSS, vec_S::Vector{T}) where {T <: AbstractSubsys # Z stabilizers H_Z = nothing - for j in 0:D - 1 + for j = 0:(D-1) temp_row = nothing - for l in 1:D^2 + for l = 1:(D^2) if (l - 1) % D == j if l == 1 temp_row = vec_S[l].Z_stabs @@ -991,10 +1149,10 @@ function symmetric_product(::IsCSS, vec_S::Vector{T}) where {T <: AbstractSubsys H_Z = vcat(H_Z, temp_row) end end - + return CSSCode(H_X, H_Z) end -symmetric_product(::IsNotCSS, vec_S::Vector{T}) where {T <: AbstractSubsystemCode} = +symmetric_product(::IsNotCSS, vec_S::Vector{T}) where {T<:AbstractSubsystemCode} = error("Only valid for CSS codes.") # has this been extended to subsystem codes? @@ -1005,36 +1163,54 @@ symmetric_product(::IsNotCSS, vec_S::Vector{T}) where {T <: AbstractSubsystemCod # Note - This is the single-sector homological product. Use ⊗ for the more general product. """ -function homological_product(S1::AbstractStabilizerCode, S2::AbstractStabilizerCode, - U::CTMatrixTypes = identity_matrix(S1.F, S1.n), V::CTMatrixTypes = identity_matrix(S2.F, S2.n)) +function homological_product( + S1::AbstractStabilizerCode, + S2::AbstractStabilizerCode, + U::CTMatrixTypes = identity_matrix(S1.F, S1.n), + V::CTMatrixTypes = identity_matrix(S2.F, S2.n), +) return homological_product(CSSTrait(typeof(S1)), CSSTrait(typeof(S2)), S1, S2, U, V) end -function homological_product(::IsCSS, ::IsCSS, S1::AbstractStabilizerCode, S2::AbstractStabilizerCode, U::CTMatrixTypes, V::CTMatrixTypes) +function homological_product( + ::IsCSS, + ::IsCSS, + S1::AbstractStabilizerCode, + S2::AbstractStabilizerCode, + U::CTMatrixTypes, + V::CTMatrixTypes, +) num_stabs1 = num_X_stabs(S1) - num_stabs1 == num_Z_stabs(S1) || throw(ArgumentError("The first code didn't have the same number of X and Z stabilizers")) + num_stabs1 == num_Z_stabs(S1) || throw( + ArgumentError("The first code didn't have the same number of X and Z stabilizers"), + ) num_stabs2 = num_X_stabs(S2) - num_stabs2 == num_Z_stabs(S2) || throw(ArgumentError("The second code didn't have the same number of X and Z stabilizers")) - nrows(U) == ncols(U) == S1.n || throw(ArgumentError("U is the wrong size for the code S1")) - nrows(V) == ncols(V) == S2.n || throw(ArgumentError("V is the wrong size for the code S2")) + num_stabs2 == num_Z_stabs(S2) || throw( + ArgumentError("The second code didn't have the same number of X and Z stabilizers"), + ) + nrows(U) == ncols(U) == S1.n || + throw(ArgumentError("U is the wrong size for the code S1")) + nrows(V) == ncols(V) == S2.n || + throw(ArgumentError("V is the wrong size for the code S2")) isinvertible(U) || throw(ArgumentError("U must be invertible")) isinvertible(V) || throw(ArgumentError("V must be invertible")) F = S1.F - F == S2.F == base_ring(U) == base_ring(V) || throw(ArgumentError("S1, S2, U, and V should all have the same base ring")) + F == S2.F == base_ring(U) == base_ring(V) || + throw(ArgumentError("S1, S2, U, and V should all have the same base ring")) δ1 = zero_matrix(F, S1.n, S1.n) - for i in 1:num_stabs1 - for j in 1:num_stabs1 + for i = 1:num_stabs1 + for j = 1:num_stabs1 # TODO are X and Z in the correct order here? δ1 += U[i, j] * transpose(S1.Z_stabs[i, :]) * S1.X_stabs[j, :] end end δ2 = zero_matrix(F, S2.n, S2.n) - for i in 1:num_stabs2 - for j in 1:num_stabs2 + for i = 1:num_stabs2 + for j = 1:num_stabs2 # TODO are X and Z in the correct order here? δ2 += V[i, j] * transpose(S2.Z_stabs[i, :]) * S2.X_stabs[j, :] end @@ -1046,12 +1222,30 @@ function homological_product(::IsCSS, ::IsCSS, S1::AbstractStabilizerCode, S2::A return CSSCode(∂, transpose(∂)) end -homological_product(::IsNotCSS, ::IsNotCSS, S1::AbstractStabilizerCode, S2::AbstractStabilizerCode, - U, V) = throw(ArgumentError("This is only defined for CSS codes")) -homological_product(::IsNotCSS, ::IsCSS, S1::AbstractStabilizerCode, S2::AbstractStabilizerCode, U, - V) = throw(ArgumentError("This is only defined for CSS codes")) -homological_product(::IsCSS, ::IsNotCSS, S1::AbstractStabilizerCode, S2::AbstractStabilizerCode, U, - V) = throw(ArgumentError("This is only defined for CSS codes")) +homological_product( + ::IsNotCSS, + ::IsNotCSS, + S1::AbstractStabilizerCode, + S2::AbstractStabilizerCode, + U, + V, +) = throw(ArgumentError("This is only defined for CSS codes")) +homological_product( + ::IsNotCSS, + ::IsCSS, + S1::AbstractStabilizerCode, + S2::AbstractStabilizerCode, + U, + V, +) = throw(ArgumentError("This is only defined for CSS codes")) +homological_product( + ::IsCSS, + ::IsNotCSS, + S1::AbstractStabilizerCode, + S2::AbstractStabilizerCode, + U, + V, +) = throw(ArgumentError("This is only defined for CSS codes")) @doc (@doc homological_product) ⊠(S1::AbstractStabilizerCode, S2::AbstractStabilizerCode) = homological_product(S1, S2) @@ -1059,7 +1253,7 @@ function _rand_single_sector_boundary(n::Int, k::Int) num_stabs = divexact(n - k, 2) U = _rand_invertible_matrix(GF(2), n) d0 = zero_matrix(GF(2), n, n) - d0[k + 1:k + num_stabs, k + num_stabs + 1:end] = identity_matrix(GF(2), num_stabs) + d0[(k+1):(k+num_stabs), (k+num_stabs+1):end] = identity_matrix(GF(2), num_stabs) return U * d0 * inv(U) end @@ -1111,12 +1305,17 @@ julia> length(code), dimension(code) (360, 12) ``` """ -function BivariateBicycleCode(a::T, b::T) where T <: Union{MPolyQuoRingElem{FqMPolyRingElem}, MPolyQuoRingElem{fpMPolyRingElem}} +function BivariateBicycleCode( + a::T, + b::T, +) where {T<:Union{MPolyQuoRingElem{FqMPolyRingElem},MPolyQuoRingElem{fpMPolyRingElem}}} R = parent(a) R == parent(b) || throw(DomainError("Polynomials must have the same parent.")) F = base_ring(base_ring(a)) - order(F) == 2 || throw(DomainError("This code family is currently only defined over binary fields.")) - length(symbols(parent(a))) == 2 || throw(DomainError("Polynomials must be over two variables.")) + order(F) == 2 || + throw(DomainError("This code family is currently only defined over binary fields.")) + length(symbols(parent(a))) == 2 || + throw(DomainError("Polynomials must be over two variables.")) g = gens(modulus(R)) length(g) == 2 || throw(DomainError("Residue rings must have only two generators.")) @@ -1126,7 +1325,9 @@ function BivariateBicycleCode(a::T, b::T) where T <: Union{MPolyQuoRingElem{FqMP exps = collect(exponents(g1)) length(exps) == 2 || throw(ArgumentError("Moduli of the incorrect form.")) iszero(exps[2]) || throw(ArgumentError("Moduli of the incorrect form.")) - !iszero(exps[1][1]) && !iszero(exps[1][2]) && throw(ArgumentError("Moduli of the incorrect form.")) + !iszero(exps[1][1]) && + !iszero(exps[1][2]) && + throw(ArgumentError("Moduli of the incorrect form.")) if iszero(exps[1][1]) m = exps[1][2] else @@ -1134,12 +1335,17 @@ function BivariateBicycleCode(a::T, b::T) where T <: Union{MPolyQuoRingElem{FqMP end end - x = matrix(F, [mod1(i + 1, l) == j ? 1 : 0 for i in 1:l, j in 1:l]) ⊗ identity_matrix(F, m) - y = identity_matrix(F, l) ⊗ matrix(F, [mod1(i + 1, m) == j ? 1 : 0 for i in 1:m, j in 1:m]) + x = + matrix(F, [mod1(i + 1, l) == j ? 1 : 0 for i = 1:l, j = 1:l]) ⊗ identity_matrix(F, m) + y = + identity_matrix(F, l) ⊗ + matrix(F, [mod1(i + 1, m) == j ? 1 : 0 for i = 1:m, j = 1:m]) A = zero_matrix(F, l * m, l * m) for ex in exponents(lift(a)) - iszero(ex[1]) || iszero(ex[2]) || throw(ArgumentError("Polynomial `a` must not have any `xy` terms")) + iszero(ex[1]) || + iszero(ex[2]) || + throw(ArgumentError("Polynomial `a` must not have any `xy` terms")) power, which = findmax(ex) if which == 1 A += x^power @@ -1150,7 +1356,9 @@ function BivariateBicycleCode(a::T, b::T) where T <: Union{MPolyQuoRingElem{FqMP B = zero_matrix(F, l * m, l * m) for ex in exponents(lift(b)) - iszero(ex[1]) || iszero(ex[2]) || throw(ArgumentError("Polynomial `b` must not have any `xy` terms")) + iszero(ex[1]) || + iszero(ex[2]) || + throw(ArgumentError("Polynomial `b` must not have any `xy` terms")) power, which = findmax(ex) if which == 1 B += x^power @@ -1177,11 +1385,13 @@ function CoprimeBivariateBicycleCode(a::ResElem, b::ResElem) S = base_ring(a) R == parent(b) || throw(DomainError("Polynomials must have the same parent.")) F = base_ring(S) - order(F) == 2 || throw(DomainError("This code family is currently only defined over binary fields.")) + order(F) == 2 || + throw(DomainError("This code family is currently only defined over binary fields.")) length(gens(S)) == 1 || throw(DomainError("Polynomials must be over one variable.")) f = modulus(R) deg_P = degree(f) - f == gen(S)^deg_P - 1 || throw(ArgumentError("Residue ring not of the form π^(l * m) - 1.")) + f == gen(S)^deg_P - 1 || + throw(ArgumentError("Residue ring not of the form π^(l * m) - 1.")) facs = Nemo.factor(deg_P) length(facs) == 2 || throw(ArgumentError("Residue ring not of the form π^(l * m) - 1.")) @@ -1196,8 +1406,11 @@ function CoprimeBivariateBicycleCode(a::ResElem, b::ResElem) # factorization # gcd(l, m) == 1 || throw(ArgumentError("l and m must be coprime")) - x = matrix(F, [mod1(i + 1, l) == j ? 1 : 0 for i in 1:l, j in 1:l]) ⊗ identity_matrix(F, m) - y = identity_matrix(F, l) ⊗ matrix(F, [mod1(i + 1, m) == j ? 1 : 0 for i in 1:m, j in 1:m]) + x = + matrix(F, [mod1(i + 1, l) == j ? 1 : 0 for i = 1:l, j = 1:l]) ⊗ identity_matrix(F, m) + y = + identity_matrix(F, l) ⊗ + matrix(F, [mod1(i + 1, m) == j ? 1 : 0 for i = 1:m, j = 1:m]) P = x * y A = zero_matrix(F, deg_P, deg_P) diff --git a/src/Quantum/simulation.jl b/src/Quantum/simulation.jl index f86ffddd..518c582d 100644 --- a/src/Quantum/simulation.jl +++ b/src/Quantum/simulation.jl @@ -5,12 +5,18 @@ # LICENSE file in the root directory of this source tree. ############################# - # Methods +# Methods ############################# -function _message_passing_init_CSS(S::AbstractStabilizerCode, chn::Dict{Int, Float64}, - max_iter::Int, X_chn_inits::Union{Missing, Vector{Float64}}, - Z_chn_inits::Union{Missing, Vector{Float64}}, schedule::Symbol, erasures::Vector{Int}) +function _message_passing_init_CSS( + S::AbstractStabilizerCode, + chn::Dict{Int,Float64}, + max_iter::Int, + X_chn_inits::Union{Missing,Vector{Float64}}, + Z_chn_inits::Union{Missing,Vector{Float64}}, + schedule::Symbol, + erasures::Vector{Int}, +) # initial checks X_stabs = _Flint_matrix_to_Julia_int_matrix(X_stabilizers(S)) @@ -22,10 +28,10 @@ function _message_passing_init_CSS(S::AbstractStabilizerCode, chn::Dict{Int, Flo Z_num_check > 0 || throw(ArgumentError("Input matrix of improper dimension")) 2 <= max_iter || throw(DomainError("Number of maximum iterations must be at least two")) - X_check_adj_list = [Int[] for _ in 1:X_num_check] - X_var_adj_list = [Int[] for _ in 1:n] - for r in 1:X_num_check - for c in 1:n + X_check_adj_list = [Int[] for _ = 1:X_num_check] + X_var_adj_list = [Int[] for _ = 1:n] + for r = 1:X_num_check + for c = 1:n if !iszero(X_stabs[r, c]) push!(X_check_adj_list[r], c) push!(X_var_adj_list[c], r) @@ -33,10 +39,10 @@ function _message_passing_init_CSS(S::AbstractStabilizerCode, chn::Dict{Int, Flo end end - Z_check_adj_list = [Int[] for _ in 1:Z_num_check] - Z_var_adj_list = [Int[] for _ in 1:n] - for r in 1:Z_num_check - for c in 1:n + Z_check_adj_list = [Int[] for _ = 1:Z_num_check] + Z_var_adj_list = [Int[] for _ = 1:n] + for r = 1:Z_num_check + for c = 1:n if !iszero(Z_stabs[r, c]) push!(Z_check_adj_list[r], c) push!(Z_var_adj_list[c], r) @@ -47,14 +53,14 @@ function _message_passing_init_CSS(S::AbstractStabilizerCode, chn::Dict{Int, Flo Pauli_weights = collect(values(chn)) if ismissing(X_chn_inits) # CSS - so initial condition is log(p_I / p_X) - X_chn_inits_2 = [log(Pauli_weights[1] / Pauli_weights[2]) for _ in 1:n] + X_chn_inits_2 = [log(Pauli_weights[1] / Pauli_weights[2]) for _ = 1:n] else length(X_chn_inits) ≠ n && throw(ArgumentError("Channel inputs has wrong size")) X_chn_inits_2 = X_chn_inits end if ismissing(Z_chn_inits) # CSS - so initial condition is log(p_I / p_Z) - Z_chn_inits_2 = [log(Pauli_weights[1] / Pauli_weights[4]) for _ in 1:n] + Z_chn_inits_2 = [log(Pauli_weights[1] / Pauli_weights[4]) for _ = 1:n] else length(Z_chn_inits) ≠ n && throw(ArgumentError("Channel inputs has wrong size")) Z_chn_inits_2 = Z_chn_inits @@ -92,13 +98,28 @@ function _message_passing_init_CSS(S::AbstractStabilizerCode, chn::Dict{Int, Flo end end - return X_stabs, Z_stabs, logs, X_err, Z_err, X_var_adj_list, X_check_adj_list, - Z_var_adj_list, Z_check_adj_list, X_chn_inits_2, Z_chn_inits_2, - X_check_to_var_messages, X_var_to_check_messages, Z_check_to_var_messages, - Z_var_to_check_messages, current_bits, totals, X_syn, Z_syn + return X_stabs, + Z_stabs, + logs, + X_err, + Z_err, + X_var_adj_list, + X_check_adj_list, + Z_var_adj_list, + Z_check_adj_list, + X_chn_inits_2, + Z_chn_inits_2, + X_check_to_var_messages, + X_var_to_check_messages, + Z_check_to_var_messages, + Z_var_to_check_messages, + current_bits, + totals, + X_syn, + Z_syn end -CSS_decoder_test(S::T) where T <: AbstractStabilizerCode = CSS_decoder_test(CSSTrait(T), S) +CSS_decoder_test(S::T) where {T<:AbstractStabilizerCode} = CSS_decoder_test(CSSTrait(T), S) function CSS_decoder_test(::IsCSS, S::AbstractStabilizerCode) # noise details # noise = [0.01] @@ -127,26 +148,47 @@ function CSS_decoder_test(::IsCSS, S::AbstractStabilizerCode) # a place to store results FER = zeros(Float64, len_noise) - X_local_iters = [Int[] for _ in 1:num_threads] - Z_local_iters = [Int[] for _ in 1:num_threads] + X_local_iters = [Int[] for _ = 1:num_threads] + Z_local_iters = [Int[] for _ = 1:num_threads] for (i, p) in enumerate(noise) println("Starting p = $p") # setup noise model - chn = Dict(0 => 1 - p, 1 => p /3, 2 => p /3, 3 => p / 3) + chn = Dict(0 => 1 - p, 1 => p / 3, 2 => p / 3, 3 => p / 3) Pauli_types = collect(keys(chn)) Pauli_weights = Weights(collect(values(chn))) Pauli_op = [0] # a place to store results local_counts = zeros(Int, num_threads) - Threads.@threads for th in 1:num_threads - X_stabs_dir, Z_stabs_dir, logs_dir, X_err_dir, Z_err_dir, X_var_adj_list_dir, - X_check_adj_list_dir, Z_var_adj_list_dir, Z_check_adj_list_dir, X_chn_inits_dir, - Z_chn_inits_dir, X_check_to_var_messages_dir, X_var_to_check_messages_dir, - Z_check_to_var_messages_dir, Z_var_to_check_messages_dir, current_bits_dir, - totals_dir, X_syn_dir, Z_syn_dir = _message_passing_init_CSS(S, chn, max_iter, - missing, missing, schedule, erasures) + Threads.@threads for th = 1:num_threads + X_stabs_dir, + Z_stabs_dir, + logs_dir, + X_err_dir, + Z_err_dir, + X_var_adj_list_dir, + X_check_adj_list_dir, + Z_var_adj_list_dir, + Z_check_adj_list_dir, + X_chn_inits_dir, + Z_chn_inits_dir, + X_check_to_var_messages_dir, + X_var_to_check_messages_dir, + Z_check_to_var_messages_dir, + Z_var_to_check_messages_dir, + current_bits_dir, + totals_dir, + X_syn_dir, + Z_syn_dir = _message_passing_init_CSS( + S, + chn, + max_iter, + missing, + missing, + schedule, + erasures, + ) nr_X = size(X_stabs_dir, 1) nr_Z = size(Z_stabs_dir, 1) @@ -154,9 +196,9 @@ function CSS_decoder_test(::IsCSS, S::AbstractStabilizerCode) X_meas_syn_dir = zeros(Int, nr_X) Z_meas_syn_dir = zeros(Int, nr_Z) - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread # sample - @inbounds @simd for j in 1:n + @inbounds @simd for j = 1:n sample!(Pauli_types, Pauli_weights, Pauli_op) # println(Pauli_op) if Pauli_op[1] == 0 @@ -183,16 +225,28 @@ function CSS_decoder_test(::IsCSS, S::AbstractStabilizerCode) # TODO do some timing on this reset vs map or broadcast # X syndrome LinearAlgebra.mul!(X_meas_syn_dir, X_stabs_dir, Z_err_dir) - @inbounds @simd for i in 1:nr_X + @inbounds @simd for i = 1:nr_X X_meas_syn_dir[i] %= 2 end # println(X_syn_dir) # decode X - X_flag_dir, X_out_dir, X_iter_dir, = _message_passing(X_stabs_dir, X_meas_syn_dir, - X_chn_inits_dir, _SP_check_node_message_box_plus, X_var_adj_list_dir, - X_check_adj_list_dir, max_iter, schedule, current_bits_dir, totals_dir, - X_syn_dir, X_check_to_var_messages_dir, X_var_to_check_messages_dir, 0.0) + X_flag_dir, X_out_dir, X_iter_dir, = _message_passing( + X_stabs_dir, + X_meas_syn_dir, + X_chn_inits_dir, + _SP_check_node_message_box_plus, + X_var_adj_list_dir, + X_check_adj_list_dir, + max_iter, + schedule, + current_bits_dir, + totals_dir, + X_syn_dir, + X_check_to_var_messages_dir, + X_var_to_check_messages_dir, + 0.0, + ) # shouldn't matter if I mod 2 this now or later? Z_err_dir += X_out_dir X_flag_dir && push!(X_local_iters[th], X_iter_dir) @@ -200,21 +254,33 @@ function CSS_decoder_test(::IsCSS, S::AbstractStabilizerCode) # Z syndrome LinearAlgebra.mul!(Z_meas_syn_dir, Z_stabs_dir, X_err_dir) - @inbounds @simd for i in 1:nr_Z + @inbounds @simd for i = 1:nr_Z Z_meas_syn_dir[i] %= 2 end # println(Z_syn_dir) # decode Z - Z_flag_dir, Z_out_dir, Z_iter_dir, = _message_passing(Z_stabs_dir, Z_meas_syn_dir, - Z_chn_inits_dir, _SP_check_node_message_box_plus, Z_var_adj_list_dir, - Z_check_adj_list_dir, max_iter, schedule, current_bits_dir, totals_dir, - Z_syn_dir, Z_check_to_var_messages_dir, Z_var_to_check_messages_dir, 0.0) + Z_flag_dir, Z_out_dir, Z_iter_dir, = _message_passing( + Z_stabs_dir, + Z_meas_syn_dir, + Z_chn_inits_dir, + _SP_check_node_message_box_plus, + Z_var_adj_list_dir, + Z_check_adj_list_dir, + max_iter, + schedule, + current_bits_dir, + totals_dir, + Z_syn_dir, + Z_check_to_var_messages_dir, + Z_var_to_check_messages_dir, + 0.0, + ) X_err_dir += Z_out_dir Z_flag_dir && push!(Z_local_iters[th], Z_iter_dir) # println(Z_flag_dir, " ", Z_out_dir, " ", Z_iter_dir) # return - + if X_flag_dir && Z_flag_dir # converged # this implements !iszero(hcat(Z_err, -X_err) * transpose(logs)) but avoids the @@ -224,10 +290,12 @@ function CSS_decoder_test(::IsCSS, S::AbstractStabilizerCode) # if !iszero(temp .% 2) # local_counts[th] += 1 # end - @inbounds for j in 1:nr_logs + @inbounds for j = 1:nr_logs # introduced a logical error - iseven(dot(view(logs_dir, j, 1:n), Z_err_dir) - dot(view(logs_dir, j, n + - 1:2 * n), X_err_dir)) || (local_counts[th] += 1; break;) + iseven( + dot(view(logs_dir, j, 1:n), Z_err_dir) - + dot(view(logs_dir, j, (n+1):(2*n)), X_err_dir), + ) || (local_counts[th] += 1; break;) end else # did not converge @@ -246,14 +314,15 @@ function CSS_decoder_test(::IsCSS, S::AbstractStabilizerCode) println("FER = $(FER[i])") println("Finished p = $p") end - return FER, StatsBase.countmap(reduce(vcat, X_local_iters)), - StatsBase.countmap(reduce(vcat, Z_local_iters)) + return FER, + StatsBase.countmap(reduce(vcat, X_local_iters)), + StatsBase.countmap(reduce(vcat, Z_local_iters)) end CSS_decoder_test(::IsNotCSS, S::AbstractStabilizerCode) = throw(ArgumentError("CSS decoders are only valid for CSS codes")) # using Bayes from X to update the Z priors -CSS_decoder_with_Bayes(S::T; verbose::Bool = true) where T <: AbstractStabilizerCode = +CSS_decoder_with_Bayes(S::T; verbose::Bool = true) where {T<:AbstractStabilizerCode} = CSS_decoder_with_Bayes(CSSTrait(T), S, verbose) function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # noise details @@ -261,7 +330,7 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # these are the markers from the paper # noise = [0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.11, 0.12, 0.13, 0.14] # noise = [0.001, 0.005, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.11, 0.12, 0.13, 0.14] - noise = 10 .^(-3:.25:-1); + noise = 10 .^ (-3:0.25:-1); # left = 1e-2 # right = 1e-1 # intervals = 11 @@ -285,18 +354,20 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo num_threads = Threads.nthreads() runs_per_thread = cld(num_runs, num_threads) new_num_runs = runs_per_thread * num_threads - verbose && println("Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs") + verbose && println( + "Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs", + ) # preallocate places to store results FER = zeros(Float64, len_noise) local_log_failure_counts = zeros(Int, num_threads) local_conv_failure_counts = zeros(Int, num_threads) - X_local_iters = [Dict{Int, Int}() for _ in 1:num_threads] - Z_local_iters = [Dict{Int, Int}() for _ in 1:num_threads] - for i in 1:num_threads + X_local_iters = [Dict{Int,Int}() for _ = 1:num_threads] + Z_local_iters = [Dict{Int,Int}() for _ = 1:num_threads] + for i = 1:num_threads sizehint!(X_local_iters[i], max_iter) sizehint!(Z_local_iters[i], max_iter) - for j in 1:max_iter + for j = 1:max_iter X_local_iters[i][j] = 0 Z_local_iters[i][j] = 0 end @@ -305,7 +376,7 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # check which should be importance sampled imp_sam_ind = len_noise sort!(noise) - for i in 1:len_noise + for i = 1:len_noise # first probability where the expected value of the error weight under # direct sampling is nontrivial in a way that isn't going to severely # under estimate the FER @@ -322,20 +393,22 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # TODO: fix min_subset = 0 max_subset = 36 - subsets = [i for i in min_subset:max_subset] - subset_dic = Dict{Int, Float64}() + subsets = [i for i = min_subset:max_subset] + subset_dic = Dict{Int,Float64}() fail_flag = false if verbose println("Starting importance sampling on $(length(noise_impt)) noise values.") - println("Minimum subset: $min_subset, maximum subset: $max_subset, tolerance: $tolerance") + println( + "Minimum subset: $min_subset, maximum subset: $max_subset, tolerance: $tolerance", + ) end p = noise_impt[end] verbose && println("Starting importance sampling in noise range $noise_impt") # setup noise model - chn = Dict(0 => 1 - p, 1 => p /3, 2 => p /3, 3 => p / 3) + chn = Dict(0 => 1 - p, 1 => p / 3, 2 => p / 3, 3 => p / 3) Pauli_types = collect(keys(chn)) Pauli_weights = collect(values(chn)) PrII = Pauli_weights[1] / (Pauli_weights[1] + Pauli_weights[4]) @@ -353,13 +426,34 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo subset_dic[s] = 1.0 else verbose && println("Subset $s") - Threads.@threads for th in 1:num_threads - X_stabs, Z_stabs, logs, X_err, Z_err, X_var_adj_list, - X_check_adj_list, Z_var_adj_list, Z_check_adj_list, X_chn_inits, - Z_chn_inits, X_check_to_var_messages, X_var_to_check_messages, - Z_check_to_var_messages, Z_var_to_check_messages, current_bits, - totals, X_syn, Z_syn = _message_passing_init_CSS(S, chn, max_iter, - missing, missing, schedule, erasures) + Threads.@threads for th = 1:num_threads + X_stabs, + Z_stabs, + logs, + X_err, + Z_err, + X_var_adj_list, + X_check_adj_list, + Z_var_adj_list, + Z_check_adj_list, + X_chn_inits, + Z_chn_inits, + X_check_to_var_messages, + X_var_to_check_messages, + Z_check_to_var_messages, + Z_var_to_check_messages, + current_bits, + totals, + X_syn, + Z_syn = _message_passing_init_CSS( + S, + chn, + max_iter, + missing, + missing, + schedule, + erasures, + ) nr_X = size(X_stabs, 1) nr_Z = size(Z_stabs, 1) @@ -368,14 +462,15 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo Z_meas_syn = zeros(Int, nr_Z) err_locs = zeros(Int, s) - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread # sample X_err[:] .= 0 Z_err[:] .= 0 sample!(sample_range, err_locs, replace = false) @inbounds for e in err_locs # exclude I here - Pauli_op = sample(Pauli_types[2:end], Weights(Pauli_weights[2:end])) + Pauli_op = + sample(Pauli_types[2:end], Weights(Pauli_weights[2:end])) # println(Pauli_op) if Pauli_op == 1 # X @@ -394,7 +489,7 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # X syndrome LinearAlgebra.mul!(X_meas_syn, X_stabs, Z_err) - @inbounds @simd for i in 1:nr_X + @inbounds @simd for i = 1:nr_X X_meas_syn[i] %= 2 end @@ -403,10 +498,23 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # X_chn_inits, _SP_check_node_message_box_plus, X_var_adj_list, # X_check_adj_list, max_iter, schedule, current_bits, totals, # X_syn, X_check_to_var_messages, X_var_to_check_messages, 0.0) - X_flag, X_out, X_iter, = _message_passing_layered(X_stabs, X_meas_syn, - X_chn_inits, _SP_check_node_message_box_plus, X_var_adj_list, - X_check_adj_list, max_iter, schedule, current_bits, totals, - X_syn, X_check_to_var_messages, X_var_to_check_messages, 0.0, X_layers) + X_flag, X_out, X_iter, = _message_passing_layered( + X_stabs, + X_meas_syn, + X_chn_inits, + _SP_check_node_message_box_plus, + X_var_adj_list, + X_check_adj_list, + max_iter, + schedule, + current_bits, + totals, + X_syn, + X_check_to_var_messages, + X_var_to_check_messages, + 0.0, + X_layers, + ) # shouldn't matter if I mod 2 this now or later Z_err += X_out X_flag && (X_local_iters[th][X_iter] += 1;) @@ -414,7 +522,7 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # Z syndrome LinearAlgebra.mul!(Z_meas_syn, Z_stabs, X_err) - @inbounds @simd for i in 1:nr_Z + @inbounds @simd for i = 1:nr_Z Z_meas_syn[i] %= 2 end # println(Z_syn) @@ -422,7 +530,7 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # update priors on Z given the results from X # always log(Pr(no error) / Pr(error)) so now # log(Pr(I | I) / Pr(Z | I)) and log(Pr(I | X) / Pr(Z | X)) - @inbounds @simd for i in 1:n + @inbounds @simd for i = 1:n if X_out[i] == 0 Z_chn_inits[i] = without_X_err else @@ -435,14 +543,27 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # Z_chn_inits, _SP_check_node_message_box_plus, Z_var_adj_list, # Z_check_adj_list, max_iter, schedule, current_bits, totals, # Z_syn, Z_check_to_var_messages, Z_var_to_check_messages, 0.0) - Z_flag, Z_out, Z_iter, = _message_passing_layered(Z_stabs, Z_meas_syn, - Z_chn_inits, _SP_check_node_message_box_plus, Z_var_adj_list, - Z_check_adj_list, max_iter, schedule, current_bits, totals, - Z_syn, Z_check_to_var_messages, Z_var_to_check_messages, 0.0, Z_layers) + Z_flag, Z_out, Z_iter, = _message_passing_layered( + Z_stabs, + Z_meas_syn, + Z_chn_inits, + _SP_check_node_message_box_plus, + Z_var_adj_list, + Z_check_adj_list, + max_iter, + schedule, + current_bits, + totals, + Z_syn, + Z_check_to_var_messages, + Z_var_to_check_messages, + 0.0, + Z_layers, + ) X_err += Z_out Z_flag && (Z_local_iters[th][Z_iter] += 1;) # println(Z_flag, " ", Z_out, " ", Z_iter) - + if X_flag && Z_flag # converged # this implements !iszero(hcat(Z_err, -X_err) * transpose(logs)) but avoids the @@ -453,10 +574,12 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # local_counts[th] += 1 # end # TODO keep track of the logical error rate on individual logical qubits - @inbounds for j in 1:nr_logs + @inbounds for j = 1:nr_logs # introduced a logical error - iseven(dot(view(logs, j, 1:n), Z_err) - dot(view(logs, j, n + - 1:2 * n), X_err)) || (local_log_failure_counts[th] += 1; break;) + iseven( + dot(view(logs, j, 1:n), Z_err) - + dot(view(logs, j, (n+1):(2*n)), X_err), + ) || (local_log_failure_counts[th] += 1; break;) end # continue else @@ -474,7 +597,9 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo verbose && println("logical failures: $local_log_failure_counts") verbose && println("convergence failures: $local_conv_failure_counts") - subset_dic[s] = (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / new_num_runs + subset_dic[s] = + (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / + new_num_runs # short circuit the rest of the subsets if they are all going to fail if subset_dic[s] ≥ 0.97 @@ -504,12 +629,12 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo local_log_failure_counts[:] .= 0 end - for i in imp_sam_ind + 1:len_noise + for i = (imp_sam_ind+1):len_noise p = noise[i] println("Starting p = $p") # setup noise model - chn = Dict(0 => 1 - p, 1 => p /3, 2 => p /3, 3 => p / 3) + chn = Dict(0 => 1 - p, 1 => p / 3, 2 => p / 3, 3 => p / 3) Pauli_types = collect(keys(chn)) Pauli_weights = collect(values(chn)) PrII = Pauli_weights[1] / (Pauli_weights[1] + Pauli_weights[4]) @@ -519,13 +644,34 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo without_X_err = log(PrII / PrZI) with_X_err = log(PrIX / PrZX) - Threads.@threads for th in 1:num_threads - X_stabs_dir, Z_stabs_dir, logs_dir, X_err_dir, Z_err_dir, X_var_adj_list_dir, - X_check_adj_list_dir, Z_var_adj_list_dir, Z_check_adj_list_dir, X_chn_inits_dir, - Z_chn_inits_dir, X_check_to_var_messages_dir, X_var_to_check_messages_dir, - Z_check_to_var_messages_dir, Z_var_to_check_messages_dir, current_bits_dir, - totals_dir, X_syn_dir, Z_syn_dir = _message_passing_init_CSS(S, chn, max_iter, - missing, missing, schedule, erasures) + Threads.@threads for th = 1:num_threads + X_stabs_dir, + Z_stabs_dir, + logs_dir, + X_err_dir, + Z_err_dir, + X_var_adj_list_dir, + X_check_adj_list_dir, + Z_var_adj_list_dir, + Z_check_adj_list_dir, + X_chn_inits_dir, + Z_chn_inits_dir, + X_check_to_var_messages_dir, + X_var_to_check_messages_dir, + Z_check_to_var_messages_dir, + Z_var_to_check_messages_dir, + current_bits_dir, + totals_dir, + X_syn_dir, + Z_syn_dir = _message_passing_init_CSS( + S, + chn, + max_iter, + missing, + missing, + schedule, + erasures, + ) nr_X = size(X_stabs_dir, 1) nr_Z = size(Z_stabs_dir, 1) @@ -533,9 +679,9 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo X_meas_syn_dir = zeros(Int, nr_X) Z_meas_syn_dir = zeros(Int, nr_Z) - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread # sample - @inbounds @simd for j in 1:n + @inbounds @simd for j = 1:n Pauli_op = sample(Pauli_types, Weights(Pauli_weights)) # println(Pauli_op) if Pauli_op == 0 @@ -561,7 +707,7 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # X syndrome LinearAlgebra.mul!(X_meas_syn_dir, X_stabs_dir, Z_err_dir) - @inbounds @simd for i in 1:nr_X + @inbounds @simd for i = 1:nr_X X_meas_syn_dir[i] %= 2 end # println(X_syn_dir) @@ -571,10 +717,23 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # X_chn_inits_dir, _SP_check_node_message_box_plus, X_var_adj_list_dir, # X_check_adj_list_dir, max_iter, schedule, current_bits_dir, totals_dir, # X_syn_dir, X_check_to_var_messages_dir, X_var_to_check_messages_dir, 0.0) - X_flag_dir, X_out_dir, X_iter_dir, = _message_passing_layered(X_stabs_dir, X_meas_syn_dir, - X_chn_inits_dir, _SP_check_node_message_box_plus, X_var_adj_list_dir, - X_check_adj_list_dir, max_iter, schedule, current_bits_dir, totals_dir, - X_syn_dir, X_check_to_var_messages_dir, X_var_to_check_messages_dir, 0.0, X_layers) + X_flag_dir, X_out_dir, X_iter_dir, = _message_passing_layered( + X_stabs_dir, + X_meas_syn_dir, + X_chn_inits_dir, + _SP_check_node_message_box_plus, + X_var_adj_list_dir, + X_check_adj_list_dir, + max_iter, + schedule, + current_bits_dir, + totals_dir, + X_syn_dir, + X_check_to_var_messages_dir, + X_var_to_check_messages_dir, + 0.0, + X_layers, + ) # shouldn't matter if I mod 2 this now or later? Z_err_dir += X_out_dir # X_flag_dir && push!(X_local_iters[th], X_iter_dir) @@ -583,7 +742,7 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # Z syndrome LinearAlgebra.mul!(Z_meas_syn_dir, Z_stabs_dir, X_err_dir) - @inbounds @simd for i in 1:nr_Z + @inbounds @simd for i = 1:nr_Z Z_meas_syn_dir[i] %= 2 end # println(Z_syn_dir) @@ -591,7 +750,7 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # update priors on Z given the results from X # always log(Pr(no error) / Pr(error)) so now # log((Pr(I | I) + Pr(I | X)) / (Pr(Z | I) + Pr(Z | X))) - @inbounds @simd for i in 1:n + @inbounds @simd for i = 1:n if X_out_dir[i] == 0 Z_chn_inits_dir[i] = without_X_err else @@ -603,16 +762,29 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # Z_chn_inits_dir, _SP_check_node_message_box_plus, Z_var_adj_list_dir, # Z_check_adj_list_dir, max_iter, schedule, current_bits_dir, totals_dir, # Z_syn_dir, Z_check_to_var_messages_dir, Z_var_to_check_messages_dir, 0.0) - Z_flag_dir, Z_out_dir, Z_iter_dir, = _message_passing_layered(Z_stabs_dir, Z_meas_syn_dir, - Z_chn_inits_dir, _SP_check_node_message_box_plus, Z_var_adj_list_dir, - Z_check_adj_list_dir, max_iter, schedule, current_bits_dir, totals_dir, - Z_syn_dir, Z_check_to_var_messages_dir, Z_var_to_check_messages_dir, 0.0, Z_layers) + Z_flag_dir, Z_out_dir, Z_iter_dir, = _message_passing_layered( + Z_stabs_dir, + Z_meas_syn_dir, + Z_chn_inits_dir, + _SP_check_node_message_box_plus, + Z_var_adj_list_dir, + Z_check_adj_list_dir, + max_iter, + schedule, + current_bits_dir, + totals_dir, + Z_syn_dir, + Z_check_to_var_messages_dir, + Z_var_to_check_messages_dir, + 0.0, + Z_layers, + ) X_err_dir += Z_out_dir # Z_flag_dir && push!(Z_local_iters[th], Z_iter_dir) Z_flag_dir && (Z_local_iters[th][Z_iter_dir] += 1;) # println(Z_flag_dir, " ", Z_out_dir, " ", Z_iter_dir) # return - + if X_flag_dir && Z_flag_dir # converged # this implements !iszero(hcat(Z_err, -X_err) * transpose(logs)) but avoids the @@ -623,10 +795,12 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo # local_counts[th] += 1 # end # TODO keep track of the logical error rate on individual logical qubits - @inbounds for j in 1:nr_logs + @inbounds for j = 1:nr_logs # introduced a logical error - iseven(dot(view(logs_dir, j, 1:n), Z_err_dir) - dot(view(logs_dir, j, n + - 1:2 * n), X_err_dir)) || (local_log_failure_counts[th] += 1; break;) + iseven( + dot(view(logs_dir, j, 1:n), Z_err_dir) - + dot(view(logs_dir, j, (n+1):(2*n)), X_err_dir), + ) || (local_log_failure_counts[th] += 1; break;) end # continue else @@ -643,7 +817,9 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo end verbose && println("logical failures: $local_log_failure_counts") verbose && println("convergence failures: $local_conv_failure_counts") - @inbounds FER[i] = (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / new_num_runs + @inbounds FER[i] = + (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / + new_num_runs verbose && println("FER = $(FER[i])") verbose && println("Finished p = $p") @@ -652,9 +828,10 @@ function CSS_decoder_with_Bayes(::IsCSS, S::AbstractStabilizerCode, verbose::Boo end end # return FER, StatsBase.countmap(reduce(vcat, X_local_iters)), - # StatsBase.countmap(reduce(vcat, Z_local_iters)) - return FER, foldl(mergewith!(+), X_local_iters; init = Dict{Int, Int}()), - foldl(mergewith!(+), Z_local_iters; init = Dict{Int, Int}()) + # StatsBase.countmap(reduce(vcat, Z_local_iters)) + return FER, + foldl(mergewith!(+), X_local_iters; init = Dict{Int,Int}()), + foldl(mergewith!(+), Z_local_iters; init = Dict{Int,Int}()) end CSS_decoder_with_Bayes(::IsNotCSS, S::AbstractStabilizerCode, verbose::Bool) = throw(ArgumentError("CSS decoders are only valid for CSS codes")) @@ -662,13 +839,13 @@ CSS_decoder_with_Bayes(::IsNotCSS, S::AbstractStabilizerCode, verbose::Bool) = #### # M -CSS_metachecks_Mike(S::T; verbose::Bool = true) where T <: AbstractStabilizerCode = +CSS_metachecks_Mike(S::T; verbose::Bool = true) where {T<:AbstractStabilizerCode} = CSS_metachecks_Mike(CSSTrait(T), S, verbose) function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # noise details # these are the markers from the paper # noise = [0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.11, 0.12, 0.13, 0.14] - noise = 10 .^(-3:.25:-1); + noise = 10 .^ (-3:0.25:-1); len_noise = length(noise) # BP details @@ -691,18 +868,20 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) num_threads = Threads.nthreads() runs_per_thread = cld(num_runs, num_threads) new_num_runs = runs_per_thread * num_threads - verbose && println("Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs") + verbose && println( + "Number of threads: $num_threads, runs per thread: $runs_per_thread, new number of runs: $new_num_runs", + ) # preallocate places to store results FER = zeros(Float64, len_noise) local_log_failure_counts = zeros(Int, num_threads) local_conv_failure_counts = zeros(Int, num_threads) - X_local_iters = [Dict{Int, Int}() for _ in 1:num_threads] - Z_local_iters = [Dict{Int, Int}() for _ in 1:num_threads] - for i in 1:num_threads + X_local_iters = [Dict{Int,Int}() for _ = 1:num_threads] + Z_local_iters = [Dict{Int,Int}() for _ = 1:num_threads] + for i = 1:num_threads sizehint!(X_local_iters[i], max_iter) sizehint!(Z_local_iters[i], max_iter) - for j in 1:max_iter + for j = 1:max_iter X_local_iters[i][j] = 0 Z_local_iters[i][j] = 0 end @@ -711,7 +890,7 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # check which should be importance sampled imp_sam_ind = len_noise sort!(noise) - for i in 1:len_noise + for i = 1:len_noise # first probability where the expected value of the error weight under # direct sampling is nontrivial in a way that isn't going to severely # under estimate the FER @@ -728,20 +907,22 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # TODO: fix min_subset = 0 max_subset = 36 - subsets = [i for i in min_subset:max_subset] - subset_dic = Dict{Int, Float64}() + subsets = [i for i = min_subset:max_subset] + subset_dic = Dict{Int,Float64}() fail_flag = false if verbose println("Starting importance sampling on $(length(noise_impt)) noise values.") - println("Minimum subset: $min_subset, maximum subset: $max_subset, tolerance: $tolerance") + println( + "Minimum subset: $min_subset, maximum subset: $max_subset, tolerance: $tolerance", + ) end p = noise_impt[end] verbose && println("Starting importance sampling in noise range $noise_impt") # setup noise model - chn = Dict(0 => 1 - p, 1 => p /3, 2 => p /3, 3 => p / 3) + chn = Dict(0 => 1 - p, 1 => p / 3, 2 => p / 3, 3 => p / 3) Pauli_types = collect(keys(chn)) Pauli_weights = collect(values(chn)) PrII = Pauli_weights[1] / (Pauli_weights[1] + Pauli_weights[4]) @@ -764,14 +945,35 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) subset_dic[s] = 1.0 else verbose && println("Subset $s") - Threads.@threads for th in 1:num_threads + Threads.@threads for th = 1:num_threads # code - X_stabs, Z_stabs, logs, X_err, Z_err, X_var_adj_list, - X_check_adj_list, Z_var_adj_list, Z_check_adj_list, X_chn_inits, - Z_chn_inits, X_check_to_var_messages, X_var_to_check_messages, - Z_check_to_var_messages, Z_var_to_check_messages, current_bits, - totals, X_syn, Z_syn = _message_passing_init_CSS(S, chn, max_iter, - missing, missing, schedule, erasures) + X_stabs, + Z_stabs, + logs, + X_err, + Z_err, + X_var_adj_list, + X_check_adj_list, + Z_var_adj_list, + Z_check_adj_list, + X_chn_inits, + Z_chn_inits, + X_check_to_var_messages, + X_var_to_check_messages, + Z_check_to_var_messages, + Z_var_to_check_messages, + current_bits, + totals, + X_syn, + Z_syn = _message_passing_init_CSS( + S, + chn, + max_iter, + missing, + missing, + schedule, + erasures, + ) nr_X = size(X_stabs, 1) nr_Z = size(Z_stabs, 1) @@ -783,25 +985,54 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) err_locs = zeros(Int, s) # metachecks - X_meta_Int, _, var_adj_list_X_meta, check_adj_list_X_meta, chn_inits_X_meta, - check_to_var_messages_X_meta, var_to_check_messages_X_meta, - current_bits_X_meta, totals_X_meta, syn_X_meta = - _message_passing_init(X_metacheck(S), X_meas_syn, chn_X_meas, max_iter, :SP, - missing, schedule, X_syn_erasures) - Z_meta_Int, _, var_adj_list_Z_meta, check_adj_list_Z_meta, chn_inits_Z_meta, - check_to_var_messages_Z_meta, var_to_check_messages_Z_meta, - current_bits_Z_meta, totals_Z_meta, syn_Z_meta = - _message_passing_init(Z_metacheck(S), Z_meas_syn, chn_Z_meas, max_iter, :SP, - missing, schedule, Z_syn_erasures) - - for _ in 1:runs_per_thread + X_meta_Int, + _, + var_adj_list_X_meta, + check_adj_list_X_meta, + chn_inits_X_meta, + check_to_var_messages_X_meta, + var_to_check_messages_X_meta, + current_bits_X_meta, + totals_X_meta, + syn_X_meta = _message_passing_init( + X_metacheck(S), + X_meas_syn, + chn_X_meas, + max_iter, + :SP, + missing, + schedule, + X_syn_erasures, + ) + Z_meta_Int, + _, + var_adj_list_Z_meta, + check_adj_list_Z_meta, + chn_inits_Z_meta, + check_to_var_messages_Z_meta, + var_to_check_messages_Z_meta, + current_bits_Z_meta, + totals_Z_meta, + syn_Z_meta = _message_passing_init( + Z_metacheck(S), + Z_meas_syn, + chn_Z_meas, + max_iter, + :SP, + missing, + schedule, + Z_syn_erasures, + ) + + for _ = 1:runs_per_thread # sample X_err[:] .= 0 Z_err[:] .= 0 sample!(sample_range, err_locs, replace = false) @inbounds for e in err_locs # exclude I here - Pauli_op = sample(Pauli_types[2:end], Weights(Pauli_weights[2:end])) + Pauli_op = + sample(Pauli_types[2:end], Weights(Pauli_weights[2:end])) # println(Pauli_op) if Pauli_op == 1 # X @@ -820,7 +1051,7 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # X syndrome LinearAlgebra.mul!(X_meas_syn, X_stabs, Z_err) - @inbounds @simd for i in 1:nr_X + @inbounds @simd for i = 1:nr_X X_meas_syn[i] %= 2 end @@ -835,12 +1066,24 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # TODO: this multiplication if !iszero(X_metacheck * X_meas_syn) # decode X syndrome - X_flag_meta, X_out_meta, X_iter_meta, = _message_passing_layered( - X_meta_Int, X_meas_syn, chn_inits_X_meta, - _SP_check_node_message_box_plus, var_adj_list_X_meta, - check_adj_list_X_meta, max_iter, schedule, current_bits_X_meta, - totals_X_meta, syn_X_meta, check_to_var_messages_X_meta, - var_to_check_messages_X_meta, 0.0, X_layers_meta) + X_flag_meta, X_out_meta, X_iter_meta, = + _message_passing_layered( + X_meta_Int, + X_meas_syn, + chn_inits_X_meta, + _SP_check_node_message_box_plus, + var_adj_list_X_meta, + check_adj_list_X_meta, + max_iter, + schedule, + current_bits_X_meta, + totals_X_meta, + syn_X_meta, + check_to_var_messages_X_meta, + var_to_check_messages_X_meta, + 0.0, + X_layers_meta, + ) if X_flag_meta # converged @@ -850,14 +1093,24 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # detected an invalid syndrome, re-decode with L_X # TODO this matrix and these values # TODO unclear some of these need an L version - X_flag_meta, X_out_meta, X_iter_meta, = - _message_passing_layered(X_meta_L_Int, X_meas_syn, - chn_inits_X_meta_L, _SP_check_node_message_box_plus, - var_adj_list_X_meta_L, check_adj_list_X_meta_L, - max_iter, schedule, current_bits_X_meta_L, - totals_X_meta_L, syn_X_meta_L, - check_to_var_messages_X_meta_L, - var_to_check_messages_X_meta_L, 0.0, X_layers_meta_L) + X_flag_meta, X_out_meta, X_iter_meta, = + _message_passing_layered( + X_meta_L_Int, + X_meas_syn, + chn_inits_X_meta_L, + _SP_check_node_message_box_plus, + var_adj_list_X_meta_L, + check_adj_list_X_meta_L, + max_iter, + schedule, + current_bits_X_meta_L, + totals_X_meta_L, + syn_X_meta_L, + check_to_var_messages_X_meta_L, + var_to_check_messages_X_meta_L, + 0.0, + X_layers_meta_L, + ) if !X_flag_meta # failed to converge @@ -865,7 +1118,7 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) skip = true end end - + if !skip X_meas_syn += X_out_meta X_meas_syn .%= 2 @@ -882,10 +1135,23 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # forcing it to find an error which doesn't return to the codespace if !skip # decode X - X_flag, X_out, X_iter, = _message_passing_layered(X_stabs, X_meas_syn, - X_chn_inits, _SP_check_node_message_box_plus, X_var_adj_list, - X_check_adj_list, max_iter, schedule, current_bits, totals, - X_syn, X_check_to_var_messages, X_var_to_check_messages, 0.0, X_layers) + X_flag, X_out, X_iter, = _message_passing_layered( + X_stabs, + X_meas_syn, + X_chn_inits, + _SP_check_node_message_box_plus, + X_var_adj_list, + X_check_adj_list, + max_iter, + schedule, + current_bits, + totals, + X_syn, + X_check_to_var_messages, + X_var_to_check_messages, + 0.0, + X_layers, + ) # shouldn't matter if I mod 2 this now or later Z_err += X_out X_flag && (X_local_iters[th][X_iter] += 1; skip = true;) @@ -894,11 +1160,11 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) if !skip # Z syndrome LinearAlgebra.mul!(Z_meas_syn, Z_stabs, X_err) - @inbounds @simd for i in 1:nr_Z + @inbounds @simd for i = 1:nr_Z Z_meas_syn[i] %= 2 end - # add measurement errors + # add measurement errors sample!(syn_err_choices, syn_err_weights, Z_syn_err) if !iszero(Z_syn_err) Z_meas_syn += Z_syn_err @@ -909,12 +1175,24 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # TODO: this multiplication if !iszero(Z_metacheck * Z_meas_syn) # decode Z syndrome - Z_flag_meta, Z_out_meta, Z_iter_meta, = _message_passing_layered( - Z_meta_Int, Z_meas_syn, chn_inits_Z_meta, - _SP_check_node_message_box_plus, var_adj_list_Z_meta, - check_adj_list_Z_meta, max_iter, schedule, current_bits_Z_meta, - totals_Z_meta, syn_Z_meta, check_to_var_messages_Z_meta, - var_to_check_messages_Z_meta, 0.0, Z_layers_meta) + Z_flag_meta, Z_out_meta, Z_iter_meta, = + _message_passing_layered( + Z_meta_Int, + Z_meas_syn, + chn_inits_Z_meta, + _SP_check_node_message_box_plus, + var_adj_list_Z_meta, + check_adj_list_Z_meta, + max_iter, + schedule, + current_bits_Z_meta, + totals_Z_meta, + syn_Z_meta, + check_to_var_messages_Z_meta, + var_to_check_messages_Z_meta, + 0.0, + Z_layers_meta, + ) if Z_flag_meta # converged @@ -924,15 +1202,24 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # detected an invalid syndrome, re-decode with L_X # TODO this matrix and these values # TODO unclear some of these need an L version - Z_flag_meta, Z_out_meta, Z_iter_meta, = - _message_passing_layered(Z_meta_L_Int, Z_meas_syn, - chn_inits_Z_meta_L, _SP_check_node_message_box_plus, - var_adj_list_Z_meta_L, check_adj_list_Z_meta_L, - max_iter, schedule, current_bits_Z_meta_L, - totals_Z_meta_L, syn_Z_meta_L, - check_to_var_messages_Z_meta_L, - var_to_check_messages_Z_meta_L, 0.0, - Z_layers_meta_L) + Z_flag_meta, Z_out_meta, Z_iter_meta, = + _message_passing_layered( + Z_meta_L_Int, + Z_meas_syn, + chn_inits_Z_meta_L, + _SP_check_node_message_box_plus, + var_adj_list_Z_meta_L, + check_adj_list_Z_meta_L, + max_iter, + schedule, + current_bits_Z_meta_L, + totals_Z_meta_L, + syn_Z_meta_L, + check_to_var_messages_Z_meta_L, + var_to_check_messages_Z_meta_L, + 0.0, + Z_layers_meta_L, + ) if !X_flag_meta # failed to converge @@ -940,7 +1227,7 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) skip = true end end - + if !skip X_meas_syn += X_out_meta X_meas_syn .%= 2 @@ -959,7 +1246,7 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # update priors on Z given the results from X # always log(Pr(no error) / Pr(error)) so now # log(Pr(I | I) / Pr(Z | I)) and log(Pr(I | X) / Pr(Z | X)) - @inbounds @simd for i in 1:n + @inbounds @simd for i = 1:n if X_out[i] == 0 Z_chn_inits[i] = without_X_err else @@ -968,10 +1255,23 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) end # decode Z - Z_flag, Z_out, Z_iter, = _message_passing_layered(Z_stabs, Z_meas_syn, - Z_chn_inits, _SP_check_node_message_box_plus, Z_var_adj_list, - Z_check_adj_list, max_iter, schedule, current_bits, totals, - Z_syn, Z_check_to_var_messages, Z_var_to_check_messages, 0.0, Z_layers) + Z_flag, Z_out, Z_iter, = _message_passing_layered( + Z_stabs, + Z_meas_syn, + Z_chn_inits, + _SP_check_node_message_box_plus, + Z_var_adj_list, + Z_check_adj_list, + max_iter, + schedule, + current_bits, + totals, + Z_syn, + Z_check_to_var_messages, + Z_var_to_check_messages, + 0.0, + Z_layers, + ) X_err += Z_out Z_flag && (Z_local_iters[th][Z_iter] += 1; skip = true) end @@ -987,10 +1287,12 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # local_counts[th] += 1 # end # TODO keep track of the logical error rate on individual logical qubits - @inbounds for j in 1:nr_logs + @inbounds for j = 1:nr_logs # introduced a logical error - iseven(dot(view(logs, j, 1:n), Z_err) - dot(view(logs, j, n + - 1:2 * n), X_err)) || (local_log_failure_counts[th] += 1; break;) + iseven( + dot(view(logs, j, 1:n), Z_err) - + dot(view(logs, j, (n+1):(2*n)), X_err), + ) || (local_log_failure_counts[th] += 1; break;) end # continue else @@ -1008,7 +1310,9 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) verbose && println("logical failures: $local_log_failure_counts") verbose && println("convergence failures: $local_conv_failure_counts") - subset_dic[s] = (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / new_num_runs + subset_dic[s] = + (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / + new_num_runs # short circuit the rest of the subsets if they are all going to fail if subset_dic[s] ≥ 0.97 @@ -1038,12 +1342,12 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) local_log_failure_counts[:] .= 0 end - for i in imp_sam_ind + 1:len_noise + for i = (imp_sam_ind+1):len_noise p = noise[i] println("Starting p = $p") # setup noise model - chn = Dict(0 => 1 - p, 1 => p /3, 2 => p /3, 3 => p / 3) + chn = Dict(0 => 1 - p, 1 => p / 3, 2 => p / 3, 3 => p / 3) Pauli_types = collect(keys(chn)) Pauli_weights = collect(values(chn)) PrII = Pauli_weights[1] / (Pauli_weights[1] + Pauli_weights[4]) @@ -1053,13 +1357,34 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) without_X_err = log(PrII / PrZI) with_X_err = log(PrIX / PrZX) - Threads.@threads for th in 1:num_threads - X_stabs_dir, Z_stabs_dir, logs_dir, X_err_dir, Z_err_dir, X_var_adj_list_dir, - X_check_adj_list_dir, Z_var_adj_list_dir, Z_check_adj_list_dir, X_chn_inits_dir, - Z_chn_inits_dir, X_check_to_var_messages_dir, X_var_to_check_messages_dir, - Z_check_to_var_messages_dir, Z_var_to_check_messages_dir, current_bits_dir, - totals_dir, X_syn_dir, Z_syn_dir = _message_passing_init_CSS(S, chn, max_iter, - missing, missing, schedule, erasures) + Threads.@threads for th = 1:num_threads + X_stabs_dir, + Z_stabs_dir, + logs_dir, + X_err_dir, + Z_err_dir, + X_var_adj_list_dir, + X_check_adj_list_dir, + Z_var_adj_list_dir, + Z_check_adj_list_dir, + X_chn_inits_dir, + Z_chn_inits_dir, + X_check_to_var_messages_dir, + X_var_to_check_messages_dir, + Z_check_to_var_messages_dir, + Z_var_to_check_messages_dir, + current_bits_dir, + totals_dir, + X_syn_dir, + Z_syn_dir = _message_passing_init_CSS( + S, + chn, + max_iter, + missing, + missing, + schedule, + erasures, + ) nr_X = size(X_stabs_dir, 1) nr_Z = size(Z_stabs_dir, 1) @@ -1067,9 +1392,9 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) X_meas_syn_dir = zeros(Int, nr_X) Z_meas_syn_dir = zeros(Int, nr_Z) - for _ in 1:runs_per_thread + for _ = 1:runs_per_thread # sample - @inbounds @simd for j in 1:n + @inbounds @simd for j = 1:n Pauli_op = sample(Pauli_types, Weights(Pauli_weights)) # println(Pauli_op) if Pauli_op == 0 @@ -1093,29 +1418,42 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # X syndrome LinearAlgebra.mul!(X_meas_syn_dir, X_stabs_dir, Z_err_dir) - @inbounds @simd for i in 1:nr_X + @inbounds @simd for i = 1:nr_X X_meas_syn_dir[i] %= 2 end # decode X - X_flag_dir, X_out_dir, X_iter_dir, = _message_passing_layered(X_stabs_dir, X_meas_syn_dir, - X_chn_inits_dir, _SP_check_node_message_box_plus, X_var_adj_list_dir, - X_check_adj_list_dir, max_iter, schedule, current_bits_dir, totals_dir, - X_syn_dir, X_check_to_var_messages_dir, X_var_to_check_messages_dir, 0.0, X_layers) + X_flag_dir, X_out_dir, X_iter_dir, = _message_passing_layered( + X_stabs_dir, + X_meas_syn_dir, + X_chn_inits_dir, + _SP_check_node_message_box_plus, + X_var_adj_list_dir, + X_check_adj_list_dir, + max_iter, + schedule, + current_bits_dir, + totals_dir, + X_syn_dir, + X_check_to_var_messages_dir, + X_var_to_check_messages_dir, + 0.0, + X_layers, + ) # shouldn't matter if I mod 2 this now or later? Z_err_dir += X_out_dir X_flag_dir && (X_local_iters[th][X_iter_dir] += 1;) # Z syndrome LinearAlgebra.mul!(Z_meas_syn_dir, Z_stabs_dir, X_err_dir) - @inbounds @simd for i in 1:nr_Z + @inbounds @simd for i = 1:nr_Z Z_meas_syn_dir[i] %= 2 end # update priors on Z given the results from X # always log(Pr(no error) / Pr(error)) so now # log((Pr(I | I) + Pr(I | X)) / (Pr(Z | I) + Pr(Z | X))) - @inbounds @simd for i in 1:n + @inbounds @simd for i = 1:n if X_out_dir[i] == 0 Z_chn_inits_dir[i] = without_X_err else @@ -1123,13 +1461,26 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) end end # decode Z - Z_flag_dir, Z_out_dir, Z_iter_dir, = _message_passing_layered(Z_stabs_dir, Z_meas_syn_dir, - Z_chn_inits_dir, _SP_check_node_message_box_plus, Z_var_adj_list_dir, - Z_check_adj_list_dir, max_iter, schedule, current_bits_dir, totals_dir, - Z_syn_dir, Z_check_to_var_messages_dir, Z_var_to_check_messages_dir, 0.0, Z_layers) + Z_flag_dir, Z_out_dir, Z_iter_dir, = _message_passing_layered( + Z_stabs_dir, + Z_meas_syn_dir, + Z_chn_inits_dir, + _SP_check_node_message_box_plus, + Z_var_adj_list_dir, + Z_check_adj_list_dir, + max_iter, + schedule, + current_bits_dir, + totals_dir, + Z_syn_dir, + Z_check_to_var_messages_dir, + Z_var_to_check_messages_dir, + 0.0, + Z_layers, + ) X_err_dir += Z_out_dir Z_flag_dir && (Z_local_iters[th][Z_iter_dir] += 1;) - + if X_flag_dir && Z_flag_dir # converged # this implements !iszero(hcat(Z_err, -X_err) * transpose(logs)) but avoids the @@ -1140,10 +1491,12 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) # local_counts[th] += 1 # end # TODO keep track of the logical error rate on individual logical qubits - @inbounds for j in 1:nr_logs + @inbounds for j = 1:nr_logs # introduced a logical error - iseven(dot(view(logs_dir, j, 1:n), Z_err_dir) - dot(view(logs_dir, j, n + - 1:2 * n), X_err_dir)) || (local_log_failure_counts[th] += 1; break;) + iseven( + dot(view(logs_dir, j, 1:n), Z_err_dir) - + dot(view(logs_dir, j, (n+1):(2*n)), X_err_dir), + ) || (local_log_failure_counts[th] += 1; break;) end # continue else @@ -1160,7 +1513,9 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) end verbose && println("logical failures: $local_log_failure_counts") verbose && println("convergence failures: $local_conv_failure_counts") - @inbounds FER[i] = (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / new_num_runs + @inbounds FER[i] = + (sum(local_conv_failure_counts) + sum(local_log_failure_counts)) / + new_num_runs verbose && println("FER = $(FER[i])") verbose && println("Finished p = $p") @@ -1168,19 +1523,20 @@ function CSS_metachecks_Mike(::IsCSS, S::AbstractStabilizerCode, verbose::Bool) local_log_failure_counts[:] .= 0 end end - return FER, foldl(mergewith!(+), X_local_iters; init = Dict{Int, Int}()), - foldl(mergewith!(+), Z_local_iters; init = Dict{Int, Int}()) + return FER, + foldl(mergewith!(+), X_local_iters; init = Dict{Int,Int}()), + foldl(mergewith!(+), Z_local_iters; init = Dict{Int,Int}()) end CSS_metachecks_Mike(::IsNotCSS, S::AbstractStabilizerCode, verbose::Bool) = throw(ArgumentError("CSS decoders are only valid for CSS codes")) -function _make_single_shot_Tanner_graph(H::T, M::T) where T <: CTMatrixTypes +function _make_single_shot_Tanner_graph(H::T, M::T) where {T<:CTMatrixTypes} # internal function, so skip checks on correctness nc_H = ncols(H) nc_M = ncols(M) single_shot_matrix = _Flint_matrix_to_Julia_int_matrix(H ⊕ M) - @inbounds @simd for r in nc_H + 1:nc_H + nc_M + @inbounds @simd for r = (nc_H+1):(nc_H+nc_M) single_shot_matrix[r, r] = 1 end # of form (H I; 0 M) diff --git a/src/Quantum/stabilizer_code.jl b/src/Quantum/stabilizer_code.jl index 80025776..ebd7f58a 100644 --- a/src/Quantum/stabilizer_code.jl +++ b/src/Quantum/stabilizer_code.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -20,11 +20,20 @@ and `C2` with `C2 ⊆ C1`. and minimum distance `d >= min(d1, d2^⟂)`. The `X` stabilizers are given by the parity-check matrix of `C2^⟂`, `H(C2^⟂)`, and the `Z` stabilizers by `H(C1)`. """ -function StabilizerCodeCSS(C1::AbstractLinearCode, C2::AbstractLinearCode; - char_vec::Union{Vector{zzModRingElem}, Missing} = missing, logs_alg::Symbol = :stnd_frm) - - logs_alg ∈ [:stnd_frm, :VS, :sys_eqs] || throw(ArgumentError("Unrecognized logicals algorithm")) - C2 ⊆ C1 || throw(ArgumentError("The second argument must be a subset of the first in the CSS construction.")) +function StabilizerCodeCSS( + C1::AbstractLinearCode, + C2::AbstractLinearCode; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) + + logs_alg ∈ [:stnd_frm, :VS, :sys_eqs] || + throw(ArgumentError("Unrecognized logicals algorithm")) + C2 ⊆ C1 || throw( + ArgumentError( + "The second argument must be a subset of the first in the CSS construction.", + ), + ) p = Int(characteristic(C1.F)) char_vec = _process_char_vec(char_vec, p, 2 * C1.n) @@ -37,13 +46,16 @@ function StabilizerCodeCSS(C1::AbstractLinearCode, C2::AbstractLinearCode; stabs_stand, P_stand, stand_r, stand_k, rnk = _standard_form_stabilizer(stabs) if !iszero(stand_k) if logs_alg == :stnd_frm - logs = _make_pairs(_logicals_standard_form(stabs_stand, C1.n, stand_k, stand_r, P_stand)) - logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i in 1:length(logs)]) + logs = _make_pairs( + _logicals_standard_form(stabs_stand, C1.n, stand_k, stand_r, P_stand), + ) + logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i = 1:length(logs)]) else logs, logs_mat = _logicals(stabs, direct_sum(C1.G, D2.G), logs_alg) end end - signs, X_signs, Z_signs = _determine_signs_CSS(stabs, char_vec, nrows(D2.H), nrows(C1.H)) + signs, X_signs, Z_signs = + _determine_signs_CSS(stabs, char_vec, nrows(D2.H), nrows(C1.H)) # q^n / p^k but rows is n - k if !iszero(stand_k) @@ -52,19 +64,53 @@ function StabilizerCodeCSS(C1::AbstractLinearCode, C2::AbstractLinearCode; _, mat = rref(vcat(D2.H, C1.G)) anti = _remove_empty(mat, :rows) * transpose(C1.G) - u_bound_dx, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dx, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) _, mat = rref(vcat(C1.H, D2.G)) anti = _remove_empty(mat, :rows) * transpose(D2.G) - u_bound_dz, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dz, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) u_bound = min(u_bound_dx, u_bound_dz) if !ismissing(C1.d) && !ismissing(D2.d) u_bound_classical = min(C1.d, D2.d) u_bound_classical < u_bound && (u_bound = u_bound_classical;) end - return StabilizerCodeCSS(C1.F, C1.n, dim_code, missing, missing, missing, 1, - u_bound, 1, u_bound_dx, 1, u_bound_dz, stabs, D2.H, C1.H, C2, C1, signs, X_signs, - Z_signs, logs, logs_mat, char_vec, missing, missing, missing, false, missing, - stabs_stand, stand_r, stand_k, P_stand, missing, missing) + return StabilizerCodeCSS( + C1.F, + C1.n, + dim_code, + missing, + missing, + missing, + 1, + u_bound, + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + D2.H, + C1.H, + C2, + C1, + signs, + X_signs, + Z_signs, + logs, + logs_mat, + char_vec, + missing, + missing, + missing, + false, + missing, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) else # graph state distance is defined to be smallest weight stabilizer # TODO check if d's are known already from classical @@ -75,19 +121,51 @@ function StabilizerCodeCSS(C1::AbstractLinearCode, C2::AbstractLinearCode; mat = _remove_empty(mat, :rows) u_bound_dz, _ = _min_wt_row(Z_mat) u_bound = min(u_bound_dx, u_bound_dz) - if !ismissing(C1.d) && is !ismissing(D2.d) + if !ismissing(C1.d) && is + !ismissing(D2.d) u_bound_classical = min(C1.d, D2.d) u_bound_classical < u_bound && (u_bound = u_bound_classical;) end # TODO set upper bounds to distance if known - return GraphStateStabilizerCSS(C1.F, C1.n, 0, missing, D2.d, C1.d, 1, u_bound, 1, u_bound_dx, 1, u_bound_dz, stabs, D2.H, C1.H, C2, - C1, signs, X_signs, Z_signs, char_vec, missing, false, stabs_stand, stand_r, stand_k, - P_stand, missing, missing) + return GraphStateStabilizerCSS( + C1.F, + C1.n, + 0, + missing, + D2.d, + C1.d, + 1, + u_bound, + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + D2.H, + C1.H, + C2, + C1, + signs, + X_signs, + Z_signs, + char_vec, + missing, + false, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) end end -CSSCode(C1::AbstractLinearCode, C2::AbstractLinearCode; char_vec::Union{Vector{zzModRingElem}, Missing} - = missing, logs_alg::Symbol = :stnd_frm) = StabilizerCodeCSS(C1, C2, char_vec = char_vec, - logs_alg = logs_alg) +CSSCode( + C1::AbstractLinearCode, + C2::AbstractLinearCode; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) = StabilizerCodeCSS(C1, C2, char_vec = char_vec, logs_alg = logs_alg) """ StabilizerCodeCSS(C::AbstractLinearCode; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, logs_alg::Symbol = :stnd_frm) @@ -101,10 +179,14 @@ Return the CSS code given by the CSS construction on a self-orthogonal linear co and minimum distance `d >= min(d1, d2^⟂)`. The `X` stabilizers are given by the parity-check matrix of `C2^⟂`, `H(C2^⟂)`, and the `Z` stabilizers by `H(C1)`. """ -function StabilizerCodeCSS(C::LinearCode; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) - - logs_alg ∈ [:stnd_frm, :VS, :sys_eqs] || throw(ArgumentError("Unrecognized logicals algorithm")) +function StabilizerCodeCSS( + C::LinearCode; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) + + logs_alg ∈ [:stnd_frm, :VS, :sys_eqs] || + throw(ArgumentError("Unrecognized logicals algorithm")) # this should have Xstabs = Zstabs D = dual(C) C ⊆ D || throw(ArgumentError("The single code CSS construction requires C ⊆ C^⟂.")) @@ -119,8 +201,10 @@ function StabilizerCodeCSS(C::LinearCode; char_vec::Union{Vector{zzModRingElem}, stabs_stand, P_stand, stand_r, stand_k, rnk = _standard_form_stabilizer(stabs) if !iszero(stand_k) if logs_alg == :stnd_frm - logs = _make_pairs(_logicals_standard_form(stabs_stand, C.n, stand_k, stand_r, P_stand)) - logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i in 1:length(logs)]) + logs = _make_pairs( + _logicals_standard_form(stabs_stand, C.n, stand_k, stand_r, P_stand), + ) + logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i = 1:length(logs)]) else logs, logs_mat = _logicals(stabs, direct_sum(D.G, D.G), logs_alg) end @@ -134,35 +218,128 @@ function StabilizerCodeCSS(C::LinearCode; char_vec::Union{Vector{zzModRingElem}, isinteger(dim_code) && (dim_code = round(Int, log(BigInt(p), dim_code));) X_logs = reduce(vcat, [log[1][:, 1:n] for log in logs]) - Z_logs = reduce(vcat, [log[2][:, n + 1:end] for log in logs]) + Z_logs = reduce(vcat, [log[2][:, (n+1):end] for log in logs]) _, mat = rref(vcat(D.H, X_logs)) anti = _remove_empty(mat, :rows) * transpose(Z_logs) - u_bound_dx, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dx, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) _, mat = rref(vcat(D.H, Z_logs)) anti = _remove_empty(mat, :rows) * transpose(X_logs) - u_bound_dz, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - return StabilizerCodeCSS(D.F, D.n, dim_code, missing, missing, missing, 1, - min(u_bound_dx, u_bound_dz), 1, u_bound_dx, 1, u_bound_dz, stabs, D.H, D.H, C, - D, signs, X_signs, Z_signs, logs, logs_mat, char_vec, missing, missing, missing, false, - missing, stabs_stand, stand_r, stand_k, P_stand, missing, missing) + u_bound_dz, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + return StabilizerCodeCSS( + D.F, + D.n, + dim_code, + missing, + missing, + missing, + 1, + min(u_bound_dx, u_bound_dz), + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + D.H, + D.H, + C, + D, + signs, + X_signs, + Z_signs, + logs, + logs_mat, + char_vec, + missing, + missing, + missing, + false, + missing, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) else # graph state distance is defined to be smallest weight stabilizer if ismissing(D.d) _, mat = rref(D.H) mat = _remove_empty(mat, :rows) u_bound, _ = _min_wt_row(mat) - return GraphStateStabilizerCSS(D.F, D.n, 0, missing, missing, missing, 1, u_bound, 1, - u_bound, 1, u_bound, stabs, D.H, D.H, C, D, signs, X_signs, Z_signs, char_vec, - missing, false, stabs_stand, stand_r, stand_k, P_stand, missing, missing) + return GraphStateStabilizerCSS( + D.F, + D.n, + 0, + missing, + missing, + missing, + 1, + u_bound, + 1, + u_bound, + 1, + u_bound, + stabs, + D.H, + D.H, + C, + D, + signs, + X_signs, + Z_signs, + char_vec, + missing, + false, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) else - return GraphStateStabilizerCSS(D.F, D.n, 0, D.d, D.d, D.d, D.d, D.d, D.d, D.d, D.d, - D.d, stabs, D.H, D.H, C, D, signs, X_signs, Z_signs, char_vec, missing, false, - stabs_stand, stand_r, stand_k, P_stand, missing, missing) + return GraphStateStabilizerCSS( + D.F, + D.n, + 0, + D.d, + D.d, + D.d, + D.d, + D.d, + D.d, + D.d, + D.d, + D.d, + stabs, + D.H, + D.H, + C, + D, + signs, + X_signs, + Z_signs, + char_vec, + missing, + false, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) end end end -CSSCode(C::AbstractLinearCode; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) = StabilizerCodeCSS(C, char_vec = char_vec, logs_alg = logs_alg) +CSSCode( + C::AbstractLinearCode; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) = StabilizerCodeCSS(C, char_vec = char_vec, logs_alg = logs_alg) """ StabilizerCodeCSS(X_matrix::fqPolyRepMatrix, Z_matrix::fqPolyRepMatrix; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, logs_alg::Symbol = :stnd_frm) @@ -170,17 +347,29 @@ CSSCode(C::AbstractLinearCode; char_vec::Union{Vector{zzModRingElem}, Missing} = Return a CSS code whose `X`-stabilizers are given by `X_matrix`, `Z`-stabilizers by `Z_matrix`. """ -function StabilizerCodeCSS(X_matrix::T, Z_matrix::T; char_vec::Union{Vector{zzModRingElem}, Missing} = - missing, logs_alg::Symbol = :stnd_frm) where T <: CTMatrixTypes - - logs_alg ∈ [:stnd_frm, :VS, :sys_eqs] || throw(ArgumentError("Unrecognized logicals algorithm")) +function StabilizerCodeCSS( + X_matrix::T, + Z_matrix::T; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:CTMatrixTypes} + + logs_alg ∈ [:stnd_frm, :VS, :sys_eqs] || + throw(ArgumentError("Unrecognized logicals algorithm")) iszero(X_matrix) && throw(ArgumentError("The `X` stabilizer matrix is empty.")) iszero(Z_matrix) && throw(ArgumentError("The `Z` stabilizer matrix is empty.")) n = ncols(X_matrix) - n == ncols(Z_matrix) || throw(ArgumentError("Both matrices must have the same length in the CSS construction.")) + n == ncols(Z_matrix) || throw( + ArgumentError("Both matrices must have the same length in the CSS construction."), + ) F = base_ring(X_matrix) - F == base_ring(Z_matrix) || throw(ArgumentError("Both matrices must be over the same base field in the CSS construction.")) - iszero(Z_matrix * transpose(X_matrix)) || throw(ArgumentError("The given matrices are not symplectic orthogonal.")) + F == base_ring(Z_matrix) || throw( + ArgumentError( + "Both matrices must be over the same base field in the CSS construction.", + ), + ) + iszero(Z_matrix * transpose(X_matrix)) || + throw(ArgumentError("The given matrices are not symplectic orthogonal.")) p = Int(characteristic(F)) char_vec = _process_char_vec(char_vec, p, 2 * n) @@ -190,16 +379,19 @@ function StabilizerCodeCSS(X_matrix::T, Z_matrix::T; char_vec::Union{Vector{zzMo # determine if the provided set of stabilizers are redundant X_rank = rank(X_matrix) Z_rank = rank(Z_matrix) - nrows(X_matrix) > X_rank || nrows(Z_matrix) > Z_rank ? (over_comp = true) : (over_comp = false) + nrows(X_matrix) > X_rank || nrows(Z_matrix) > Z_rank ? (over_comp = true) : + (over_comp = false) stabs = direct_sum(X_matrix, Z_matrix) stabs_stand, P_stand, stand_r, stand_k, rnk = _standard_form_stabilizer(stabs) if !iszero(stand_k) if logs_alg == :stnd_frm - logs = _make_pairs(_logicals_standard_form(stabs_stand, n, stand_k, stand_r, P_stand)) - logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i in 1:length(logs)]) + logs = _make_pairs( + _logicals_standard_form(stabs_stand, n, stand_k, stand_r, P_stand), + ) + logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i = 1:length(logs)]) else - H = kernel(hcat(stabs[:, n + 1:end], -stabs[:, 1:n]), side = :right) + H = kernel(hcat(stabs[:, (n+1):end], -stabs[:, 1:n]), side = :right) rnk_H = rank(H) if ncols(H) == rnk_H H_tr = transpose(H) @@ -207,18 +399,20 @@ function StabilizerCodeCSS(X_matrix::T, Z_matrix::T; char_vec::Union{Vector{zzMo # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(H) H_tr = zero_matrix(base_ring(H), rnk_H, nr) - for r in 1:nr - for c in 1:rnk_H + for r = 1:nr + for c = 1:rnk_H !iszero(H[r, c]) && (H_tr[c, r] = H[r, c];) end end end # n + (n - Srank) - nrows(H) == 2 * n - X_rank - Z_rank || error("Normalizer matrix is not size n + k.") + nrows(H) == 2 * n - X_rank - Z_rank || + error("Normalizer matrix is not size n + k.") logs, logs_mat = _logicals(stabs, H_tr, logs_alg) end end - signs, X_signs, Z_signs = _determine_signs_CSS(stabs, char_vec, nrows(X_matrix), nrows(Z_matrix)) + signs, X_signs, Z_signs = + _determine_signs_CSS(stabs, char_vec, nrows(X_matrix), nrows(Z_matrix)) # q^n / p^k but rows is n - k if !iszero(stand_k) @@ -226,17 +420,51 @@ function StabilizerCodeCSS(X_matrix::T, Z_matrix::T; char_vec::Union{Vector{zzMo isinteger(dim_code) && (dim_code = round(Int, log(BigInt(p), dim_code));) X_logs = reduce(vcat, [log[1][:, 1:n] for log in logs]) - Z_logs = reduce(vcat, [log[2][:, n + 1:end] for log in logs]) + Z_logs = reduce(vcat, [log[2][:, (n+1):end] for log in logs]) _, mat = rref(vcat(X_matrix, X_logs)) anti = _remove_empty(mat, :rows) * transpose(Z_logs) - u_bound_dx, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dx, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) _, mat = rref(vcat(Z_matrix, Z_logs)) anti = _remove_empty(mat, :rows) * transpose(X_logs) - u_bound_dz, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - return StabilizerCodeCSS(F, n, dim_code, missing, missing, missing, 1, min(u_bound_dx, - u_bound_dz), 1, u_bound_dx, 1, u_bound_dz, stabs, X_matrix, Z_matrix, - missing, missing, signs, X_signs, Z_signs, logs, logs_mat, char_vec, missing, missing, - missing, over_comp, missing, stabs_stand, stand_r, stand_k, P_stand, missing, missing) + u_bound_dz, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + return StabilizerCodeCSS( + F, + n, + dim_code, + missing, + missing, + missing, + 1, + min(u_bound_dx, u_bound_dz), + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + X_matrix, + Z_matrix, + missing, + missing, + signs, + X_signs, + Z_signs, + logs, + logs_mat, + char_vec, + missing, + missing, + missing, + over_comp, + missing, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) else # graph state distance is defined to be smallest weight stabilizer _, mat = rref(X_matrix) @@ -245,15 +473,46 @@ function StabilizerCodeCSS(X_matrix::T, Z_matrix::T; char_vec::Union{Vector{zzMo _, mat = rref(Z_matrix) mat = _remove_empty(mat, :rows) u_bound_dz, _ = _min_wt_row(mat) - return GraphStateStabilizerCSS(F, n, 0, missing, missing, missing, 1, min(u_bound_dx, - u_bound_dz), 1, u_bound_dx, 1, u_bound_dz, stabs, X_matrix, Z_matrix, missing, - missing, signs, X_signs, Z_signs, char_vec, missing, over_comp, stabs_stand, stand_r, - stand_k, P_stand, missing, missing) + return GraphStateStabilizerCSS( + F, + n, + 0, + missing, + missing, + missing, + 1, + min(u_bound_dx, u_bound_dz), + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + X_matrix, + Z_matrix, + missing, + missing, + signs, + X_signs, + Z_signs, + char_vec, + missing, + over_comp, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) end end -CSSCode(X_matrix::T, Z_matrix::T; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) where T <: CTMatrixTypes = StabilizerCodeCSS(X_matrix, Z_matrix, - char_vec = char_vec, logs_alg = logs_alg) +CSSCode( + X_matrix::T, + Z_matrix::T; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:CTMatrixTypes} = + StabilizerCodeCSS(X_matrix, Z_matrix, char_vec = char_vec, logs_alg = logs_alg) """ StabilizerCodeCSS(S_Pauli::Vector{T}; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, logs_alg::Symbol = :stnd_frm) where T <: Union{String, Vector{Char}} @@ -265,27 +524,38 @@ Return the CSS code whose stabilizers are determined by the vector of Pauli stri * Any +/- 1 characters in front of each stabilizer are stripped. No check is done to make sure these signs agree with the ones computed using the character vector. """ -function StabilizerCodeCSS(S_Pauli::Vector{T}; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) where T <: Union{String, Vector{Char}} - - logs_alg ∈ [:stnd_frm, :VS, :sys_eqs] || throw(ArgumentError("Unrecognized logicals algorithm")) +function StabilizerCodeCSS( + S_Pauli::Vector{T}; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:Union{String,Vector{Char}}} + + logs_alg ∈ [:stnd_frm, :VS, :sys_eqs] || + throw(ArgumentError("Unrecognized logicals algorithm")) stabs = _Pauli_string_to_symplectic(_process_strings(S_Pauli)) - iszero(stabs) && throw(ArgumentError("The processed Pauli strings returned a set of empty stabilizer generators.")) + iszero(stabs) && throw( + ArgumentError( + "The processed Pauli strings returned a set of empty stabilizer generators.", + ), + ) stabs = _remove_empty(stabs, :rows) # the reason we repeat here and not call another constructor is the else # statement at the bottom of this function # would also need to compute down to signs to call _is_CSS_symplectic # which would allow us to call the other constructor - are_symplectic_orthogonal(stabs, stabs) || throw(ArgumentError("The given stabilizers are not symplectic orthogonal.")) - + are_symplectic_orthogonal(stabs, stabs) || + throw(ArgumentError("The given stabilizers are not symplectic orthogonal.")) + n = div(ncols(stabs), 2) stabs_stand, P_stand, stand_r, stand_k, rnk = _standard_form_stabilizer(stabs) if !iszero(stand_k) if logs_alg == :stnd_frm - logs = _make_pairs(_logicals_standard_form(stabs_stand, n, stand_k, stand_r, P_stand)) - logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i in 1:length(logs)]) + logs = _make_pairs( + _logicals_standard_form(stabs_stand, n, stand_k, stand_r, P_stand), + ) + logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i = 1:length(logs)]) else - H = kernel(hcat(stabs[:, n + 1:end], -stabs[:, 1:n]), side = :right) + H = kernel(hcat(stabs[:, (n+1):end], -stabs[:, 1:n]), side = :right) rnk_H = rank(H) if ncols(H) == rnk_H H_tr = transpose(H) @@ -293,8 +563,8 @@ function StabilizerCodeCSS(S_Pauli::Vector{T}; char_vec::Union{Vector{zzModRingE # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(H) H_tr = zero_matrix(base_ring(H), rnk_H, nr) - for r in 1:nr - for c in 1:rnk_H + for r = 1:nr + for c = 1:rnk_H !iszero(H[r, c]) && (H_tr[c, r] = H[r, c];) end end @@ -319,18 +589,51 @@ function StabilizerCodeCSS(S_Pauli::Vector{T}; char_vec::Union{Vector{zzModRingE isinteger(dim_code) && (dim_code = round(Int, log(BigInt(p), dim_code));) X_logs = reduce(vcat, [log[1][:, 1:n] for log in logs]) - Z_logs = reduce(vcat, [log[2][:, n + 1:end] for log in logs]) + Z_logs = reduce(vcat, [log[2][:, (n+1):end] for log in logs]) _, mat = rref(vcat(args[2], X_logs)) anti = _remove_empty(mat, :rows) * transpose(Z_logs) - u_bound_dx, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dx, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) _, mat = rref(vcat(args[4], Z_logs)) anti = _remove_empty(mat, :rows) * transpose(X_logs) - u_bound_dz, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - return StabilizerCodeCSS(F, n, dim_code, missing, missing, missing, 1, min(u_bound_dx, - u_bound_dz), 1, u_bound_dx, 1, u_bound_dz, stabs, args[2], args[4], missing, - missing, signs, args[3], args[5], logs, logs_mat, char_vec, missing, missing, - missing, over_comp, missing, stabs_stand, stand_r, stand_k, P_stand, missing, - missing) + u_bound_dz, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + return StabilizerCodeCSS( + F, + n, + dim_code, + missing, + missing, + missing, + 1, + min(u_bound_dx, u_bound_dz), + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + args[2], + args[4], + missing, + missing, + signs, + args[3], + args[5], + logs, + logs_mat, + char_vec, + missing, + missing, + missing, + over_comp, + missing, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) else # graph state distance is defined to be smallest weight stabilizer _, mat = rref(args[2]) @@ -339,17 +642,47 @@ function StabilizerCodeCSS(S_Pauli::Vector{T}; char_vec::Union{Vector{zzModRingE _, mat = rref(args[4]) mat = _remove_empty(mat, :rows) u_bound_dz, _ = _min_wt_row(mat) - return GraphStateStabilizerCSS(F, n, 0, missing, missing, missing, 1, min(u_bound_dx, - u_bound_dz), 1, u_bound_dx, 1, u_bound_dz, stabs, args[2], args[4], missing, - missing, signs, args[3], args[5], char_vec, missing, over_comp, stabs_stand, - stand_r, stand_k, P_stand, missing, missing) + return GraphStateStabilizerCSS( + F, + n, + 0, + missing, + missing, + missing, + 1, + min(u_bound_dx, u_bound_dz), + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + args[2], + args[4], + missing, + missing, + signs, + args[3], + args[5], + char_vec, + missing, + over_comp, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) end else error("Provided Pauli strings are not CSS.") end end -CSSCode(S_Pauli::Vector{T}; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) where T <: Union{String, Vector{Char}} = +CSSCode( + S_Pauli::Vector{T}; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:Union{String,Vector{Char}}} = StabilizerCodeCSS(S_Pauli, char_vec = char_vec, logs_alg = logs_alg) """ @@ -362,12 +695,12 @@ code `S` using the technique of arXiv:2311.18003. function StabilizerCodeCSS(S::AbstractStabilizerCode; logs_alg::Symbol = :stnd_frm) # correct size, fastest object creation, reset all entries anyway Z = deepcopy(S.stabs) - Z[:, 1:S.n] = S.stabs[:, S.n + 1:2 * S.n] - Z[:, S.n + 1:2 * S.n] = -S.stabs[:, 1:S.n] + Z[:, 1:S.n] = S.stabs[:, (S.n+1):(2*S.n)] + Z[:, (S.n+1):(2*S.n)] = -S.stabs[:, 1:S.n] return CSSCode(S.stabs, Z, logs_alg = logs_alg) end -CSSCode(S::AbstractStabilizerCode; logs_alg::Symbol = :stnd_frm) = StabilizerCodeCSS(S; logs_alg = - logs_alg) +CSSCode(S::AbstractStabilizerCode; logs_alg::Symbol = :stnd_frm) = + StabilizerCodeCSS(S; logs_alg = logs_alg) """ StabilizerCode(S::AbstractStabilizerCode; logs_alg::Symbol = :stnd_frm) @@ -375,16 +708,18 @@ CSSCode(S::AbstractStabilizerCode; logs_alg::Symbol = :stnd_frm) = StabilizerCod Return the `[[n, k, d' <= d]]` stabilizer code from the `[[2n, 2k, d]]` CSS code using the inverse of the technique of arXiv:2311.18003. """ -StabilizerCode(S::T; logs_alg::Symbol = :stnd_frm) where {T <: AbstractStabilizerCode} = +StabilizerCode(S::T; logs_alg::Symbol = :stnd_frm) where {T<:AbstractStabilizerCode} = StabilizerCode(CSSTrait(T), S, logs_alg) function StabilizerCode(::IsCSS, S::AbstractStabilizerCode, logs_alg::Symbol) iseven(S.n) || throw(ArgumentError("Only valid for codes of even length")) - nrows(S.X_stabs) == nrows(S.Z_stabs) || throw(ArgumentError("Requires an equal number of X and Z stabilizers")) + nrows(S.X_stabs) == nrows(S.Z_stabs) || + throw(ArgumentError("Requires an equal number of X and Z stabilizers")) n = div(S.n, 2) return StabilizerCode(hcat(S.X_stabs[:, 1:n], S.Z_stabs[:, 1:n]), logs_alg = logs_alg) end -StabilizerCode(::IsNotCSS, S::AbstractStabilizerCode, logs_alg::Symbol) = throw(ArgumentError("Only valid for CSS codes of even length")) +StabilizerCode(::IsNotCSS, S::AbstractStabilizerCode, logs_alg::Symbol) = + throw(ArgumentError("Only valid for CSS codes of even length")) # entanglement-assisted is not symplectic orthogonal """ @@ -396,12 +731,19 @@ Return the stabilizer code whose stabilizers are determined by the vector of Pau * Any +/- 1 characters in front of each stabilizer are stripped. No check is done to make sure these signs agree with the ones computed using the character vector. """ -function StabilizerCode(S_Pauli::Vector{T}; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) where T <: Union{String, Vector{Char}} +function StabilizerCode( + S_Pauli::Vector{T}; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) where {T<:Union{String,Vector{Char}}} S_Pauli_stripped = _process_strings(S_Pauli) stabs = _Pauli_string_to_symplectic(S_Pauli_stripped) - iszero(stabs) && throw(ArgumentError("The processed Pauli strings returned a set of empty stabilizer generators.")) + iszero(stabs) && throw( + ArgumentError( + "The processed Pauli strings returned a set of empty stabilizer generators.", + ), + ) return StabilizerCode(stabs, char_vec = char_vec, logs_alg = logs_alg) end @@ -410,22 +752,29 @@ end Return the stabilizer code whose stabilizers is determined by `stabs`. """ -function StabilizerCode(stabs::CTMatrixTypes; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :stnd_frm) - - logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || throw(ArgumentError("Unrecognized logicals algorithm")) +function StabilizerCode( + stabs::CTMatrixTypes; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :stnd_frm, +) + + logs_alg ∈ (:stnd_frm, :VS, :sys_eqs) || + throw(ArgumentError("Unrecognized logicals algorithm")) iszero(stabs) && throw(ArgumentError("The stabilizer matrix is empty.")) stabs = _remove_empty(stabs, :rows) - are_symplectic_orthogonal(stabs, stabs) || throw(ArgumentError("The given stabilizers are not symplectic orthogonal.")) - + are_symplectic_orthogonal(stabs, stabs) || + throw(ArgumentError("The given stabilizers are not symplectic orthogonal.")) + n = div(ncols(stabs), 2) stabs_stand, P_stand, stand_r, stand_k, rnk = _standard_form_stabilizer(stabs) if !iszero(stand_k) if logs_alg == :stnd_frm - logs = _make_pairs(_logicals_standard_form(stabs_stand, n, stand_k, stand_r, P_stand)) - logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i in 1:length(logs)]) + logs = _make_pairs( + _logicals_standard_form(stabs_stand, n, stand_k, stand_r, P_stand), + ) + logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i = 1:length(logs)]) else - H = kernel(hcat(stabs[:, n + 1:end], -stabs[:, 1:n]), side = :right) + H = kernel(hcat(stabs[:, (n+1):end], -stabs[:, 1:n]), side = :right) rnk_H = rank(H) if ncols(H) == rnk_H H_tr = transpose(H) @@ -433,8 +782,8 @@ function StabilizerCode(stabs::CTMatrixTypes; char_vec::Union{Vector{zzModRingEl # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(H) H_tr = zero_matrix(base_ring(H), rnk_H, nr) - for r in 1:nr - for c in 1:rnk_H + for r = 1:nr + for c = 1:rnk_H !iszero(H[r, c]) && (H_tr[c, r] = H[r, c];) end end @@ -459,18 +808,51 @@ function StabilizerCode(stabs::CTMatrixTypes; char_vec::Union{Vector{zzModRingEl if args[1] if !iszero(stand_k) X_logs = reduce(vcat, [log[1][:, 1:n] for log in logs]) - Z_logs = reduce(vcat, [log[2][:, n + 1:end] for log in logs]) + Z_logs = reduce(vcat, [log[2][:, (n+1):end] for log in logs]) _, mat = rref(vcat(args[2], X_logs)) anti = _remove_empty(mat, :rows) * transpose(Z_logs) - u_bound_dx, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dx, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) _, mat = rref(vcat(args[4], Z_logs)) anti = _remove_empty(mat, :rows) * transpose(X_logs) - u_bound_dz, _ = _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - return StabilizerCodeCSS(F, n, dim_code, missing, missing, missing, 1, min(u_bound_dx, - u_bound_dz), 1, u_bound_dx, 1, u_bound_dz, stabs, args[2], args[4], missing, - missing, signs, args[3], args[5], logs, logs_mat, char_vec, missing, missing, - missing, over_comp, missing, stabs_stand, stand_r, stand_k, P_stand, missing, - missing) + u_bound_dz, _ = + _min_wt_row(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + return StabilizerCodeCSS( + F, + n, + dim_code, + missing, + missing, + missing, + 1, + min(u_bound_dx, u_bound_dz), + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + args[2], + args[4], + missing, + missing, + signs, + args[3], + args[5], + logs, + logs_mat, + char_vec, + missing, + missing, + missing, + over_comp, + missing, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) else # graph state distance is defined to be smallest weight stabilizer _, mat = rref(args[2]) @@ -479,26 +861,95 @@ function StabilizerCode(stabs::CTMatrixTypes; char_vec::Union{Vector{zzModRingEl _, mat = rref(args[4]) mat = _remove_empty(mat, :rows) u_bound_dz, _ = _min_wt_row(mat) - return GraphStateStabilizerCSS(F, n, 0, missing, missing, missing, 1, min(u_bound_dx, - u_bound_dz), 1, u_bound_dx, 1, u_bound_dz, stabs, args[2], args[4], missing, - missing, signs, args[3], args[5], char_vec, missing, over_comp, stabs_stand, - stand_r, stand_k, P_stand, missing, missing) + return GraphStateStabilizerCSS( + F, + n, + 0, + missing, + missing, + missing, + 1, + min(u_bound_dx, u_bound_dz), + 1, + u_bound_dx, + 1, + u_bound_dz, + stabs, + args[2], + args[4], + missing, + missing, + signs, + args[3], + args[5], + char_vec, + missing, + over_comp, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) end else if !iszero(stand_k) mat = _rref_symp_col_swap(vcat(stabs, logs_mat)) - anti = hcat(logs_mat[:, n + 1:end], -logs_mat[:, 1:n]) * transpose(_remove_empty(mat, :rows)) - u_bound = minimum(row_wts_symplectic(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :])) - return StabilizerCode(F, n, dim_code, missing, 1, u_bound, stabs, logs, logs_mat, - char_vec, signs, missing, missing, missing, over_comp, missing, stabs_stand, - stand_r, stand_k, P_stand, missing) + anti = + hcat(logs_mat[:, (n+1):end], -logs_mat[:, 1:n]) * + transpose(_remove_empty(mat, :rows)) + u_bound = minimum( + row_wts_symplectic( + mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :], + ), + ) + return StabilizerCode( + F, + n, + dim_code, + missing, + 1, + u_bound, + stabs, + logs, + logs_mat, + char_vec, + signs, + missing, + missing, + missing, + over_comp, + missing, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + ) else # graph state distance is defined to be smallest weight stabilizer _, mat = rref(stabs) mat = _remove_empty(mat, :rows) u_bound, _ = _min_wt_row(mat) - return GraphStateStabilizer(F, n, 0, missing, 1, u_bound, stabs, char_vec, signs, - missing, over_comp, stabs_stand, stand_r, stand_k, P_stand, missing) + return GraphStateStabilizer( + F, + n, + 0, + missing, + 1, + u_bound, + stabs, + char_vec, + signs, + missing, + over_comp, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + ) end end end @@ -517,7 +968,7 @@ end # end ############################# - # getter functions +# getter functions ############################# """ @@ -536,36 +987,44 @@ minimum_distance_upper_bound(S::AbstractStabilizerCode) = S.u_bound X_minimum_distance_lower_bound(S::AbstractStabilizerCode) Return the currently stored lower bound on the minimum `X`-distance. """ -X_minimum_distance_lower_bound(S::T) where T <: AbstractStabilizerCode = X_minimum_distance_lower_bound(CSSTrait(T), S) +X_minimum_distance_lower_bound(S::T) where {T<:AbstractStabilizerCode} = + X_minimum_distance_lower_bound(CSSTrait(T), S) X_minimum_distance_lower_bound(::IsCSS, S::AbstractStabilizerCode) = S.l_bound_dx -X_minimum_distance_lower_bound(::IsNotCSS, S::AbstractStabilizerCode) = error("Only valid for CSS codes") +X_minimum_distance_lower_bound(::IsNotCSS, S::AbstractStabilizerCode) = + error("Only valid for CSS codes") """ X_minimum_distance_upper_bound(S::AbstractStabilizerCode) Return the currently stored upper bound on the minimum `X`-distance. """ -X_minimum_distance_upper_bound(S::T) where T <: AbstractStabilizerCode = X_minimum_distance_upper_bound(CSSTrait(T), S) +X_minimum_distance_upper_bound(S::T) where {T<:AbstractStabilizerCode} = + X_minimum_distance_upper_bound(CSSTrait(T), S) X_minimum_distance_upper_bound(::IsCSS, S::AbstractStabilizerCode) = S.u_bound_dx -X_minimum_distance_upper_bound(::IsNotCSS, S::AbstractStabilizerCode) = error("Only valid for CSS codes") +X_minimum_distance_upper_bound(::IsNotCSS, S::AbstractStabilizerCode) = + error("Only valid for CSS codes") """ Z_minimum_distance_lower_bound(S::AbstractStabilizerCode) Return the currently stored lower bound on the minimum `Z`-distance. """ -Z_minimum_distance_lower_bound(S::T) where T <: AbstractStabilizerCode = Z_minimum_distance_lower_bound(CSSTrait(T), S) +Z_minimum_distance_lower_bound(S::T) where {T<:AbstractStabilizerCode} = + Z_minimum_distance_lower_bound(CSSTrait(T), S) Z_minimum_distance_lower_bound(::IsCSS, S::AbstractStabilizerCode) = S.l_bound_dz -Z_minimum_distance_lower_bound(::IsNotCSS, S::AbstractStabilizerCode) = error("Only valid for CSS codes") +Z_minimum_distance_lower_bound(::IsNotCSS, S::AbstractStabilizerCode) = + error("Only valid for CSS codes") """ Z_minimum_distance_upper_bound(S::AbstractStabilizerCode) Return the currently stored upper bound on the minimum `Z`-distance. """ -Z_minimum_distance_upper_bound(S::T) where T <: AbstractStabilizerCode = Z_minimum_distance_upper_bound(CSSTrait(T), S) +Z_minimum_distance_upper_bound(S::T) where {T<:AbstractStabilizerCode} = + Z_minimum_distance_upper_bound(CSSTrait(T), S) Z_minimum_distance_upper_bound(::IsCSS, S::AbstractStabilizerCode) = S.u_bound_dz -Z_minimum_distance_upper_bound(::IsNotCSS, S::AbstractStabilizerCode) = error("Only valid for CSS codes") +Z_minimum_distance_upper_bound(::IsNotCSS, S::AbstractStabilizerCode) = + error("Only valid for CSS codes") ############################# - # setter functions +# setter functions ############################# """ @@ -574,9 +1033,12 @@ Z_minimum_distance_upper_bound(::IsNotCSS, S::AbstractStabilizerCode) = error("O Set the minimum distance of the code to `d`. """ function set_minimum_distance!(S::AbstractStabilizerCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound)") - d < S.l_bound && (@warn "The distance set is less than the current lower bound of $(S.l_bound)") + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound)") + d < S.l_bound && + (@warn "The distance set is less than the current lower bound of $(S.l_bound)") S.d = d S.l_bound = d S.u_bound = d @@ -593,11 +1055,15 @@ end Set the minimum `X`-distance of the code to `d`. """ -set_X_minimum_distance!(S::T, d::Int) where T <: AbstractStabilizerCode = set_X_minimum_distance!(CSSTrait(T), S, d) +set_X_minimum_distance!(S::T, d::Int) where {T<:AbstractStabilizerCode} = + set_X_minimum_distance!(CSSTrait(T), S, d) function set_X_minimum_distance!(::IsCSS, S::AbstractStabilizerCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound_dx < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dx)") - d < S.l_bound_dx && (@warn "The distance set is less than the current lower bound of $(S.l_bound_dx)") + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound_dx < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dx)") + d < S.l_bound_dx && + (@warn "The distance set is less than the current lower bound of $(S.l_bound_dx)") S.dx = d S.l_bound_dx = d S.u_bound_dx = d @@ -619,11 +1085,15 @@ set_X_minimum_distance!(::IsNotCSS, S::AbstractStabilizerCode, d::Int) = Set the minimum `Z`-distance of the code to `d`. """ -set_Z_minimum_distance!(S::T, d::Int) where T <: AbstractStabilizerCode = set_Z_minimum_distance!(CSSTrait(T), S, d) +set_Z_minimum_distance!(S::T, d::Int) where {T<:AbstractStabilizerCode} = + set_Z_minimum_distance!(CSSTrait(T), S, d) function set_Z_minimum_distance!(::IsCSS, S::AbstractStabilizerCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound_dz < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dz)") - d < S.l_bound_dz && (@warn "The distance set is less than the current lower bound of $(S.l_bound_dz)") + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound_dz < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dz)") + d < S.l_bound_dz && + (@warn "The distance set is less than the current lower bound of $(S.l_bound_dz)") S.dz = d S.l_bound_dz = d S.u_bound_dz = d @@ -641,19 +1111,24 @@ set_Z_minimum_distance!(::IsNotCSS, S::AbstractStabilizerCode, d::Int) = error("Only valid for CSS codes") ############################# - # general functions +# general functions ############################# -function _logicals(stabs::T, dual_gens::T, logs_alg::Symbol = :sys_eqs) where {T <: CTMatrixTypes} +function _logicals( + stabs::T, + dual_gens::T, + logs_alg::Symbol = :sys_eqs, +) where {T<:CTMatrixTypes} logs_alg ∈ [:sys_eqs, :VS] || throw(ArgumentError("Unrecognized logicals algorithm")) L = _quotient_space(dual_gens, stabs, logs_alg) logs = _make_pairs(L) # verify n = div(ncols(L), 2) - logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i in 1:length(logs)]) - are_symplectic_orthogonal(stabs, logs_mat) || error("Computed logicals do not commute with the codespace.") - prod = hcat(logs_mat[:, n + 1:end], -logs_mat[:, 1:n]) * transpose(logs_mat) + logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i = 1:length(logs)]) + are_symplectic_orthogonal(stabs, logs_mat) || + error("Computed logicals do not commute with the codespace.") + prod = hcat(logs_mat[:, (n+1):end], -logs_mat[:, 1:n]) * transpose(logs_mat) sum(_Flint_matrix_to_Julia_int_matrix(prod), dims = 1) == ones(Int, 1, size(prod, 1)) || error("Computed logicals do not have the right commutation relations.") return logs, logs_mat @@ -668,9 +1143,9 @@ function random_CSS_code(n::Int, k::Int) d = _rand_single_sector_boundary(n, k) dt = transpose(d) Xrref = rref(dt) - Xind = [findfirst(!iszero, Xrref[2][i, :])[2] for i in 1:Xrref[1]] + Xind = [findfirst(!iszero, Xrref[2][i, :])[2] for i = 1:Xrref[1]] Zrref = rref(d) - Zind = [findfirst(!iszero, Zrref[2][i, :])[2] for i in 1:Zrref[1]] + Zind = [findfirst(!iszero, Zrref[2][i, :])[2] for i = 1:Zrref[1]] return CSSCode(d[Xind, :], dt[Zind, :]) end @@ -679,17 +1154,17 @@ end Return `true` if `S` is a CSS-T code. """ -is_CSS_T_code(S::AbstractStabilizerCode; verbose::Bool = false) = is_CSS_T_code(CSSTrait( - typeof(S)), S; verbose = verbose) +is_CSS_T_code(S::AbstractStabilizerCode; verbose::Bool = false) = + is_CSS_T_code(CSSTrait(typeof(S)), S; verbose = verbose) function is_CSS_T_code(::IsCSS, S::AbstractStabilizerCode; verbose::Bool = false) C_X = LinearCode(S.X_stabs) # C_2 C_Z = LinearCode(S.Z_stabs) # dual(C_1) - + num_thrds = Threads.nthreads() verbose && println("Detected $num_thrds threads.") # should probably floor some logs here power = 0 - for i in 1:20 + for i = 1:20 if 2^i > num_thrds power = i - 1 break @@ -701,10 +1176,10 @@ function is_CSS_T_code(::IsCSS, S::AbstractStabilizerCode; verbose::Bool = false k = C_X.k z = zeros(Int, n) G = _Flint_matrix_to_Julia_int_matrix(transpose(C_X.G)) - for r in 1:k + for r = 1:k verbose && println("r: $r") flag = Threads.Atomic{Bool}(true) - Threads.@threads for m in 1:num_thrds # + Threads.@threads for m = 1:num_thrds # # println("here") c = deepcopy(z) # prefix = digits(m - 1, base = 2, pad = power) @@ -717,11 +1192,11 @@ function is_CSS_T_code(::IsCSS, S::AbstractStabilizerCode; verbose::Bool = false LinearAlgebra.mul!(c, G, u) wt_c = 0 supp_c = Int[] - @inbounds for j in 1:n + @inbounds for j = 1:n c[j] % p != 0 && (wt_c += 1; append!(supp_c, j);) end - # for binary codes we can do this with a homomorphism, but this is non-linear for q-ary + # for binary codes we can do this with a homomorphism, but this is non-linear for q-ary # since we have to enumerate the codes anyway, we might as well just do this # note, this is not even-like for q-ary if !iseven(wt_c) diff --git a/src/Quantum/subsystem_code.jl b/src/Quantum/subsystem_code.jl index 57b68d3a..7b8afebc 100644 --- a/src/Quantum/subsystem_code.jl +++ b/src/Quantum/subsystem_code.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# """ @@ -13,8 +13,11 @@ Return the subsystem code whose gauge group is determined by `G`. """ -function SubsystemCode(G::CTMatrixTypes; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :sys_eqs) +function SubsystemCode( + G::CTMatrixTypes; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :sys_eqs, +) logs_alg ∈ (:sys_eqs, :VS) || throw(ArgumentError("Unrecognized logicals algorithm")) iszero(G) && throw(ArgumentError("The gauge matrix is empty.")) @@ -34,7 +37,7 @@ function SubsystemCode(G::CTMatrixTypes; char_vec::Union{Vector{zzModRingElem}, # dressed operators = < logs, gauge ops > # stabilizer group: ker G ∩ G - ker_G = kernel(hcat(G[:, n + 1:end], -G[:, 1:n]), side = :right) + ker_G = kernel(hcat(G[:, (n+1):end], -G[:, 1:n]), side = :right) rnk_ker_G = rank(ker_G) if ncols(ker_G) == rnk_ker_G ker_G = transpose(ker_G) @@ -42,23 +45,28 @@ function SubsystemCode(G::CTMatrixTypes; char_vec::Union{Vector{zzModRingElem}, # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(ker_G) ker_G_tr = zero_matrix(base_ring(ker_G), rnk_ker_G, nr) - for r in 1:nr - for c in 1:rnk_ker_G + for r = 1:nr + for c = 1:rnk_ker_G !iszero(ker_G[r, c]) && (ker_G_tr[c, r] = ker_G[r, c];) end end ker_G = ker_G_tr end V = vector_space(base_ring(G), ncols(ker_G)) - ker_G_VS, ker_G_to_V = sub(V, [V(ker_G[i, :]) for i in 1:nrows(ker_G)]) - G_VS, _ = sub(V, [V(G[i, :]) for i in 1:nrows(G)]) + ker_G_VS, ker_G_to_V = sub(V, [V(ker_G[i, :]) for i = 1:nrows(ker_G)]) + G_VS, _ = sub(V, [V(G[i, :]) for i = 1:nrows(G)]) I, I_to_ker_G = intersect(ker_G_VS, G_VS) if !iszero(AbstractAlgebra.dim(I)) I_basis = [ker_G_to_V(I_to_ker_G(g)) for g in gens(I)] - F_basis = [[F(I_basis[j][i]) for i in 1:AbstractAlgebra.dim(parent(I_basis[1]))] for j in 1:length(I_basis)] + F_basis = [ + [F(I_basis[j][i]) for i = 1:AbstractAlgebra.dim(parent(I_basis[1]))] for + j = 1:length(I_basis) + ] stabs = matrix(F, length(F_basis), 2 * n, reduce(vcat, F_basis)) else - error("Error computing the stabilizer group of the subsystem code; ker G ∩ G has dimension zero.") + error( + "Error computing the stabilizer group of the subsystem code; ker G ∩ G has dimension zero.", + ) end # check if this subsystem code is really a stabilizer code @@ -78,32 +86,42 @@ function SubsystemCode(G::CTMatrixTypes; char_vec::Union{Vector{zzModRingElem}, if !iszero(BL) bare_logs = _make_pairs(BL) # verify - bare_logs_mat = reduce(vcat, [reduce(vcat, bare_logs[i]) for i in 1:length(bare_logs)]) - are_symplectic_orthogonal(stabs, bare_logs_mat) || error("Computed logicals do not commute with the codespace.") - prod = hcat(bare_logs_mat[:, n + 1:end], -bare_logs_mat[:, 1:n]) * transpose(bare_logs_mat) - sum(_Flint_matrix_to_Julia_int_matrix(prod), dims=1) == ones(Int, 1, size(prod, 1)) || error("Computed logicals do not have the right commutation relations.") + bare_logs_mat = + reduce(vcat, [reduce(vcat, bare_logs[i]) for i = 1:length(bare_logs)]) + are_symplectic_orthogonal(stabs, bare_logs_mat) || + error("Computed logicals do not commute with the codespace.") + prod = + hcat(bare_logs_mat[:, (n+1):end], -bare_logs_mat[:, 1:n]) * + transpose(bare_logs_mat) + sum(_Flint_matrix_to_Julia_int_matrix(prod), dims = 1) == + ones(Int, 1, size(prod, 1)) || + error("Computed logicals do not have the right commutation relations.") else graph_state = true end - + # gauge operators (reps): G / S # this can't be zero if S != G GO = _quotient_space(G, stabs, logs_alg) gauge_ops = _make_pairs(GO) # verify - gauge_ops_mat = reduce(vcat, [reduce(vcat, gauge_ops[i]) for i in 1:length(gauge_ops)]) - are_symplectic_orthogonal(stabs, gauge_ops_mat) || error("Computed gauge operators do not commute with the codespace.") + gauge_ops_mat = reduce(vcat, [reduce(vcat, gauge_ops[i]) for i = 1:length(gauge_ops)]) + are_symplectic_orthogonal(stabs, gauge_ops_mat) || + error("Computed gauge operators do not commute with the codespace.") if !graph_state - are_symplectic_orthogonal(bare_logs_mat, gauge_ops_mat) || error("Computed gauge operators do not commute with the computed logicals.") + are_symplectic_orthogonal(bare_logs_mat, gauge_ops_mat) || + error("Computed gauge operators do not commute with the computed logicals.") end - prod = hcat(gauge_ops_mat[:, n + 1:end], -gauge_ops_mat[:, 1:n]) * transpose(gauge_ops_mat) - sum(_Flint_matrix_to_Julia_int_matrix(prod), dims=1) == ones(Int, 1, size(prod, 1)) || error("Computed gauge operators do not have the right commutation relations.") + prod = + hcat(gauge_ops_mat[:, (n+1):end], -gauge_ops_mat[:, 1:n]) * transpose(gauge_ops_mat) + sum(_Flint_matrix_to_Julia_int_matrix(prod), dims = 1) == ones(Int, 1, size(prod, 1)) || + error("Computed gauge operators do not have the right commutation relations.") # since S is computed, it automatically has full rank and is not overcomplete # q^n / p^k but rows is n - k top = BigInt(order(F))^n r = length(gauge_ops) - k = top // BigInt(p)^(nrows(stabs) + r) + k = top // BigInt(p)^(nrows(stabs) + r) isinteger(k) && (k = round(Int, log(BigInt(p), k));) # r = top // BigInt(p)^length(gauge_ops) # isinteger(r) && (r = round(Int, log(BigInt(p), r));) @@ -123,44 +141,128 @@ function SubsystemCode(G::CTMatrixTypes; char_vec::Union{Vector{zzModRingElem}, u_bound_dz_bare, _ = _min_wt_row(Z_mat) # dressed - _, X_mat = rref(vcat(X_mat, reduce(vcat, [log[1][:, 1:n] for log in gauge_ops]))) + _, X_mat = + rref(vcat(X_mat, reduce(vcat, [log[1][:, 1:n] for log in gauge_ops]))) X_mat = _remove_empty(X_mat, :rows) u_bound_dx_dressed, _ = _min_wt_row(X_mat) - _, Z_mat = rref(vcat(Z_mat, reduce(vcat, [log[2][:, n + 1:end] for log in gauge_ops]))) + _, Z_mat = + rref(vcat(Z_mat, reduce(vcat, [log[2][:, (n+1):end] for log in gauge_ops]))) Z_mat = _remove_empty(Z_mat, :rows) u_bound_dz_dressed, _ = _min_wt_row(Z_mat) - return GraphStateSubsystemCSS(F, n, 0, r, missing, missing, missing, missing, missing, - missing, 1, min(u_bound_dx_bare, u_bound_dz_bare), 1, min(u_bound_dx_dressed, - u_bound_dz_dressed), 1, u_bound_dx_bare, 1, u_bound_dz_bare, 1, u_bound_dx_dressed, 1, u_bound_dz_dressed, stabs, args[2], - args[4], missing, missing, signs, args[3], args[5], char_vec, missing, false, - gauge_ops, gauge_ops_mat, stabs_stand, stand_r, stand_k, P_stand, missing, missing) + return GraphStateSubsystemCSS( + F, + n, + 0, + r, + missing, + missing, + missing, + missing, + missing, + missing, + 1, + min(u_bound_dx_bare, u_bound_dz_bare), + 1, + min(u_bound_dx_dressed, u_bound_dz_dressed), + 1, + u_bound_dx_bare, + 1, + u_bound_dz_bare, + 1, + u_bound_dx_dressed, + 1, + u_bound_dz_dressed, + stabs, + args[2], + args[4], + missing, + missing, + signs, + args[3], + args[5], + char_vec, + missing, + false, + gauge_ops, + gauge_ops_mat, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) else # bare X_logs = reduce(vcat, [log[1][:, 1:n] for log in bare_logs]) - Z_logs = reduce(vcat, [log[2][:, n + 1:end] for log in bare_logs]) + Z_logs = reduce(vcat, [log[2][:, (n+1):end] for log in bare_logs]) _, X_mat = rref(vcat(args[2], X_logs)) anti = _remove_empty(X_mat, :rows) * transpose(Z_logs) - u_bound_dx_bare, _ = _min_wt_row(X_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dx_bare, _ = + _min_wt_row(X_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) _, Z_mat = rref(vcat(args[4], Z_logs)) anti = _remove_empty(Z_mat, :rows) * transpose(X_logs) - u_bound_dz_bare, _ = _min_wt_row(Z_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dz_bare, _ = + _min_wt_row(Z_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) # dressed - _, X_mat = rref(vcat(X_mat, reduce(vcat, [log[1][:, 1:n] for log in gauge_ops]))) + _, X_mat = + rref(vcat(X_mat, reduce(vcat, [log[1][:, 1:n] for log in gauge_ops]))) anti = _remove_empty(X_mat, :rows) * transpose(Z_logs) - u_bound_dx_dressed, _ = _min_wt_row(X_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - _, Z_mat = rref(vcat(Z_mat, reduce(vcat, [log[2][:, n + 1:end] for log in gauge_ops]))) + u_bound_dx_dressed, _ = + _min_wt_row(X_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + _, Z_mat = + rref(vcat(Z_mat, reduce(vcat, [log[2][:, (n+1):end] for log in gauge_ops]))) anti = _remove_empty(Z_mat, :rows) * transpose(X_logs) - u_bound_dz_dressed, _ =_min_wt_row(Z_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - return SubsystemCodeCSS(F, n, k, r, missing, missing, missing, missing, missing, - missing, 1, min(u_bound_dx_bare, u_bound_dz_bare), 1, min(u_bound_dx_dressed, - u_bound_dz_dressed), 1, u_bound_dx_bare, 1, u_bound_dz_bare, 1, u_bound_dx_dressed, 1, u_bound_dz_dressed, stabs, args[2], - args[4], missing, missing, signs, args[3], args[5], bare_logs, bare_logs_mat, - char_vec, gauge_ops, gauge_ops_mat, false, stabs_stand, stand_r, stand_k, P_stand, - missing, missing) + u_bound_dz_dressed, _ = + _min_wt_row(Z_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + return SubsystemCodeCSS( + F, + n, + k, + r, + missing, + missing, + missing, + missing, + missing, + missing, + 1, + min(u_bound_dx_bare, u_bound_dz_bare), + 1, + min(u_bound_dx_dressed, u_bound_dz_dressed), + 1, + u_bound_dx_bare, + 1, + u_bound_dz_bare, + 1, + u_bound_dx_dressed, + 1, + u_bound_dz_dressed, + stabs, + args[2], + args[4], + missing, + missing, + signs, + args[3], + args[5], + bare_logs, + bare_logs_mat, + char_vec, + gauge_ops, + gauge_ops_mat, + false, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) end - # if not CSS code + # if not CSS code else if graph_state # graph state distance is defined to be smallest weight stabilizer @@ -172,23 +274,78 @@ function SubsystemCode(G::CTMatrixTypes; char_vec::Union{Vector{zzModRingElem}, # dressed _, mat = _remove_empty(_rref_symp_col_swap(vcat(mat, gauge_ops_mat)), :rows) u_bound_dressed, _ = _min_wt_row(mat) - return GraphStateSubsystem(F, n, 0, r, missing, missing, 1, u_bound_bare, 1, - u_bound_dressed, stabs, char_vec, signs, missing, false, gauge_ops, gauge_ops_mat, - stabs_stand, stand_r, stand_k, P_stand, missing) + return GraphStateSubsystem( + F, + n, + 0, + r, + missing, + missing, + 1, + u_bound_bare, + 1, + u_bound_dressed, + stabs, + char_vec, + signs, + missing, + false, + gauge_ops, + gauge_ops_mat, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + ) else # bare # TODO use ! versions throughout after vcats _, mat = _remove_empty(_rref_symp_col_swap(vcat(stabs, bare_logs)), :rows) - anti = hcat(logs_mat[:, n + 1:end], -logs_mat[:, 1:n]) * transpose(_remove_empty(mat, :rows)) - u_bound_bare, _ = minimum(row_wts_symplectic(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :])) + anti = + hcat(logs_mat[:, (n+1):end], -logs_mat[:, 1:n]) * + transpose(_remove_empty(mat, :rows)) + u_bound_bare, _ = minimum( + row_wts_symplectic( + mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :], + ), + ) # dressed _, mat = _remove_empty(_rref_symp_col_swap(vcat(mat, gauge_ops_mat)), :rows) - anti = hcat(logs_mat[:, n + 1:end], -logs_mat[:, 1:n]) * transpose(_remove_empty(mat, :rows)) - u_bound_dressed, _ = minimum(row_wts_symplectic(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :])) - return SubsystemCode(F, n, k, r, missing, missing, 1, u_bound_bare, 1, u_bound_dressed, - stabs, signs, bare_logs, bare_logs_mat, char_vec, gauge_ops, gauge_ops_mat, false, - stabs_stand, stand_r, stand_k, P_stand, missing) + anti = + hcat(logs_mat[:, (n+1):end], -logs_mat[:, 1:n]) * + transpose(_remove_empty(mat, :rows)) + u_bound_dressed, _ = minimum( + row_wts_symplectic( + mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :], + ), + ) + return SubsystemCode( + F, + n, + k, + r, + missing, + missing, + 1, + u_bound_bare, + 1, + u_bound_dressed, + stabs, + signs, + bare_logs, + bare_logs_mat, + char_vec, + gauge_ops, + gauge_ops_mat, + false, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + ) end end end @@ -202,13 +359,17 @@ Return the subsystem code whose gauge group is determined by the vector of Pauli * Any +/- 1 characters in front of each stabilizer are stripped. No check is done to make sure these signs agree with the ones computed using the character vector. """ -function SubsystemCode(G_Pauli::Vector{T}; char_vec::Union{Vector{zzModRingElem}, Missing} = missing, - logs_alg::Symbol = :sys_eqs) where T <: Union{String, Vector{Char}} +function SubsystemCode( + G_Pauli::Vector{T}; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, + logs_alg::Symbol = :sys_eqs, +) where {T<:Union{String,Vector{Char}}} logs_alg ∈ (:sys_eqs, :VS) || throw(ArgumentError("Unrecognized logicals algorithm")) G_Pauli_stripped = _process_strings(G_Pauli) G = _Pauli_string_to_symplectic(G_Pauli_stripped) - iszero(G) && error("The processed Pauli strings returned a set of empty gauge group generators.") + iszero(G) && + error("The processed Pauli strings returned a set of empty gauge group generators.") return SubsystemCode(G, char_vec = char_vec, logs_alg = logs_alg) end @@ -218,14 +379,19 @@ end Return the subsystem code whose stabilizers are given by `S`, (bare) logical operators by `L`, gauge operators (not including stabilizers) by `G`. """ -function SubsystemCode(S::CTMatrixTypes, L::CTMatrixTypes, G::CTMatrixTypes; - char_vec::Union{Vector{zzModRingElem}, Missing} = missing) +function SubsystemCode( + S::CTMatrixTypes, + L::CTMatrixTypes, + G::CTMatrixTypes; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, +) iszero(S) && error("The stabilizer matrix is empty.") S = _remove_empty(S, :rows) n = div(ncols(S), 2) # check S commutes with itself - are_symplectic_orthogonal(S, S) || error("The given stabilizers are not symplectic orthogonal.") + are_symplectic_orthogonal(S, S) || + error("The given stabilizers are not symplectic orthogonal.") stabs_stand, P_stand, stand_r, stand_k, rnk = _standard_form_stabilizer(S) # logicals @@ -234,16 +400,16 @@ function SubsystemCode(S::CTMatrixTypes, L::CTMatrixTypes, G::CTMatrixTypes; # check S commutes with L are_symplectic_orthogonal(S, L) || error("Logicals do not commute with the code.") # check L doesn't commute with itself - prod = hcat(L[:, n + 1:end], -L[:, 1:n]) * transpose(L) + prod = hcat(L[:, (n+1):end], -L[:, 1:n]) * transpose(L) iszero(prod) && error("Logicals should not be symplectic self-orthogonal.") # check L is properly in pairs nc_pr = ncols(prod) # need an integer sum and this is cheaper than Nemo.ZZ prod_Jul = _Flint_matrix_to_Julia_int_matrix(prod) - cols = [sum(prod_Jul[:, i]) for i in 1:nc_pr] + cols = [sum(prod_Jul[:, i]) for i = 1:nc_pr] sum(cols) == nc_pr || println("Detected logicals not in anticommuting pairs.") log_pairs = _make_pairs(L) - logs_mat = reduce(vcat, [reduce(vcat, log_pairs[i]) for i in 1:length(log_pairs)]) + logs_mat = reduce(vcat, [reduce(vcat, log_pairs[i]) for i = 1:length(log_pairs)]) # gauge operators iszero(G) && error("The gauges are empty.") @@ -251,19 +417,20 @@ function SubsystemCode(S::CTMatrixTypes, L::CTMatrixTypes, G::CTMatrixTypes; # check S commutes with G are_symplectic_orthogonal(S, G) || error("Gauges do not commute with the code.") # check L commutes with G - are_symplectic_orthogonal(logs_mat, G) || error("Gauges do not commute with the logicals.") + are_symplectic_orthogonal(logs_mat, G) || + error("Gauges do not commute with the logicals.") # check G doesn't commute with itself - prod = hcat(G[:, n + 1:end], -G[:, 1:n]) * transpose(G) + prod = hcat(G[:, (n+1):end], -G[:, 1:n]) * transpose(G) iszero(prod) && error("Gauges should not be symplectic self-orthogonal.") # check G is properly in pairs nc_pr = ncols(prod) # need an integer sum and this is cheaper than Nemo.ZZ prod_Jul = _Flint_matrix_to_Julia_int_matrix(prod) - cols = [sum(prod_Jul[:, i]) for i in 1:nc_pr] + cols = [sum(prod_Jul[:, i]) for i = 1:nc_pr] sum(cols) == nc_pr || println("Detected gauges not in anticommuting pairs.") # display(prod) g_ops_pairs = _make_pairs(G) - g_ops_mat = reduce(vcat, [reduce(vcat, g_ops_pairs[i]) for i in 1:length(g_ops_pairs)]) + g_ops_mat = reduce(vcat, [reduce(vcat, g_ops_pairs[i]) for i = 1:length(g_ops_pairs)]) F = base_ring(g_ops_mat) p = Int(characteristic(F)) @@ -275,7 +442,7 @@ function SubsystemCode(S::CTMatrixTypes, L::CTMatrixTypes, G::CTMatrixTypes; top = BigInt(order(F))^n # TODO: handle overcompleteness in inputs r = div(rnk_G, 2) - k = top // BigInt(p)^(rnk + r) + k = top // BigInt(p)^(rnk + r) isinteger(k) && (k = round(Int, log(BigInt(p), k));) signs = _determine_signs(S, char_vec) @@ -283,39 +450,117 @@ function SubsystemCode(S::CTMatrixTypes, L::CTMatrixTypes, G::CTMatrixTypes; if args[1] # bare X_logs = reduce(vcat, [log[1][:, 1:n] for log in log_pairs]) - Z_logs = reduce(vcat, [log[2][:, n + 1:end] for log in log_pairs]) + Z_logs = reduce(vcat, [log[2][:, (n+1):end] for log in log_pairs]) _, X_mat = rref(vcat(args[2], X_logs)) anti = _remove_empty(X_mat, :rows) * transpose(Z_logs) - u_bound_dx_bare, _ = _min_wt_row(X_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dx_bare, _ = + _min_wt_row(X_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) _, Z_mat = rref(vcat(args[4], Z_logs)) anti = _remove_empty(Z_mat, :rows) * transpose(X_logs) - u_bound_dz_bare, _ = _min_wt_row(Z_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + u_bound_dz_bare, _ = + _min_wt_row(Z_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) # dressed _, X_mat = rref(vcat(X_mat, reduce(vcat, [log[1][:, 1:n] for log in g_ops_pairs]))) anti = _remove_empty(X_mat, :rows) * transpose(Z_logs) - u_bound_dx_dressed, _ = _min_wt_row(X_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - _, Z_mat = rref(vcat(Z_mat, reduce(vcat, [log[2][:, n + 1:end] for log in g_ops_pairs]))) + u_bound_dx_dressed, _ = + _min_wt_row(X_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + _, Z_mat = + rref(vcat(Z_mat, reduce(vcat, [log[2][:, (n+1):end] for log in g_ops_pairs]))) anti = _remove_empty(Z_mat, :rows) * transpose(X_logs) - u_bound_dz_dressed, _ =_min_wt_row(Z_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) - return SubsystemCodeCSS(F, n, k, r, missing, missing, missing, missing, missing, - missing, 1, min(u_bound_dx_bare, u_bound_dz_bare), 1, min(u_bound_dx_dressed, - u_bound_dz_dressed), 1, u_bound_dx_bare, 1, u_bound_dz_bare, 1, u_bound_dx_dressed, 1, u_bound_dz_dressed, S, args[2], args[4], missing, missing, signs, - args[3], args[5], log_pairs, logs_mat, char_vec, g_ops_pairs, g_ops_mat, false, - stabs_stand, stand_r, stand_k, P_stand, missing, missing) + u_bound_dz_dressed, _ = + _min_wt_row(Z_mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :]) + return SubsystemCodeCSS( + F, + n, + k, + r, + missing, + missing, + missing, + missing, + missing, + missing, + 1, + min(u_bound_dx_bare, u_bound_dz_bare), + 1, + min(u_bound_dx_dressed, u_bound_dz_dressed), + 1, + u_bound_dx_bare, + 1, + u_bound_dz_bare, + 1, + u_bound_dx_dressed, + 1, + u_bound_dz_dressed, + S, + args[2], + args[4], + missing, + missing, + signs, + args[3], + args[5], + log_pairs, + logs_mat, + char_vec, + g_ops_pairs, + g_ops_mat, + false, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + missing, + ) else # bare _, mat = _remove_empty(_rref_symp_col_swap(vcat(stabs, bare_logs)), :rows) - anti = hcat(logs_mat[:, n + 1:end], -logs_mat[:, 1:n]) * transpose(_remove_empty(mat, :rows)) - u_bound_bare, _ = minimum(row_wts_symplectic(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :])) + anti = + hcat(logs_mat[:, (n+1):end], -logs_mat[:, 1:n]) * + transpose(_remove_empty(mat, :rows)) + u_bound_bare, _ = minimum( + row_wts_symplectic( + mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :], + ), + ) # dressed _, mat = _remove_empty(_rref_symp_col_swap(vcat(mat, gauge_ops_mat)), :rows) - anti = hcat(logs_mat[:, n + 1:end], -logs_mat[:, 1:n]) * transpose(_remove_empty(mat, :rows)) - u_bound_dressed, _ = minimum(row_wts_symplectic(mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :])) - return SubsystemCode(F, n, k, r, missing, missing, 1, u_bound_bare, 1, u_bound_dressed, S, - signs, log_pairs, logs_mat, char_vec, g_ops_pairs, g_ops_mat, false, stabs_stand, - stand_r, stand_k, P_stand, missing) + anti = + hcat(logs_mat[:, (n+1):end], -logs_mat[:, 1:n]) * + transpose(_remove_empty(mat, :rows)) + u_bound_dressed, _ = minimum( + row_wts_symplectic( + mat[findall(!iszero(anti[i:i, :]) for i in axes(anti, 1)), :], + ), + ) + return SubsystemCode( + F, + n, + k, + r, + missing, + missing, + 1, + u_bound_bare, + 1, + u_bound_dressed, + S, + signs, + log_pairs, + logs_mat, + char_vec, + g_ops_pairs, + g_ops_mat, + false, + stabs_stand, + stand_r, + stand_k, + P_stand, + missing, + ) end end @@ -326,15 +571,22 @@ end Return the subsystem code whose stabilizers are given by the vectors of Pauli strings `S_Pauli`, (bare) logical operators by `L_Pauli`, gauge operators (not including stabilizers) by `G_Pauli`. """ -function SubsystemCode(S_Pauli::Vector{T}, L_Pauli::Vector{T}, G_Pauli::Vector{T}; - char_vec::Union{Vector{zzModRingElem}, Missing} = missing) where T <: Union{String, Vector{Char}} +function SubsystemCode( + S_Pauli::Vector{T}, + L_Pauli::Vector{T}, + G_Pauli::Vector{T}; + char_vec::Union{Vector{zzModRingElem},Missing} = missing, +) where {T<:Union{String,Vector{Char}}} S = _Pauli_string_to_symplectic(_process_strings(S_Pauli)) - iszero(S) && error("The processed Pauli strings returned a set of empty stabilizer generators.") + iszero(S) && + error("The processed Pauli strings returned a set of empty stabilizer generators.") L = _Pauli_string_to_symplectic(_process_strings(L_Pauli)) - iszero(L) && error("The processed Pauli strings returned a set of empty logical generators.") + iszero(L) && + error("The processed Pauli strings returned a set of empty logical generators.") G = _Pauli_string_to_symplectic(_process_strings(G_Pauli)) - iszero(G) && error("The processed Pauli strings returned a set of empty gauge group generators.") + iszero(G) && + error("The processed Pauli strings returned a set of empty gauge group generators.") return SubsystemCode(S, L, G, char_vec = char_vec) end @@ -342,7 +594,7 @@ end # min dist is min dressed logical operator weight ############################# - # getter functions +# getter functions ############################# """ @@ -394,7 +646,7 @@ signs(S::AbstractSubsystemCode) = S.signs Return the signs of the `X` stabilizers of the CSS code. """ -X_signs(S::T) where {T <: AbstractSubsystemCode} = X_signs(CSSTrait(T), S) +X_signs(S::T) where {T<:AbstractSubsystemCode} = X_signs(CSSTrait(T), S) X_signs(::IsCSS, S::AbstractSubsystemCode) = S.X_signs X_signs(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes.") @@ -403,7 +655,7 @@ X_signs(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes. Return the signs of the `Z` stabilizers of the CSS code. """ -Z_signs(S::T) where {T <: AbstractSubsystemCode} = Z_signs(CSSTrait(T), S) +Z_signs(S::T) where {T<:AbstractSubsystemCode} = Z_signs(CSSTrait(T), S) Z_signs(::IsCSS, S::AbstractSubsystemCode) = S.Z_signs Z_signs(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes.") @@ -416,8 +668,8 @@ Return the stabilizer matrix of the code. - If the optional parameter `standform` is set to `true`, the standard form of the stabilizer matrix is returned instead. """ -stabilizers(S::AbstractSubsystemCode; standform::Bool = false) = standform ? - (return S.stabs_stand) : (return S.stabs) +stabilizers(S::AbstractSubsystemCode; standform::Bool = false) = + standform ? (return S.stabs_stand) : (return S.stabs) """ standard_form_permutation(S::AbstractSubsystemCode) @@ -432,68 +684,70 @@ standard_form_permutation(S::AbstractSubsystemCode) = S.P_stand Return the named matrix `A` from the standard form of the stabilizer matrix. """ -standard_form_A(S::AbstractSubsystemCode) = S.stabs_stand[1:S.stand_r, S.stand_r + 1:S.n] +standard_form_A(S::AbstractSubsystemCode) = S.stabs_stand[1:S.stand_r, (S.stand_r+1):S.n] """ standard_form_A1(S::AbstractSubsystemCode) Return the named matrix `A1` from the standard form of the stabilizer matrix. """ -standard_form_A1(S::AbstractSubsystemCode) = S.stabs_stand[1:S.stand_r, S.stand_r + 1:S.n - - S.stand_k] +standard_form_A1(S::AbstractSubsystemCode) = + S.stabs_stand[1:S.stand_r, (S.stand_r+1):(S.n-S.stand_k)] """ standard_form_A2(S::AbstractSubsystemCode) Return the named matrix `A2` from the standard form of the stabilizer matrix. """ -standard_form_A2(S::AbstractSubsystemCode) = S.stabs_stand[1:S.stand_r, S.n - S.stand_k + 1:S.n] +standard_form_A2(S::AbstractSubsystemCode) = + S.stabs_stand[1:S.stand_r, (S.n-S.stand_k+1):S.n] """ standard_form_B(S::AbstractSubsystemCode) Return the named matrix `B` from the standard form of the stabilizer matrix. """ -standard_form_B(S::AbstractSubsystemCode) = S.stabs_stand[1:S.stand_r, S.n + 1:S.n + S.stand_r] +standard_form_B(S::AbstractSubsystemCode) = + S.stabs_stand[1:S.stand_r, (S.n+1):(S.n+S.stand_r)] """ standard_form_C1(S::AbstractSubsystemCode) Return the named matrix `C1` from the standard form of the stabilizer matrix. """ -standard_form_C1(S::AbstractSubsystemCode) = S.stabs_stand[1:S.stand_r, S.n + S.stand_r + 1:2 * - S.n - S.stand_k] +standard_form_C1(S::AbstractSubsystemCode) = + S.stabs_stand[1:S.stand_r, (S.n+S.stand_r+1):(2*S.n-S.stand_k)] """ standard_form_C2(S::AbstractSubsystemCode) Return the named matrix `C2` from the standard form of the stabilizer matrix. """ -standard_form_C2(S::AbstractSubsystemCode) = S.stabs_stand[1:S.stand_r, 2 * S.n - S.stand_k + 1:2 * - S.n] +standard_form_C2(S::AbstractSubsystemCode) = + S.stabs_stand[1:S.stand_r, (2*S.n-S.stand_k+1):(2*S.n)] """ standard_form_D(S::AbstractSubsystemCode) Return the named matrix `D` from the standard form of the stabilizer matrix. """ -standard_form_D(S::AbstractSubsystemCode) = S.stabs_stand[S.stand_r + 1:S.n - S.stand_k, S.n + - 1:S.n + S.stand_r] +standard_form_D(S::AbstractSubsystemCode) = + S.stabs_stand[(S.stand_r+1):(S.n-S.stand_k), (S.n+1):(S.n+S.stand_r)] """ standard_form_E(S::AbstractSubsystemCode) Return the named matrix `E` from the standard form of the stabilizer matrix. """ -standard_form_E(S::AbstractSubsystemCode) = S.stabs_stand[S.stand_r + 1:S.n - S.stand_k, 2 * S.n - - S.stand_k + 1:2 * S.n] +standard_form_E(S::AbstractSubsystemCode) = + S.stabs_stand[(S.stand_r+1):(S.n-S.stand_k), (2*S.n-S.stand_k+1):(2*S.n)] """ X_stabilizers(S::AbstractSubsystemCode) Return the `X`-stabilizer matrix of the CSS code. """ -X_stabilizers(S::T) where {T <: AbstractSubsystemCode} = X_stabilizers(CSSTrait(T), S) +X_stabilizers(S::T) where {T<:AbstractSubsystemCode} = X_stabilizers(CSSTrait(T), S) X_stabilizers(::IsCSS, S::AbstractSubsystemCode) = S.X_stabs X_stabilizers(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes.") @@ -502,7 +756,7 @@ X_stabilizers(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS Return the `Z`-stabilizer matrix of the CSS code. """ -Z_stabilizers(S::T) where {T <: AbstractSubsystemCode} = Z_stabilizers(CSSTrait(T), S) +Z_stabilizers(S::T) where {T<:AbstractSubsystemCode} = Z_stabilizers(CSSTrait(T), S) Z_stabilizers(::IsCSS, S::AbstractSubsystemCode) = S.Z_stabs Z_stabilizers(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes.") @@ -511,7 +765,7 @@ Z_stabilizers(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS Return the metacheck matrix of the code, if it has been set; otherwise returns missing. """ -metacheck(S::T) where {T <: AbstractSubsystemCode} = metacheck(CSSTrait(T), S) +metacheck(S::T) where {T<:AbstractSubsystemCode} = metacheck(CSSTrait(T), S) metacheck(::IsCSS, S::AbstractSubsystemCode) = error("Use `X_metacheck` or `Z_metacheck` for CSS codes.") metacheck(::IsNotCSS, S::AbstractSubsystemCode) = S.metacheck @@ -521,7 +775,7 @@ metacheck(::IsNotCSS, S::AbstractSubsystemCode) = S.metacheck Return the `X`-metacheck matrix of the CSS code, if it has been set; otherwise returns missing. """ -X_metacheck(S::T) where {T <: AbstractSubsystemCode} = X_metacheck(CSSTrait(T), S) +X_metacheck(S::T) where {T<:AbstractSubsystemCode} = X_metacheck(CSSTrait(T), S) X_metacheck(::IsCSS, S::AbstractSubsystemCode) = S.X_metacheck X_metacheck(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes.") @@ -530,7 +784,7 @@ X_metacheck(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS co Return the `Z`-metacheck matrix of the CSS code, if it has been set; otherwise returns missing. """ -Z_metacheck(S::T) where {T <: AbstractSubsystemCode} = Z_metacheck(CSSTrait(T), S) +Z_metacheck(S::T) where {T<:AbstractSubsystemCode} = Z_metacheck(CSSTrait(T), S) Z_metacheck(::IsCSS, S::AbstractSubsystemCode) = S.Z_metacheck Z_metacheck(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes.") @@ -539,7 +793,7 @@ Z_metacheck(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS co Return the number of `X` stabilizers of the CSS code. """ -num_X_stabs(S::T) where {T <: AbstractSubsystemCode} = num_X_stabs(CSSTrait(T), S) +num_X_stabs(S::T) where {T<:AbstractSubsystemCode} = num_X_stabs(CSSTrait(T), S) num_X_stabs(::IsCSS, S::AbstractSubsystemCode) = nrows(S.X_stabs) num_X_stabs(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes.") @@ -548,7 +802,7 @@ num_X_stabs(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS co Return the number of `Z` stabilizers of the CSS code. """ -num_Z_stabs(S::T) where {T <: AbstractSubsystemCode} = num_Z_stabs(CSSTrait(T), S) +num_Z_stabs(S::T) where {T<:AbstractSubsystemCode} = num_Z_stabs(CSSTrait(T), S) num_Z_stabs(::IsCSS, S::AbstractSubsystemCode) = nrows(S.Z_stabs) num_Z_stabs(::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes.") @@ -572,7 +826,7 @@ is_overcomplete(S::AbstractSubsystemCode) = S.overcomplete Return `true` if `S` is CSS. """ -is_CSS(S::T) where {T <: AbstractSubsystemCode} = is_CSS(CSSTrait(T), S) +is_CSS(S::T) where {T<:AbstractSubsystemCode} = is_CSS(CSSTrait(T), S) is_CSS(::IsCSS, S::AbstractSubsystemCode) = true is_CSS(::IsNotCSS, S::AbstractSubsystemCode) = false @@ -598,9 +852,10 @@ end Return a vector of logical operator generator pairs for `S`. """ -logicals(S::T) where {T <: AbstractSubsystemCode} = logicals(LogicalTrait(T), S) +logicals(S::T) where {T<:AbstractSubsystemCode} = logicals(LogicalTrait(T), S) logicals(::HasLogicals, S::AbstractSubsystemCode) = S.logicals -logicals(::HasNoLogicals, S::AbstractSubsystemCode) = error("Type $(typeof(S)) has no logicals.") +logicals(::HasNoLogicals, S::AbstractSubsystemCode) = + error("Type $(typeof(S)) has no logicals.") logical_operators(S::AbstractSubsystemCode) = logicals(S) bare_logicals(S::AbstractSubsystemCode) = logicals(S) bare(S::AbstractSubsystemCode) = logicals(S) @@ -610,18 +865,22 @@ bare(S::AbstractSubsystemCode) = logicals(S) Returns the result of `logicals(S)` as a vertically concatenated matrix. """ -logicals_matrix(S::T) where {T <: AbstractSubsystemCode} = logicals_matrix(LogicalTrait(T), S) +logicals_matrix(S::T) where {T<:AbstractSubsystemCode} = logicals_matrix(LogicalTrait(T), S) logicals_matrix(::HasLogicals, S::AbstractSubsystemCode) = S.logs_mat -logicals_matrix(::HasNoLogicals, S::AbstractSubsystemCode) = error("Type $(typeof(S)) has no logicals.") +logicals_matrix(::HasNoLogicals, S::AbstractSubsystemCode) = + error("Type $(typeof(S)) has no logicals.") """ logicals_standard_form(S::AbstractSubsystemCode) Return the a matrix of logical operators as determined by the stabilizers in standard form. """ -logicals_standard_form(S::T) where {T <: AbstractSubsystemCode} = logicals_standard_form(LogicalsTrait(T), S) -logicals_standard_form(::HasLogicals, S::AbstractSubsystemCode) = _logicals_standard_form(S.stabs_stand, S.n, S.stand_k,S.stand_r, S.P_stand) -logicals_standard_form(::HasNoLogicals, S::AbstractSubsystemCode) = error("Type $(typeof(S)) has no logicals.") +logicals_standard_form(S::T) where {T<:AbstractSubsystemCode} = + logicals_standard_form(LogicalsTrait(T), S) +logicals_standard_form(::HasLogicals, S::AbstractSubsystemCode) = + _logicals_standard_form(S.stabs_stand, S.n, S.stand_k, S.stand_r, S.P_stand) +logicals_standard_form(::HasNoLogicals, S::AbstractSubsystemCode) = + error("Type $(typeof(S)) has no logicals.") """ gauges(S::AbstractSubsystemCode) @@ -632,7 +891,7 @@ Return a vector of gauge operator generator pairs for `S`. # Notes - Here, gauge operators refers to the gauge group minus the stabilizers. """ -gauges(S::T) where {T <: AbstractSubsystemCode} = gauges(GaugeTrait(T), S) +gauges(S::T) where {T<:AbstractSubsystemCode} = gauges(GaugeTrait(T), S) gauges(::HasGauges, S::AbstractSubsystemCode) = S.gauge_ops gauges(::HasNoGauges, S::AbstractSubsystemCode) = error("Type $(typeof(S)) has no gauges.") gauge_operators(S::AbstractSubsystemCode) = gauges(S) @@ -643,9 +902,10 @@ gauge_operators(S::AbstractSubsystemCode) = gauges(S) Return the result of `gauges(S)` as a vertically concatenated matrix. """ -gauges_matrix(S::T) where {T <: AbstractSubsystemCode} = gauges_matrix(GaugeTrait(T), S) +gauges_matrix(S::T) where {T<:AbstractSubsystemCode} = gauges_matrix(GaugeTrait(T), S) gauges_matrix(::HasGauges, S::AbstractSubsystemCode) = S.g_ops_mat -gauges_matrix(::HasNoGauges, S::AbstractSubsystemCode) = error("Type $(typeof(S)) has no gauges.") +gauges_matrix(::HasNoGauges, S::AbstractSubsystemCode) = + error("Type $(typeof(S)) has no gauges.") gauge_operators_matrix(S::AbstractSubsystemCode) = gauges_matrix(S) """ @@ -658,7 +918,7 @@ Return a vector of pairs generators for the dressed operators of `S`. # Notes - Here, the dressed operators are the logicals and the gauge operators. """ -function dressed(S::T) where {T <: AbstractSubsystemCode} +function dressed(S::T) where {T<:AbstractSubsystemCode} if LogicalTrait(T) == HasNoLogicals error("Type $T has no logicals.") elseif GaugeTrait(S) == HasNoGauges @@ -680,9 +940,10 @@ Return a matrix giving a (maybe overcomplete) basis for the gauge group. # Notes * Here, this is the stabilizers and the gauge operators. """ -gauge_group(S::T) where {T <: AbstractSubsystemCode} = gauge_group(GaugeTrait(T), S) +gauge_group(S::T) where {T<:AbstractSubsystemCode} = gauge_group(GaugeTrait(T), S) gauge_group(::HasGauges, S::AbstractSubsystemCode) = vcat(S.stabs, S.g_ops_mat) -gauge_group(::HasNoGauges, S::AbstractSubsystemCode) = error("Type $(typeof(S)) has no gauges.") +gauge_group(::HasNoGauges, S::AbstractSubsystemCode) = + error("Type $(typeof(S)) has no gauges.") gauge_group_matrix(S::AbstractSubsystemCode) = gauge_group(S) gauge_generators_matrix(S::AbstractSubsystemCode) = gauge_group(S) gauge_group_generators_matrix(S::AbstractSubsystemCode) = gauge_group(S) @@ -691,47 +952,54 @@ gauge_group_generators_matrix(S::AbstractSubsystemCode) = gauge_group(S) bare_minimum_distance_lower_bound(S::AbstractSubsystemCode) Return the currently stored lower bound on the bare minimum distance. """ -bare_minimum_distance_lower_bound(S::T) where T <: AbstractSubsystemCode = +bare_minimum_distance_lower_bound(S::T) where {T<:AbstractSubsystemCode} = bare_minimum_distance_lower_bound(GaugeTrait(T), S) bare_minimum_distance_lower_bound(::HasGauges, S::AbstractSubsystemCode) = S.l_bound_bare -bare_minimum_distance_lower_bound(::HasNoGauges, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `minimum_distance_lower_bound` for stabilizer codes.") +bare_minimum_distance_lower_bound(::HasNoGauges, S::AbstractSubsystemCode) = error( + "Only valid for subsystem codes; use `minimum_distance_lower_bound` for stabilizer codes.", +) """ bare_minimum_distance_upper_bound(S::AbstractSubsystemCode) Return the currently stored upper bound on the bare minimum distance. """ -bare_minimum_distance_upper_bound(S::T) where T <: AbstractSubsystemCode = +bare_minimum_distance_upper_bound(S::T) where {T<:AbstractSubsystemCode} = bare_minimum_distance_upper_bound(GaugeTrait(T), S) bare_minimum_distance_upper_bound(::HasGauges, S::AbstractSubsystemCode) = S.u_bound_bare -bare_minimum_distance_upper_bound(::HasNoGauges, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `minimum_distance_lower_bound` for stabilizer codes.") +bare_minimum_distance_upper_bound(::HasNoGauges, S::AbstractSubsystemCode) = error( + "Only valid for subsystem codes; use `minimum_distance_lower_bound` for stabilizer codes.", +) """ dressed_minimum_distance_lower_bound(S::AbstractSubsystemCode) Return the currently stored lower bound on the dressed minimum distance. """ -dressed_minimum_distance_lower_bound(S::T) where T <: AbstractSubsystemCode = +dressed_minimum_distance_lower_bound(S::T) where {T<:AbstractSubsystemCode} = dressed_minimum_distance_lower_bound(GaugeTrait(T), S) -dressed_minimum_distance_lower_bound(::HasGauges, S::AbstractSubsystemCode) = S.l_bound_dressed -dressed_minimum_distance_lower_bound(::HasNoGauges, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `minimum_distance_lower_bound` for stabilizer codes.") +dressed_minimum_distance_lower_bound(::HasGauges, S::AbstractSubsystemCode) = + S.l_bound_dressed +dressed_minimum_distance_lower_bound(::HasNoGauges, S::AbstractSubsystemCode) = error( + "Only valid for subsystem codes; use `minimum_distance_lower_bound` for stabilizer codes.", +) """ dressed_minimum_distance_upper_bound(S::AbstractSubsystemCode) Return the currently stored upper bound on the dressed minimum distance. """ -dressed_minimum_distance_upper_bound(S::T) where T <: AbstractSubsystemCode = +dressed_minimum_distance_upper_bound(S::T) where {T<:AbstractSubsystemCode} = dressed_minimum_distance_upper_bound(GaugeTrait(T), S) -dressed_minimum_distance_upper_bound(::HasGauges, S::AbstractSubsystemCode) = S.u_bound_dressed -dressed_minimum_distance_upper_bound(::HasNoGauges, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `minimum_distance_lower_bound` for stabilizer codes.") +dressed_minimum_distance_upper_bound(::HasGauges, S::AbstractSubsystemCode) = + S.u_bound_dressed +dressed_minimum_distance_upper_bound(::HasNoGauges, S::AbstractSubsystemCode) = error( + "Only valid for subsystem codes; use `minimum_distance_lower_bound` for stabilizer codes.", +) """ bare_X_minimum_distance_lower_bound(S::AbstractSubsystemCode) Return the currently stored lower bound on the bare `X`-minimum distance. """ -bare_X_minimum_distance_lower_bound(S::T) where T <: AbstractSubsystemCode = bare_X_minimum_distance_lower_bound(GaugeTrait(T), CSSTrait(T), S) +bare_X_minimum_distance_lower_bound(S::T) where {T<:AbstractSubsystemCode} = + bare_X_minimum_distance_lower_bound(GaugeTrait(T), CSSTrait(T), S) bare_X_minimum_distance_lower_bound(::HasGauges, ::IsCSS, S::AbstractSubsystemCode) = S.l_bound_dx_bare bare_X_minimum_distance_lower_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode) = @@ -739,13 +1007,16 @@ bare_X_minimum_distance_lower_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsyste bare_X_minimum_distance_lower_bound(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for subsystem codes") bare_X_minimum_distance_lower_bound(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `X_minimum_distance_lower_bound` for stabilizer codes.") + error( + "Only valid for subsystem codes; use `X_minimum_distance_lower_bound` for stabilizer codes.", + ) """ bare_X_minimum_distance_upper_bound(S::AbstractSubsystemCode) Return the currently stored upper bound on the bare `X`-minimum distance. """ -bare_X_minimum_distance_upper_bound(S::T) where T <: AbstractSubsystemCode = bare_X_minimum_distance_upper_bound(GaugeTrait(T), CSSTrait(T), S) +bare_X_minimum_distance_upper_bound(S::T) where {T<:AbstractSubsystemCode} = + bare_X_minimum_distance_upper_bound(GaugeTrait(T), CSSTrait(T), S) bare_X_minimum_distance_upper_bound(::HasGauges, ::IsCSS, S::AbstractSubsystemCode) = S.u_bound_dx_bare bare_X_minimum_distance_upper_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode) = @@ -753,41 +1024,56 @@ bare_X_minimum_distance_upper_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsyste bare_X_minimum_distance_upper_bound(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for subsystem codes") bare_X_minimum_distance_upper_bound(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `X_minimum_distance_upper_bound` for stabilizer codes.") + error( + "Only valid for subsystem codes; use `X_minimum_distance_upper_bound` for stabilizer codes.", + ) """ dressed_X_minimum_distance_lower_bound(S::AbstractSubsystemCode) Return the currently stored lower bound on the dressed `X`-minimum distance. """ -dressed_X_minimum_distance_lower_bound(S::T) where T <: AbstractSubsystemCode = dressed_X_minimum_distance_lower_bound(GaugeTrait(T), CSSTrait(T), S) +dressed_X_minimum_distance_lower_bound(S::T) where {T<:AbstractSubsystemCode} = + dressed_X_minimum_distance_lower_bound(GaugeTrait(T), CSSTrait(T), S) dressed_X_minimum_distance_lower_bound(::HasGauges, ::IsCSS, S::AbstractSubsystemCode) = S.l_bound_dx_dressed dressed_X_minimum_distance_lower_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes") -dressed_X_minimum_distance_lower_bound(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes") +dressed_X_minimum_distance_lower_bound( + ::HasNoGauges, + ::IsNotCSS, + S::AbstractSubsystemCode, +) = error("Only valid for subsystem codes") dressed_X_minimum_distance_lower_bound(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `X_minimum_distance_lower_bound` for stabilizer codes.") + error( + "Only valid for subsystem codes; use `X_minimum_distance_lower_bound` for stabilizer codes.", + ) """ dressed_X_minimum_distance_upper_bound(S::AbstractSubsystemCode) Return the currently stored upper bound on the dressed `X`-minimum distance. """ -dressed_X_minimum_distance_upper_bound(S::T) where T <: AbstractSubsystemCode = dressed_X_minimum_distance_upper_bound(GaugeTrait(T), CSSTrait(T), S) +dressed_X_minimum_distance_upper_bound(S::T) where {T<:AbstractSubsystemCode} = + dressed_X_minimum_distance_upper_bound(GaugeTrait(T), CSSTrait(T), S) dressed_X_minimum_distance_upper_bound(::HasGauges, ::IsCSS, S::AbstractSubsystemCode) = S.u_bound_dx_dressed dressed_X_minimum_distance_upper_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes") -dressed_X_minimum_distance_upper_bound(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes") +dressed_X_minimum_distance_upper_bound( + ::HasNoGauges, + ::IsNotCSS, + S::AbstractSubsystemCode, +) = error("Only valid for subsystem codes") dressed_X_minimum_distance_upper_bound(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `X_minimum_distance_upper_bound` for stabilizer codes.") + error( + "Only valid for subsystem codes; use `X_minimum_distance_upper_bound` for stabilizer codes.", + ) """ bare_Z_minimum_distance_lower_bound(S::AbstractSubsystemCode) Return the currently stored lower bound on the bare `Z`-minimum distance. """ -bare_Z_minimum_distance_lower_bound(S::T) where T <: AbstractSubsystemCode = bare_Z_minimum_distance_lower_bound(GaugeTrait(T), CSSTrait(T), S) +bare_Z_minimum_distance_lower_bound(S::T) where {T<:AbstractSubsystemCode} = + bare_Z_minimum_distance_lower_bound(GaugeTrait(T), CSSTrait(T), S) bare_Z_minimum_distance_lower_bound(::HasGauges, ::IsCSS, S::AbstractSubsystemCode) = S.l_bound_dZ_bare bare_Z_minimum_distance_lower_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode) = @@ -795,13 +1081,16 @@ bare_Z_minimum_distance_lower_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsyste bare_Z_minimum_distance_lower_bound(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for subsystem codes") bare_Z_minimum_distance_lower_bound(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `Z_minimum_distance_lower_bound` for stabilizer codes.") + error( + "Only valid for subsystem codes; use `Z_minimum_distance_lower_bound` for stabilizer codes.", + ) """ bare_Z_minimum_distance_upper_bound(S::AbstractSubsystemCode) Return the currently stored upper bound on the bare `Z`-minimum distance. """ -bare_Z_minimum_distance_upper_bound(S::T) where T <: AbstractSubsystemCode = bare_Z_minimum_distance_upper_bound(GaugeTrait(T), CSSTrait(T), S) +bare_Z_minimum_distance_upper_bound(S::T) where {T<:AbstractSubsystemCode} = + bare_Z_minimum_distance_upper_bound(GaugeTrait(T), CSSTrait(T), S) bare_Z_minimum_distance_upper_bound(::HasGauges, ::IsCSS, S::AbstractSubsystemCode) = S.u_bound_dz_bare bare_Z_minimum_distance_upper_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode) = @@ -809,38 +1098,52 @@ bare_Z_minimum_distance_upper_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsyste bare_Z_minimum_distance_upper_bound(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for subsystem codes") bare_Z_minimum_distance_upper_bound(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `Z_minimum_distance_upper_bound` for stabilizer codes.") + error( + "Only valid for subsystem codes; use `Z_minimum_distance_upper_bound` for stabilizer codes.", + ) """ dressed_Z_minimum_distance_lower_bound(S::AbstractSubsystemCode) Return the currently stored lower bound on the dressed `Z`-minimum distance. """ -dressed_Z_minimum_distance_lower_bound(S::T) where T <: AbstractSubsystemCode = dressed_Z_minimum_distance_lower_bound(GaugeTrait(T), CSSTrait(T), S) +dressed_Z_minimum_distance_lower_bound(S::T) where {T<:AbstractSubsystemCode} = + dressed_Z_minimum_distance_lower_bound(GaugeTrait(T), CSSTrait(T), S) dressed_Z_minimum_distance_lower_bound(::HasGauges, ::IsCSS, S::AbstractSubsystemCode) = S.l_bound_dz_dressed dressed_Z_minimum_distance_lower_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes") -dressed_Z_minimum_distance_lower_bound(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes") +dressed_Z_minimum_distance_lower_bound( + ::HasNoGauges, + ::IsNotCSS, + S::AbstractSubsystemCode, +) = error("Only valid for subsystem codes") dressed_Z_minimum_distance_lower_bound(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `Z_minimum_distance_lower_bound` for stabilizer codes.") + error( + "Only valid for subsystem codes; use `Z_minimum_distance_lower_bound` for stabilizer codes.", + ) """ dressed_Z_minimum_distance_upper_bound(S::AbstractSubsystemCode) Return the currently stored upper bound on the dressed `Z`-minimum distance. """ -dressed_Z_minimum_distance_upper_bound(S::T) where T <: AbstractSubsystemCode = dressed_Z_minimum_distance_upper_bound(GaugeTrait(T), CSSTrait(T), S) +dressed_Z_minimum_distance_upper_bound(S::T) where {T<:AbstractSubsystemCode} = + dressed_Z_minimum_distance_upper_bound(GaugeTrait(T), CSSTrait(T), S) dressed_Z_minimum_distance_upper_bound(::HasGauges, ::IsCSS, S::AbstractSubsystemCode) = S.u_bound_dz_dressed dressed_Z_minimum_distance_upper_bound(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode) = error("Only valid for CSS codes") -dressed_Z_minimum_distance_upper_bound(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes") +dressed_Z_minimum_distance_upper_bound( + ::HasNoGauges, + ::IsNotCSS, + S::AbstractSubsystemCode, +) = error("Only valid for subsystem codes") dressed_Z_minimum_distance_upper_bound(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode) = - error("Only valid for subsystem codes; use `Z_minimum_distance_upper_bound` for stabilizer codes.") + error( + "Only valid for subsystem codes; use `Z_minimum_distance_upper_bound` for stabilizer codes.", + ) ############################# - # setter functions +# setter functions ############################# """ @@ -851,16 +1154,18 @@ Set the character vector of `S` to `char_vec` and update the signs. """ function set_signs!(S::AbstractSubsystemCode, char_vec::Vector{zzModRingElem}) R = base_ring(character_vector(S)) - length(char_vec) == 2 * S.n || throw(ArgumentError("Characteristic vector is of improper length for the code.")) + length(char_vec) == 2 * S.n || + throw(ArgumentError("Characteristic vector is of improper length for the code.")) for s in char_vec - modulus(s) == modulus(R) || throw(ArgumentError("Phases are not in the correct ring.")) + modulus(s) == modulus(R) || + throw(ArgumentError("Phases are not in the correct ring.")) end S.signs = _get_signs(S.stabilizers, char_vec) S.char_vec = char_vec end -set_signs(S::AbstractSubsystemCode, char_vec::Vector{zzModRingElem}) = (S_new = deepcopy(S); - return setsign!s(S_new, char_vec)) +set_signs(S::AbstractSubsystemCode, char_vec::Vector{zzModRingElem}) = + (S_new = deepcopy(S); return setsign!s(S_new, char_vec)) """ set_stabilizers(S::AbstractSubsystemCode, stabs::CTMatrixTypes) @@ -873,7 +1178,8 @@ Set the stabilizers of `S` to `stabs`. """ function set_stabilizers!(S::AbstractSubsystemCode, stabs::CTMatrixTypes) iszero(stabs) && throw(ArgumentError("The stabilizers cannot be zero.")) - order(S.F) == order(base_ring(stabs)) || throw(ArgumentError("The stabilizers must be over the same field as the code.")) + order(S.F) == order(base_ring(stabs)) || + throw(ArgumentError("The stabilizers must be over the same field as the code.")) stabs = _remove_empty(stabs, :rows) stabs = change_base_ring(S.F, stabs) @@ -899,8 +1205,8 @@ function set_stabilizers!(S::AbstractSubsystemCode, stabs::CTMatrixTypes) end return nothing end -set_stabilizers(S::AbstractSubsystemCode, stabs::CTMatrixTypes) = (S_new = deepcopy(S); - set_stabilizers!(S_new, stabs); return S_new) +set_stabilizers(S::AbstractSubsystemCode, stabs::CTMatrixTypes) = + (S_new = deepcopy(S); set_stabilizers!(S_new, stabs); return S_new) """ set_X_stabilizers(S::AbstractSubsystemCode, X_stabs::CTMatrixTypes; trimmed::Bool = true) @@ -913,19 +1219,28 @@ to have `length(S)` columns; otherwise, they are assumed to be in symplectic for # Notes * A check is done to make sure `stabs` are equivalent to the current set of stabilizers. """ -set_X_stabilizers!(S::T, X_stabs::CTMatrixTypes; trimmed::Bool = true) where {T <: - AbstractSubsystemCode} = set_X_stabilizers!(CSSTrait(T), S, X_stabs, trimmed) -function set_X_stabilizers!(::IsCSS, S::AbstractSubsystemCode, X_stabs::CTMatrixTypes, - trimmed::Bool) +set_X_stabilizers!( + S::T, + X_stabs::CTMatrixTypes; + trimmed::Bool = true, +) where {T<:AbstractSubsystemCode} = set_X_stabilizers!(CSSTrait(T), S, X_stabs, trimmed) +function set_X_stabilizers!( + ::IsCSS, + S::AbstractSubsystemCode, + X_stabs::CTMatrixTypes, + trimmed::Bool, +) iszero(X_stabs) && throw(ArgumentError("The stabilizers cannot be zero.")) - order(S.F) == order(base_ring(X_stabs)) || throw(ArgumentError("The stabilizers must be over the same field as the code.")) + order(S.F) == order(base_ring(X_stabs)) || + throw(ArgumentError("The stabilizers must be over the same field as the code.")) if trimmed ncols(X_stabs) == S.n || throw(ArgumentError("Trimmed set and input of wrong size")) X_trimmed = X_stabs else - ncols(X_stabs) == 2 * S.n || throw(ArgumentError("Trimmed not set and input of wrong size")) - iszero(X_stabs[:, S.n + 1:end]) || throw(ArgumentError("Input is not in CSS form")) + ncols(X_stabs) == 2 * S.n || + throw(ArgumentError("Trimmed not set and input of wrong size")) + iszero(X_stabs[:, (S.n+1):end]) || throw(ArgumentError("Input is not in CSS form")) X_trimmed = X_stabs[:, 1:S.n] end @@ -940,8 +1255,10 @@ function set_X_stabilizers!(::IsCSS, S::AbstractSubsystemCode, X_stabs::CTMatrix end S.X_signs = _determine_signs(X_trimmed, S.char_vec) - S.stabs = vcat(hcat(X_trimmed, zero_matrix(S.F, nrows(X_trimmed), S.n)), - hcat(zero_matrix(S.F, nrows(S.Z_stabs), S.n), S.Z_stabs)) + S.stabs = vcat( + hcat(X_trimmed, zero_matrix(S.F, nrows(X_trimmed), S.n)), + hcat(zero_matrix(S.F, nrows(S.Z_stabs), S.n), S.Z_stabs), + ) # stabs_stand, P_stand, stand_r, stand_k, _ = _standard_form_stabilizer(S.stabs) # S.stabs_stand = stabs_stand # S.stand_r = stand_r @@ -950,14 +1267,33 @@ function set_X_stabilizers!(::IsCSS, S::AbstractSubsystemCode, X_stabs::CTMatrix S.signs = S.X_signs ∪ S.Z_signs return nothing end -set_X_stabilizers!(::IsNotCSS, S::AbstractSubsystemCode, X_stabs::CTMatrixTypes, trimmed::Bool) = - error("X stabilizers are only defined for CSS codes") -set_X_stabilizers(S::T, X_stabs::CTMatrixTypes; trimmed::Bool = true) where {T <: - AbstractSubsystemCode} = set_X_stabilizers(CSSTrait(T), S, X_stabs, trimmed) -set_X_stabilizers(::IsCSS, S::AbstractSubsystemCode, X_stabs::CTMatrixTypes, trimmed::Bool) = - (S_new = deepcopy(S); set_X_stabilizers!(IsCSS(), S_new, X_stabs, trimmed); return S_new) -set_X_stabilizers(::IsNotCSS, S::AbstractSubsystemCode, X_stabs::CTMatrixTypes, trimmed::Bool) = - error("X stabilizers are only defined for CSS codes") +set_X_stabilizers!( + ::IsNotCSS, + S::AbstractSubsystemCode, + X_stabs::CTMatrixTypes, + trimmed::Bool, +) = error("X stabilizers are only defined for CSS codes") +set_X_stabilizers( + S::T, + X_stabs::CTMatrixTypes; + trimmed::Bool = true, +) where {T<:AbstractSubsystemCode} = set_X_stabilizers(CSSTrait(T), S, X_stabs, trimmed) +set_X_stabilizers( + ::IsCSS, + S::AbstractSubsystemCode, + X_stabs::CTMatrixTypes, + trimmed::Bool, +) = ( + S_new = deepcopy(S); + set_X_stabilizers!(IsCSS(), S_new, X_stabs, trimmed); + return S_new +) +set_X_stabilizers( + ::IsNotCSS, + S::AbstractSubsystemCode, + X_stabs::CTMatrixTypes, + trimmed::Bool, +) = error("X stabilizers are only defined for CSS codes") """ set_Z_stabilizers(S::AbstractSubsystemCode, Z_stabs::CTMatrixTypes; trimmed::Bool = true) @@ -970,20 +1306,29 @@ to have `length(S)` columns; otherwise, they are assumed to be in symplectic for # Notes * A check is done to make sure `stabs` are equivalent to the current set of stabilizers. """ -set_Z_stabilizers!(S::T, Z_stabs::CTMatrixTypes; trimmed::Bool = true) where {T <: - AbstractSubsystemCode} = set_Z_stabilizers!(CSSTrait(T), S, Z_stabs, trimmed) -function set_Z_stabilizers!(::IsCSS, S::AbstractSubsystemCode, Z_stabs::CTMatrixTypes, - trimmed::Bool) +set_Z_stabilizers!( + S::T, + Z_stabs::CTMatrixTypes; + trimmed::Bool = true, +) where {T<:AbstractSubsystemCode} = set_Z_stabilizers!(CSSTrait(T), S, Z_stabs, trimmed) +function set_Z_stabilizers!( + ::IsCSS, + S::AbstractSubsystemCode, + Z_stabs::CTMatrixTypes, + trimmed::Bool, +) iszero(Z_stabs) && throw(ArgumentError("The stabilizers cannot be zero.")) - order(S.F) == order(base_ring(Z_stabs)) || throw(ArgumentError("The stabilizers must be over the same field as the code.")) + order(S.F) == order(base_ring(Z_stabs)) || + throw(ArgumentError("The stabilizers must be over the same field as the code.")) if trimmed ncols(Z_stabs) == S.n || throw(ArgumentError("Trimmed set and input of wrong size")) Z_trimmed = Z_stabs else - ncols(Z_stabs) == 2 * S.n || throw(ArgumentError("Trimmed not set and input of wrong size")) + ncols(Z_stabs) == 2 * S.n || + throw(ArgumentError("Trimmed not set and input of wrong size")) iszero(Z_stabs[:, 1:S.n]) || throw(ArgumentError("Input is not in CSS form")) - Z_trimmed = Z_stabs[:, S.n + 1:end] + Z_trimmed = Z_stabs[:, (S.n+1):end] end Z_trimmed = _remove_empty(Z_trimmed, :rows) @@ -996,18 +1341,40 @@ function set_Z_stabilizers!(::IsCSS, S::AbstractSubsystemCode, Z_stabs::CTMatrix end S.Z_signs = _determine_signs(Z_trimmed, S.char_vec) - S.stabs = vcat(hcat(S.X_stabs, zero_matrix(S.F, nrows(S.X_stabs), S.n)), - hcat(zero_matrix(S.F, nrows(Z_trimmed), S.n), Z_trimmed)) + S.stabs = vcat( + hcat(S.X_stabs, zero_matrix(S.F, nrows(S.X_stabs), S.n)), + hcat(zero_matrix(S.F, nrows(Z_trimmed), S.n), Z_trimmed), + ) S.signs = S.X_signs ∪ S.Z_signs return nothing end -set_Z_stabilizers!(::IsNotCSS, S::AbstractSubsystemCode, Z_stabs::CTMatrixTypes, trimmed::Bool) = - error("Z stabilizers are only defined for CSS codes") -set_Z_stabilizers(S::T, Z_stabs::CTMatrixTypes; trimmed::Bool = true) where {T <: - AbstractSubsystemCode} = set_Z_stabilizers(CSSTrait(T), S, Z_stabs, trimmed) -set_Z_stabilizers(::IsCSS, S::AbstractSubsystemCode, Z_stabs::CTMatrixTypes, trimmed::Bool) = (S_new = deepcopy(S); set_Z_stabilizers!(IsCSS(), S_new, Z_stabs, trimmed); return S_new) -set_Z_stabilizers(::IsNotCSS, S::AbstractSubsystemCode, Z_stabs::CTMatrixTypes, trimmed::Bool) = - error("Z stabilizers are only defined for CSS codes") +set_Z_stabilizers!( + ::IsNotCSS, + S::AbstractSubsystemCode, + Z_stabs::CTMatrixTypes, + trimmed::Bool, +) = error("Z stabilizers are only defined for CSS codes") +set_Z_stabilizers( + S::T, + Z_stabs::CTMatrixTypes; + trimmed::Bool = true, +) where {T<:AbstractSubsystemCode} = set_Z_stabilizers(CSSTrait(T), S, Z_stabs, trimmed) +set_Z_stabilizers( + ::IsCSS, + S::AbstractSubsystemCode, + Z_stabs::CTMatrixTypes, + trimmed::Bool, +) = ( + S_new = deepcopy(S); + set_Z_stabilizers!(IsCSS(), S_new, Z_stabs, trimmed); + return S_new +) +set_Z_stabilizers( + ::IsNotCSS, + S::AbstractSubsystemCode, + Z_stabs::CTMatrixTypes, + trimmed::Bool, +) = error("Z stabilizers are only defined for CSS codes") """ set_logicals(S::AbstractSubsystemCode, L::CTMatrixTypes) @@ -1018,32 +1385,46 @@ Set the logical operators of `S` to `L`. # Notes * A check is done to make sure `L` are eqivalent to the current set of logicals (up to stabilizers). """ -set_logicals!(S::T, L::W) where {T <: AbstractSubsystemCode, W <: CTMatrixTypes} = +set_logicals!(S::T, L::W) where {T<:AbstractSubsystemCode,W<:CTMatrixTypes} = set_logicals!(LogicalTrait(T), S, L) -function set_logicals!(::HasLogicals, S::AbstractSubsystemCode, L::W) where {W <: CTMatrixTypes} - size(L) == (2 * S.k, 2 * S.n) || throw(ArgumentError("Provided matrix is of incorrect size for the logical space.")) - iseven(ncols(L)) || throw(ArgumentError("Expected a symplectic input but the input matrix has an odd number of columns.")) - S.F == base_ring(L) || throw(ArgumentError("The logicals must be over the same field as the code.")) - - _has_equivalent_row_spaces(vcat(S.logs_mat, S.stabs), vcat(L, S.stabs)) || error("The current logicals are not equivalent to the input.") +function set_logicals!( + ::HasLogicals, + S::AbstractSubsystemCode, + L::W, +) where {W<:CTMatrixTypes} + size(L) == (2 * S.k, 2 * S.n) || + throw(ArgumentError("Provided matrix is of incorrect size for the logical space.")) + iseven(ncols(L)) || throw( + ArgumentError( + "Expected a symplectic input but the input matrix has an odd number of columns.", + ), + ) + S.F == base_ring(L) || + throw(ArgumentError("The logicals must be over the same field as the code.")) + + _has_equivalent_row_spaces(vcat(S.logs_mat, S.stabs), vcat(L, S.stabs)) || + error("The current logicals are not equivalent to the input.") # are_symplectic_orthogonal(symplecticstabilizers(S), Lsym, true) || # error("Provided logicals do not commute with the code.") # the columns in prod give the commutation relationships between the provided # logical operators; they ideally should only consist of {X_1, Z_i} pairs # so there should only be one nonzero element in each column - prod = hcat(L[:, S.n + 1:end], -L[:, 1:S.n]) * transpose(L) - iszero(prod) && throw(ArgumentError("Provided logicals should not be symplectic self-orthogonal.")) + prod = hcat(L[:, (S.n+1):end], -L[:, 1:S.n]) * transpose(L) + iszero(prod) && + throw(ArgumentError("Provided logicals should not be symplectic self-orthogonal.")) nc_pr = ncols(prod) # need an integer sum and this is cheaper than Nemo.ZZ prod_Jul = _Flint_matrix_to_Julia_int_matrix(prod) - cols = [sum(prod_Jul[:, i]) for i in 1:nc_pr] - sum(cols) == nc_pr || throw(ArgumentError("Incorrect commutation relationships between provided logicals.")) + cols = [sum(prod_Jul[:, i]) for i = 1:nc_pr] + sum(cols) == nc_pr || throw( + ArgumentError("Incorrect commutation relationships between provided logicals."), + ) # pairs are row i, and then whatever column is nonzero, and then shift such that it is one F = base_ring(L) F_one = F(1) - logs = Vector{Tuple{W, W}}() + logs = Vector{Tuple{W,W}}() if Int(order(F)) != 2 # this does indeed grow smaller each iteration while nrows(L) >= 2 @@ -1066,11 +1447,11 @@ function set_logicals!(::HasLogicals, S::AbstractSubsystemCode, L::W) where {W < end end S.logicals = logs - S.logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i in 1:length(logs)]) + S.logs_mat = reduce(vcat, [reduce(vcat, logs[i]) for i = 1:length(logs)]) end set_logicals!(::HasNoLogicals, S::AbstractSubsystemCode, L::CTMatrixTypes) = error("Type $(typeof(S)) has no logicals.") -set_logicals(S::T, L::CTMatrixTypes) where {T <: AbstractSubsystemCode} = +set_logicals(S::T, L::CTMatrixTypes) where {T<:AbstractSubsystemCode} = set_logicals(LogicalTrait(T), S, L) set_logicals(::HasLogicals, S::AbstractSubsystemCode, L::CTMatrixTypes) = (S_new = deepcopy(S); set_logicals!(S_new, L); return S_new) @@ -1083,7 +1464,7 @@ set_logicals(::HasNoLogicals, S::AbstractSubsystemCode, L::CTMatrixTypes) = Set the metacheck matrix of `S` to `M`. """ -set_metacheck!(S::T, M::U) where {T <: AbstractSubsystemCode, U <: CTMatrixTypes} = +set_metacheck!(S::T, M::U) where {T<:AbstractSubsystemCode,U<:CTMatrixTypes} = set_metacheck!(CSSTrait(T), S, M) set_metacheck!(::IsCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = error("Use `set_X_metacheck` and `set_Z_metacheck` for CSS codes.") @@ -1091,7 +1472,7 @@ function set_metacheck!(::IsNotCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) iszero(M * S.stabs) ? (S.metacheck = M;) : error("Invalid metacheck for code") return nothing end -set_metacheck(S::T, M::U) where {T <: AbstractSubsystemCode, U <: CTMatrixTypes} = +set_metacheck(S::T, M::U) where {T<:AbstractSubsystemCode,U<:CTMatrixTypes} = set_metacheck(CSSTrait(T), S, M) set_metacheck(::IsCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = error("Use `set_X_metacheck` and `set_Z_metacheck` for CSS codes.") @@ -1104,15 +1485,15 @@ set_metacheck(::IsNotCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = Set the `X`-metacheck matrix of `S` to `M`. """ -set_X_metacheck!(S::T, M::U) where {T <: AbstractSubsystemCode, U <: CTMatrixTypes} = +set_X_metacheck!(S::T, M::U) where {T<:AbstractSubsystemCode,U<:CTMatrixTypes} = set_X_metacheck!(CSSTrait(T), S, M) function set_X_metacheck!(::IsCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) iszero(M * S.X_stabs) ? (S.X_metacheck = M;) : error("Invalid metacheck for code") return nothing end -set_X_metacheck!(::IsNotCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = +set_X_metacheck!(::IsNotCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = error("Only valid for CSS codes.") -set_X_metacheck(S::T, M::U) where {T <: AbstractSubsystemCode, U <: CTMatrixTypes} = +set_X_metacheck(S::T, M::U) where {T<:AbstractSubsystemCode,U<:CTMatrixTypes} = set_X_metacheck(CSSTrait(T), S, M) set_X_metacheck(::IsCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = (S_new = deepcopy(S); set_X_metacheck!(IsNotCSS(), S_new, M); return S_new) @@ -1125,15 +1506,15 @@ set_X_metacheck(::IsNotCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = Set the `Z`-metacheck matrix of `S` to `M`. """ -set_Z_metacheck!(S::T, M::U) where {T <: AbstractSubsystemCode, U <: CTMatrixTypes} = +set_Z_metacheck!(S::T, M::U) where {T<:AbstractSubsystemCode,U<:CTMatrixTypes} = set_Z_metacheck!(CSSTrait(T), S, M) function set_Z_metacheck!(::IsCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) iszero(M * S.Z_stabs) ? (S.Z_metacheck = M;) : error("Invalid metacheck for code") return nothing end -set_Z_metacheck!(::IsNotCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = +set_Z_metacheck!(::IsNotCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = error("Only valid for CSS codes.") -set_Z_metacheck(S::T, M::U) where {T <: AbstractSubsystemCode, U <: CTMatrixTypes} = +set_Z_metacheck(S::T, M::U) where {T<:AbstractSubsystemCode,U<:CTMatrixTypes} = set_Z_metacheck(CSSTrait(T), S, M) set_Z_metacheck(::IsCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = (S_new = deepcopy(S); set_Z_metacheck!(IsNotCSS(), S_new, M); return S_new) @@ -1145,12 +1526,15 @@ set_Z_metacheck(::IsNotCSS, S::AbstractSubsystemCode, M::CTMatrixTypes) = Set the bare minimum distance of the code to `d`. """ -set_bare_minimum_distance!(S::T, d::Int) where T <: AbstractSubsystemCode = +set_bare_minimum_distance!(S::T, d::Int) where {T<:AbstractSubsystemCode} = set_bare_minimum_distance!(GaugeTrait(T), S, d) function set_bare_minimum_distance!(::HasGauges, S::AbstractSubsystemCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound_bare < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound_bare)") - d < S.l_bound_bare && (@warn "The distance set is less than the current lower bound of $(S.l_bound_bare)") + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound_bare < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound_bare)") + d < S.l_bound_bare && + (@warn "The distance set is less than the current lower bound of $(S.l_bound_bare)") S.d_bare = d S.l_bound_bare = d S.u_bound_bare = d @@ -1159,27 +1543,39 @@ function set_bare_minimum_distance!(::HasGauges, S::AbstractSubsystemCode, d::In # bare is an upper bound on dressed S.d_bare < S.u_bound_dressed && (S.u_bound_dressed = S.d_bare;) else - S.d_dressed ≤ S.d_bare || (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") + S.d_dressed ≤ S.d_bare || + (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") end if CSSTrait(typeof(S)) == IsCSS() ismissing(S.dx_bare) && (S.l_bound_dx_bare = d;) - ismissing(S.dz_bare) && (S.l_bound_dz_bare = d;) + ismissing(S.dz_bare) && (S.l_bound_dz_bare = d;) end return nothing end -set_bare_minimum_distance!(::HasNoGauges, S::AbstractSubsystemCode, d::Int) = error("Only valid for subsytem codes; use `set_minimum_distance!` for stabilizer codes.") +set_bare_minimum_distance!(::HasNoGauges, S::AbstractSubsystemCode, d::Int) = error( + "Only valid for subsytem codes; use `set_minimum_distance!` for stabilizer codes.", +) """ set_bare_X_minimum_distance!(S::AbstractStabilizerCode, d::Int) Set the bare minimum `X`-distance of the code to `d`. """ -set_bare_X_minimum_distance!(S::T, d::Int) where T <: AbstractSubsystemCode = set_bare_X_minimum_distance!(GaugeTrait(T), CSSTrait(T), S, d) -function set_bare_X_minimum_distance!(::HasGauges, ::IsCSS, S::AbstractSubsystemCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound_dx_bare < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dx_bare)") - d < S.l_bound_dx_bare && (@warn "The distance set is less than the current lower bound of $(S.l_bound_dx_bare)") +set_bare_X_minimum_distance!(S::T, d::Int) where {T<:AbstractSubsystemCode} = + set_bare_X_minimum_distance!(GaugeTrait(T), CSSTrait(T), S, d) +function set_bare_X_minimum_distance!( + ::HasGauges, + ::IsCSS, + S::AbstractSubsystemCode, + d::Int, +) + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound_dx_bare < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dx_bare)") + d < S.l_bound_dx_bare && + (@warn "The distance set is less than the current lower bound of $(S.l_bound_dx_bare)") S.dx_bare = d S.l_bound_dx_bare = d S.u_bound_dx_bare = d @@ -1188,7 +1584,8 @@ function set_bare_X_minimum_distance!(::HasGauges, ::IsCSS, S::AbstractSubsystem # bare is an upper bound on dressed S.dx_bare < S.u_bound_dx_dressed && (S.u_bound_dx_dressed = S.dx_bare;) else - S.dx_dressed ≤ S.dx_bare || (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") + S.dx_dressed ≤ S.dx_bare || + (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") end # TODO think about whether I need to bound dressed here @@ -1206,18 +1603,29 @@ set_bare_X_minimum_distance!(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode, set_bare_X_minimum_distance!(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode, d::Int) = error("Not valid for this code") set_bare_X_minimum_distance!(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode, d::Int) = - error("Only valid for subsytem codes; use `set_X_minimum_distance!` for stabilizer codes.") + error( + "Only valid for subsytem codes; use `set_X_minimum_distance!` for stabilizer codes.", + ) """ set_bare_Z_minimum_distance!(S::AbstractStabilizerCode, d::Int) Set the bare minimum `Z`-distance of the code to `d`. """ -set_bare_Z_minimum_distance!(S::T, d::Int) where T <: AbstractSubsystemCode = set_bare_Z_minimum_distance!(GaugeTrait(T), CSSTrait(T), S, d) -function set_bare_Z_minimum_distance!(::HasGauges, ::IsCSS, S::AbstractSubsystemCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound_dz_bare < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dz_bare)") - d < S.l_bound_dz_bare && (@warn "The distance set is less than the current lower bound of $(S.l_bound_dz_bare)") +set_bare_Z_minimum_distance!(S::T, d::Int) where {T<:AbstractSubsystemCode} = + set_bare_Z_minimum_distance!(GaugeTrait(T), CSSTrait(T), S, d) +function set_bare_Z_minimum_distance!( + ::HasGauges, + ::IsCSS, + S::AbstractSubsystemCode, + d::Int, +) + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound_dz_bare < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dz_bare)") + d < S.l_bound_dz_bare && + (@warn "The distance set is less than the current lower bound of $(S.l_bound_dz_bare)") S.dz_bare = d S.l_bound_dz_bare = d S.u_bound_dz_bare = d @@ -1226,7 +1634,8 @@ function set_bare_Z_minimum_distance!(::HasGauges, ::IsCSS, S::AbstractSubsystem # bare is an upper bound on dressed S.dz_bare < S.u_bound_dz_dressed && (S.u_bound_dz_dressed = S.dz_bare;) else - S.dz_dressed ≤ S.dz_bare || (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") + S.dz_dressed ≤ S.dz_bare || + (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") end # TODO think about whether I need to bound dressed here @@ -1244,35 +1653,43 @@ set_bare_Z_minimum_distance!(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode, set_bare_Z_minimum_distance!(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode, d::Int) = error("Not valid for this code") set_bare_Z_minimum_distance!(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode, d::Int) = - error("Only valid for subsytem codes; use `set_Z_minimum_distance!` for stabilizer codes.") + error( + "Only valid for subsytem codes; use `set_Z_minimum_distance!` for stabilizer codes.", + ) """ set_dressed_minimum_distance!(S::AbstractSubsystemCode, d::Int) Set the dressed minimum distance of the code to `d`. """ -set_dressed_minimum_distance!(S::T, d::Int) where T <: AbstractSubsystemCode = +set_dressed_minimum_distance!(S::T, d::Int) where {T<:AbstractSubsystemCode} = set_dressed_minimum_distance!(GaugeTrait(T), S, d) function set_dressed_minimum_distance!(::HasGauges, S::AbstractSubsystemCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound_dressed < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dressed)") - d < S.l_bound_dressed && (@warn "The distance set is less than the current lower bound of $(S.l_bound_dressed)") + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound_dressed < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dressed)") + d < S.l_bound_dressed && + (@warn "The distance set is less than the current lower bound of $(S.l_bound_dressed)") S.d_dressed = d S.l_bound_dressed = d S.u_bound_dressed = d if !ismissing(S.d_dressed) && !ismissing(S.d_bare) # bare is an upper bound on dressed - S.d_dressed ≤ S.d_bare || (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") + S.d_dressed ≤ S.d_bare || + (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") end if CSSTrait(typeof(S)) == IsCSS() ismissing(S.dx_dressed) && (S.l_bound_dx_dressed = d;) - ismissing(S.dz_dressed) && (S.l_bound_dz_dressed = d;) + ismissing(S.dz_dressed) && (S.l_bound_dz_dressed = d;) end return nothing end -set_dressed_minimum_distance!(::HasNoGauges, S::AbstractSubsystemCode, d::Int) = error("Only valid for subsytem codes; use `set_minimum_distance!` for stabilizer codes.") +set_dressed_minimum_distance!(::HasNoGauges, S::AbstractSubsystemCode, d::Int) = error( + "Only valid for subsytem codes; use `set_minimum_distance!` for stabilizer codes.", +) """ @@ -1280,18 +1697,28 @@ set_dressed_minimum_distance!(::HasNoGauges, S::AbstractSubsystemCode, d::Int) = Set the dressed minimum `X`-distance of the code to `d`. """ -set_dressed_X_minimum_distance!(S::T, d::Int) where T <: AbstractSubsystemCode = set_dressed_X_minimum_distance!(GaugeTrait(T), CSSTrait(T), S, d) -function set_dressed_X_minimum_distance!(::HasGauges, ::IsCSS, S::AbstractSubsystemCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound_dx_dressed < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dx_dressed)") - d < S.l_bound_dx_dressed && (@warn "The distance set is less than the current lower bound of $(S.l_bound_dx_dressed)") +set_dressed_X_minimum_distance!(S::T, d::Int) where {T<:AbstractSubsystemCode} = + set_dressed_X_minimum_distance!(GaugeTrait(T), CSSTrait(T), S, d) +function set_dressed_X_minimum_distance!( + ::HasGauges, + ::IsCSS, + S::AbstractSubsystemCode, + d::Int, +) + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound_dx_dressed < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dx_dressed)") + d < S.l_bound_dx_dressed && + (@warn "The distance set is less than the current lower bound of $(S.l_bound_dx_dressed)") S.dx_dressed = d S.l_bound_dx_dressed = d S.u_bound_dx_dressed = d if !ismissing(S.dx_bare) # bare is an upper bound on dressed - S.dx_dressed ≤ S.dx_bare || (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") + S.dx_dressed ≤ S.dx_bare || + (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") end if !ismissing(S.dz_dressed) @@ -1305,28 +1732,44 @@ function set_dressed_X_minimum_distance!(::HasGauges, ::IsCSS, S::AbstractSubsys end set_dressed_X_minimum_distance!(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode, d::Int) = error("Only valid for CSS codes") -set_dressed_X_minimum_distance!(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode, d::Int) = - error("Not valid for this code") +set_dressed_X_minimum_distance!( + ::HasNoGauges, + ::IsNotCSS, + S::AbstractSubsystemCode, + d::Int, +) = error("Not valid for this code") set_dressed_X_minimum_distance!(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode, d::Int) = - error("Only valid for subsytem codes; use `set_X_minimum_distance!` for stabilizer codes.") + error( + "Only valid for subsytem codes; use `set_X_minimum_distance!` for stabilizer codes.", + ) """ set_dressed_Z_minimum_distance!(S::AbstractStabilizerCode, d::Int) Set the dressed minimum `Z`-distance of the code to `d`. """ -set_dressed_Z_minimum_distance!(S::T, d::Int) where T <: AbstractSubsystemCode = set_dressed_Z_minimum_distance!(GaugeTrait(T), CSSTrait(T), S, d) -function set_dressed_Z_minimum_distance!(::HasGauges, ::IsCSS, S::AbstractSubsystemCode, d::Int) - 0 < d <= S.n || throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) - S.u_bound_dz_dressed < d && (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dz_dressed)") - d < S.l_bound_dz_dressed && (@warn "The distance set is less than the current lower bound of $(S.l_bound_dz_dressed)") +set_dressed_Z_minimum_distance!(S::T, d::Int) where {T<:AbstractSubsystemCode} = + set_dressed_Z_minimum_distance!(GaugeTrait(T), CSSTrait(T), S, d) +function set_dressed_Z_minimum_distance!( + ::HasGauges, + ::IsCSS, + S::AbstractSubsystemCode, + d::Int, +) + 0 < d <= S.n || + throw(DomainError("The minimum distance of a code must be ≥ 1; received: d = $d.")) + S.u_bound_dz_dressed < d && + (@warn "The distance set is greater than the current upper bound of $(S.u_bound_dz_dressed)") + d < S.l_bound_dz_dressed && + (@warn "The distance set is less than the current lower bound of $(S.l_bound_dz_dressed)") S.dz_dressed = d S.l_bound_dz_dressed = d S.u_bound_dz_dressed = d if ismissing(S.dz_dressed) # bare is an upper bound on dressed - S.dz_dressed ≤ S.dz_bare || (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") + S.dz_dressed ≤ S.dz_bare || + (@warn "The bare distance is a bound on the dressed distance, but this is false for the new set parameters.") end if !ismissing(S.dx_dressed) @@ -1340,25 +1783,33 @@ function set_dressed_Z_minimum_distance!(::HasGauges, ::IsCSS, S::AbstractSubsys end set_dressed_Z_minimum_distance!(::HasGauges, ::IsNotCSS, S::AbstractSubsystemCode, d::Int) = error("Only valid for CSS codes") -set_dressed_Z_minimum_distance!(::HasNoGauges, ::IsNotCSS, S::AbstractSubsystemCode, d::Int) = - error("Not valid for this code") +set_dressed_Z_minimum_distance!( + ::HasNoGauges, + ::IsNotCSS, + S::AbstractSubsystemCode, + d::Int, +) = error("Not valid for this code") set_dressed_Z_minimum_distance!(::HasNoGauges, ::IsCSS, S::AbstractSubsystemCode, d::Int) = - error("Only valid for subsytem codes; use `set_Z_minimum_distance!` for stabilizer codes.") + error( + "Only valid for subsytem codes; use `set_Z_minimum_distance!` for stabilizer codes.", + ) ############################# - # general functions +# general functions ############################# -function _process_char_vec(char_vec::Union{Vector{zzModRingElem}, Missing}, p::Int, n::Int) +function _process_char_vec(char_vec::Union{Vector{zzModRingElem},Missing}, p::Int, n::Int) if !ismissing(char_vec) - n == length(char_vec) || throw(ArgumentError("The characteristic value is of incorrect length.")) + n == length(char_vec) || + throw(ArgumentError("The characteristic value is of incorrect length.")) if p == 2 R, _ = residue_ring(Nemo.ZZ, 4) else R, _ = residue_ring(Nemo.ZZ, p) end for s in char_vec - modulus(s) == modulus(R) || throw(ArgumentError("Phases are not in the correct ring.")) + modulus(s) == modulus(R) || + throw(ArgumentError("Phases are not in the correct ring.")) end else if p == 2 @@ -1366,7 +1817,7 @@ function _process_char_vec(char_vec::Union{Vector{zzModRingElem}, Missing}, p::I else R, _ = residue_ring(Nemo.ZZ, p) end - char_vec = [R(0) for _ in 1:n] + char_vec = [R(0) for _ = 1:n] end return char_vec end @@ -1374,23 +1825,28 @@ end function _determine_signs(S::CTMatrixTypes, char_vec::Vector{zzModRingElem}) if iszero(char_vec) R = parent(char_vec[1]) - signs = [R(0) for _ in 1:nrows(S)] + signs = [R(0) for _ = 1:nrows(S)] else signs = _get_signs(S, char_vec) end return signs end -function _determine_signs_CSS(S::CTMatrixTypes, char_vec::Vector{zzModRingElem}, X_size::Int, Z_size::Int) +function _determine_signs_CSS( + S::CTMatrixTypes, + char_vec::Vector{zzModRingElem}, + X_size::Int, + Z_size::Int, +) if iszero(char_vec) R = parent(char_vec[1]) - signs = [R(0) for _ in 1:nrows(S)] - X_signs = [R(0) for _ in 1:X_size] - Z_signs = [R(0) for _ in 1:Z_size] + signs = [R(0) for _ = 1:nrows(S)] + X_signs = [R(0) for _ = 1:X_size] + Z_signs = [R(0) for _ = 1:Z_size] else signs = _get_signs(S, char_vec) X_signs = signs[1:X_size, :] - Z_signs = signs[X_size + 1:end, :] + Z_signs = signs[(X_size+1):end, :] end return signs, X_signs, Z_signs end @@ -1398,11 +1854,15 @@ end function _get_signs(A::CTMatrixTypes, char_vec::Vector{zzModRingElem}) R = base_ring(char_vec[1]) nc = ncols(A) - length(char_vec) == nc || throw(ArgumentError("Input to _get_signs is expected to be in symplectic form and of the same length as the characteristic vector.")) - - iszero(char_vec) && return [R(0) for _ in 1:div(nc, 2)] + length(char_vec) == nc || throw( + ArgumentError( + "Input to _get_signs is expected to be in symplectic form and of the same length as the characteristic vector.", + ), + ) + + iszero(char_vec) && return [R(0) for _ = 1:div(nc, 2)] signs = Vector{Int64}() - for r in 1:nrows(A) + for r = 1:nrows(A) parity = R(0) for c = 1:nc !iszero(A[r, c]) && (parity += char_vec[c];) @@ -1412,7 +1872,7 @@ function _get_signs(A::CTMatrixTypes, char_vec::Vector{zzModRingElem}) return signs end -function _split_vectors_CSS(S::T, signs::Vector{zzModRingElem}) where {T <: CTMatrixTypes} +function _split_vectors_CSS(S::T, signs::Vector{zzModRingElem}) where {T<:CTMatrixTypes} X_stabs = Vector{T}() X_signs = Vector{zzModRingElem}() Z_stabs = Vector{T}() @@ -1421,14 +1881,14 @@ function _split_vectors_CSS(S::T, signs::Vector{zzModRingElem}) where {T <: CTMa mixed_signs = Vector{zzModRingElem}() half = div(ncols(S), 2) - for r in 1:nrows(S) + for r = 1:nrows(S) # use views? s = S[r:r, :] if iszero(s) continue else s_x = iszero(s[1, 1:half]) - s_z = iszero(s[1, half + 1:end]) + s_z = iszero(s[1, (half+1):end]) if (s_x && !s_z) push!(Z_stabs, s) push!(Z_signs, signs[r]) @@ -1472,12 +1932,17 @@ end # and then either set first or add to it (return matrix[2:end, L]) # TODO: need more robust CSS detection, what if I add and X and Z stabilizer and use it implace of the Z # TODO: what's going on here -function _is_CSS_symplectic(stabs::T, signs::Vector{zzModRingElem}, trim::Bool=true) where T <: CTMatrixTypes - X_stabs, X_signs, Z_stabs, Z_signs, mixed_stabs, mixed_signs = _split_vectors_CSS(stabs, signs) +function _is_CSS_symplectic( + stabs::T, + signs::Vector{zzModRingElem}, + trim::Bool = true, +) where {T<:CTMatrixTypes} + X_stabs, X_signs, Z_stabs, Z_signs, mixed_stabs, mixed_signs = + _split_vectors_CSS(stabs, signs) if typeof(mixed_stabs) <: Vector{T} if trim half = div(ncols(stabs), 2) - return true, X_stabs[:, 1:half], X_signs, Z_stabs[:, half + 1:end], Z_signs + return true, X_stabs[:, 1:half], X_signs, Z_stabs[:, (half+1):end], Z_signs else return true, X_stabs, X_signs, Z_stabs, Z_signs end @@ -1485,7 +1950,7 @@ function _is_CSS_symplectic(stabs::T, signs::Vector{zzModRingElem}, trim::Bool=t if trim half = div(ncols(stabs), 2) !(typeof(X_stabs) <: Vector{T}) && (X_stabs = X_stabs[:, 1:half];) - !(typeof(Z_stabs) <: Vector{T}) && (Z_stabs = Z_stabs[:, half + 1:end];) + !(typeof(Z_stabs) <: Vector{T}) && (Z_stabs = Z_stabs[:, (half+1):end];) return false, X_stabs, X_signs, Z_stabs, Z_signs, mixed_stabs, mixed_signs else return false, X_stabs, X_signs, Z_stabs, Z_signs, mixed_stabs, mixed_signs @@ -1494,22 +1959,22 @@ function _is_CSS_symplectic(stabs::T, signs::Vector{zzModRingElem}, trim::Bool=t end # using this function for logical and gauge operators -function _make_pairs(L::T) where T <: CTMatrixTypes +function _make_pairs(L::T) where {T<:CTMatrixTypes} F = base_ring(L) n = div(ncols(L), 2) - logs = Vector{Tuple{T, T}}() + logs = Vector{Tuple{T,T}}() if Int(order(F)) != 2 # this does indeed grow smaller each iteration while nrows(L) >= 2 # the columns in prod give the commutation relationships between the provided # logical operators; they ideally should only consist of {X_1, Z_i} pairs # so there should only be one nonzero element in each column - prod = hcat(L[:, n + 1:end], -L[:, 1:n]) * transpose(L) + prod = hcat(L[:, (n+1):end], -L[:, 1:n]) * transpose(L) # println("before") # display(prod) num_prod = ncols(prod) first = 0 - for c in 1:num_prod + for c = 1:num_prod if !iszero(prod[1, c]) if iszero(first) first = c @@ -1521,13 +1986,15 @@ function _make_pairs(L::T) where T <: CTMatrixTypes end end end - iszero(first) && error("Cannot make symplectic basis. Often this is due to the fact that the stabilizers are not maximal and therefore the centralizer still containing part of the isotropic subspace.") - for c in 2:num_prod + iszero(first) && error( + "Cannot make symplectic basis. Often this is due to the fact that the stabilizers are not maximal and therefore the centralizer still containing part of the isotropic subspace.", + ) + for c = 2:num_prod if !iszero(prod[first, c]) L[c:c, :] += F(prod[first, c]^-1) * L[1:1, :] end end - prod = hcat(L[:, n + 1:end], -L[:, 1:n]) * transpose(L) + prod = hcat(L[:, (n+1):end], -L[:, 1:n]) * transpose(L) # println("after") # display(prod) push!(logs, (L[1:1, :], L[first:first, :])) @@ -1540,12 +2007,12 @@ function _make_pairs(L::T) where T <: CTMatrixTypes # the columns in prod give the commutation relationships between the provided # logical operators; they ideally should only consist of {X_1, Z_i} pairs # so there should only be one nonzero element in each column - prod = hcat(L[:, n + 1:end], -L[:, 1:n]) * transpose(L) + prod = hcat(L[:, (n+1):end], -L[:, 1:n]) * transpose(L) # println("before") # display(prod) num_prod = ncols(prod) first = 0 - for c in 1:num_prod + for c = 1:num_prod if !iszero(prod[1, c]) if iszero(first) first = c @@ -1554,13 +2021,15 @@ function _make_pairs(L::T) where T <: CTMatrixTypes end end end - iszero(first) && error("Cannot make symplectic basis. Often this is due to the fact that the stabilizers are not maximal and therefore the centralizer still containing part of the isotropic subspace.") - for c in 2:num_prod + iszero(first) && error( + "Cannot make symplectic basis. Often this is due to the fact that the stabilizers are not maximal and therefore the centralizer still containing part of the isotropic subspace.", + ) + for c = 2:num_prod if !iszero(prod[first, c]) L[c:c, :] += L[1:1, :] end end - prod = hcat(L[:, n + 1:end], -L[:, 1:n]) * transpose(L) + prod = hcat(L[:, (n+1):end], -L[:, 1:n]) * transpose(L) # println("after") # display(prod) push!(logs, (L[1:1, :], L[first:first, :])) @@ -1571,22 +2040,23 @@ function _make_pairs(L::T) where T <: CTMatrixTypes return logs end -_test_logicals_relationships(S::T) where {T <: AbstractSubsystemCode} = +_test_logicals_relationships(S::T) where {T<:AbstractSubsystemCode} = _test_logicals_relationships(LogicalTrait(T), S) function _test_logicals_relationships(::HasLogicals, S::AbstractSubsystemCode) - prod = hcat(S.logs_mat[:, S.n + 1:end], -S.logs_mat[:, 1:S.n]) * transpose(S.logs_mat) + prod = hcat(S.logs_mat[:, (S.n+1):end], -S.logs_mat[:, 1:S.n]) * transpose(S.logs_mat) display(prod) return nothing end -_test_logicals_relationships(::HasNoLogicals, S) = error("Type $(typeof(S)) has no logicals.") +_test_logicals_relationships(::HasNoLogicals, S) = + error("Type $(typeof(S)) has no logicals.") """ is_logical(S::AbstractSubsystemCode, v::CTMatrixTypes) Return `true` if the vector `v` is a logical operator for `S`. """ -is_logical(S::T, v::CTMatrixTypes) where {T <: AbstractSubsystemCode} = is_logical(LogicalTrait(T), - S, v) +is_logical(S::T, v::CTMatrixTypes) where {T<:AbstractSubsystemCode} = + is_logical(LogicalTrait(T), S, v) function is_logical(::HasLogicals, S::AbstractSubsystemCode, v::CTMatrixTypes) nc = ncols(S.logs_mat) are_symplectic_orthogonal(S.stabs, v) || return false @@ -1602,7 +2072,8 @@ is_logical(::HasNoLogicals, S::AbstractSubsystemCode, v::CTMatrixTypes) = Return `true` if the vector `v` is a gauge operator for `S`. """ -is_gauge(S::T, v::CTMatrixTypes) where {T <: AbstractSubsystemCode} = is_gauge(GaugeTrait(T), S, v) +is_gauge(S::T, v::CTMatrixTypes) where {T<:AbstractSubsystemCode} = + is_gauge(GaugeTrait(T), S, v) function is_gauge(::HasGauges, S::AbstractSubsystemCode, v::CTMatrixTypes) nc = ncols(S.g_ops_mat) are_symplectic_orthogonal(S.stabs, v) || return false @@ -1610,7 +2081,8 @@ function is_gauge(::HasGauges, S::AbstractSubsystemCode, v::CTMatrixTypes) size(v) == (nc, 1) && (return !iszero(S.g_ops_mat * v);) throw(ArgumentError("Vector to be tested is of incorrect dimension.")) end -is_gauge(::HasNoGauges, S::AbstractSubsystemCode, v::CTMatrixTypes) = error("Type $(typeof(S)) has no gauges.") +is_gauge(::HasNoGauges, S::AbstractSubsystemCode, v::CTMatrixTypes) = + error("Type $(typeof(S)) has no gauges.") # TODO: make uniform with approach in function above and linear code """ @@ -1619,8 +2091,11 @@ is_gauge(::HasNoGauges, S::AbstractSubsystemCode, v::CTMatrixTypes) = error("Typ Return the syndrome of the vector `v` with respect to the stabilizers of `S`. """ function syndrome(S::AbstractSubsystemCode, v::CTMatrixTypes) - (size(v) != (2 * S.n, 1) && size(v) != (1, 2 * S.n)) && - throw(ArgumentError("Vector to be tested is of incorrect dimension; expected length $(2 * n), received: $(size(v)).")) + (size(v) != (2 * S.n, 1) && size(v) != (1, 2 * S.n)) && throw( + ArgumentError( + "Vector to be tested is of incorrect dimension; expected length $(2 * n), received: $(size(v)).", + ), + ) # base_ring(v) == field(S) || error("Vector must have the same base ring as the stabilizers.") nrows(v) != 1 || return S.stabs * transpose(v) @@ -1633,12 +2108,13 @@ end Return the syndrome of the vector `v` with respect to the `X` stabilizers of the CSS code. """ -X_syndrome(S::T, v::CTMatrixTypes) where {T <: AbstractSubsystemCode} = X_syndrome(CSSTrait(T), - S, v) +X_syndrome(S::T, v::CTMatrixTypes) where {T<:AbstractSubsystemCode} = + X_syndrome(CSSTrait(T), S, v) function X_syndrome(::IsCSS, S::AbstractSubsystemCode, v::CTMatrixTypes) - length(v) == 2 * S.n && (v = v[S.n + 1:end];) - (size(v) != (S.n, 1) && size(v) != (1, S.n)) && - error("Vector to be tested is of incorrect dimension; expected length $n, received: $(size(v)).") + length(v) == 2 * S.n && (v = v[(S.n+1):end];) + (size(v) != (S.n, 1) && size(v) != (1, S.n)) && error( + "Vector to be tested is of incorrect dimension; expected length $n, received: $(size(v)).", + ) base_ring(v) == S.F || error("Vector must have the same base ring as the stabilizers.") nrows(v) != 1 || return S.X_stabs * transpose(v) @@ -1653,12 +2129,13 @@ X_syndrome(::IsNotCSS, S::AbstractSubsystemCode, v::CTMatrixTypes) = Return the syndrome of the vector `v` with respect to the `Z` stabilizers of the CSS code. """ -Z_syndrome(S::T, v::CTMatrixTypes) where {T <: AbstractSubsystemCode} = Z_syndrome(CSSTrait(T), - S, v) +Z_syndrome(S::T, v::CTMatrixTypes) where {T<:AbstractSubsystemCode} = + Z_syndrome(CSSTrait(T), S, v) function Z_syndrome(::IsCSS, S::AbstractSubsystemCode, v::CTMatrixTypes) length(v) == 2 * S.n && (v = v[1:S.n];) - (size(v) != (n, 1) && size(v) != (1, n)) && - error("Vector to be tested is of incorrect dimension; expected length $n, received: $(size(v)).") + (size(v) != (n, 1) && size(v) != (1, n)) && error( + "Vector to be tested is of incorrect dimension; expected length $n, received: $(size(v)).", + ) base_ring(v) == S.F || error("Vector must have the same base ring as the stabilizers.") nrows(v) != 1 || return S.Z_stabs * transpose(v) @@ -1673,15 +2150,19 @@ Z_syndrome(::IsNotCSS, S::AbstractSubsystemCode, v::CTMatrixTypes) = Add the logical pairs in `pairs` to the gauge operators. """ -promote_logicals_to_gauge!(S::T, pairs::Vector{Int}) where {T <: AbstractSubsystemCode} = +promote_logicals_to_gauge!(S::T, pairs::Vector{Int}) where {T<:AbstractSubsystemCode} = promote_logicals_to_gauge!(LogicalTrait(T), S, pairs) -function promote_logicals_to_gauge!(::HasLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) +function promote_logicals_to_gauge!( + ::HasLogicals, + S::AbstractSubsystemCode, + pairs::Vector{Int}, +) pairs = sort!(unique!(pairs)) # will let this error naturally if pairs contains invalid elements S.gauge_ops = S.gauge_ops ∪ S.logicals[pairs] - S.g_ops_mat = reduce(vcat, [reduce(vcat, S.gauge_ops[i]) for i in 1:length(S.gauge_ops)]) + S.g_ops_mat = reduce(vcat, [reduce(vcat, S.gauge_ops[i]) for i = 1:length(S.gauge_ops)]) S.logicals = S.logicals[setdiff!(append!(collect(1:length(S.logicals)), pairs))] - S.logs_mat = reduce(vcat, [reduce(vcat, S.logicals[i]) for i in 1:length(S.logicals)]) + S.logs_mat = reduce(vcat, [reduce(vcat, S.logicals[i]) for i = 1:length(S.logicals)]) S.r = S.r + length(pairs) if isinteger(S.k) @@ -1696,10 +2177,13 @@ promote_logicals_to_gauge!(::HasNoLogicals, S::AbstractSubsystemCode, pairs::Vec error("Type $(typeof(S)) has no logicals.") # TODO: this can drop to a graph state, which is why I did what I did before -promote_logicals_to_gauge(S::T, pairs::Vector{Int}) where {T <: AbstractSubsystemCode} = +promote_logicals_to_gauge(S::T, pairs::Vector{Int}) where {T<:AbstractSubsystemCode} = promote_logicals_to_gauge(LogicalTrait(T), S, pairs) -promote_logicals_to_gauge(::HasLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) = - (S_new = deepcopy(S); promote_logicals_to_gauge!(HasLogicals(), S_new, pairs); return S_new) +promote_logicals_to_gauge(::HasLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) = ( + S_new = deepcopy(S); + promote_logicals_to_gauge!(HasLogicals(), S_new, pairs); + return S_new +) promote_logicals_to_gauge(::HasNoLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) = error("Type $(typeof(S)) has no logicals.") @@ -1709,21 +2193,25 @@ promote_logicals_to_gauge(::HasNoLogicals, S::AbstractSubsystemCode, pairs::Vect Add the gauge pairs in `pairs` to the logical operators. """ -promote_gauges_to_logical!(S::T, pairs::Vector{Int}) where {T <: AbstractSubsystemCode} = +promote_gauges_to_logical!(S::T, pairs::Vector{Int}) where {T<:AbstractSubsystemCode} = promote_gauges_to_logical!(LogicalTrait(T), S, pairs) -function promote_gauges_to_logical!(::HasLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) +function promote_gauges_to_logical!( + ::HasLogicals, + S::AbstractSubsystemCode, + pairs::Vector{Int}, +) pairs = sort!(unique!(pairs)) # will let this error naturally if pairs contains invalid elements S.logicals = S.logicals ∪ S.gauge_ops[pairs] - S.logs_mat = reduce(vcat, [reduce(vcat, S.logicals[i]) for i in 1:length(S.logicals)]) + S.logs_mat = reduce(vcat, [reduce(vcat, S.logicals[i]) for i = 1:length(S.logicals)]) S.gauge_ops = S.gauge_ops[setdiff!(append!(collect(1:length(S.gauge_ops)), pairs))] - S.g_ops_mat = reduce(vcat, [reduce(vcat, S.gauge_ops[i]) for i in 1:length(S.gauge_ops)]) + S.g_ops_mat = reduce(vcat, [reduce(vcat, S.gauge_ops[i]) for i = 1:length(S.gauge_ops)]) S.r = S.r - length(pairs) if isinteger(S.k) S.k = S.k + length(pairs) else - k = BigInt(order(S.F))^S.n // BigInt(p)^(S.stand_k + S.r) + k = BigInt(order(S.F))^S.n // BigInt(p)^(S.stand_k + S.r) isinteger(k) ? (S.k = round(Int, log(BigInt(p), k));) : (S.k = k;) end return nothing @@ -1732,10 +2220,13 @@ promote_gauges_to_logical!(::HasNoLogicals, S::AbstractSubsystemCode, pairs::Vec error("Type $(typeof(S)) has no logicals.") # TODO: this can drop to a graph state, which is why I did what I did before -promote_gauges_to_logical(S::T, pairs::Vector{Int}) where {T <: AbstractSubsystemCode} = +promote_gauges_to_logical(S::T, pairs::Vector{Int}) where {T<:AbstractSubsystemCode} = promote_gauges_to_logical(LogicalTrait(T), S, pairs) -promote_gauges_to_logical(::HasLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) = - (S_new = deepcopy(S); promote_gauges_to_logical!(HasLogicals(), S_new, pairs); return S_new) +promote_gauges_to_logical(::HasLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) = ( + S_new = deepcopy(S); + promote_gauges_to_logical!(HasLogicals(), S_new, pairs); + return S_new +) promote_gauges_to_logical(::HasNoLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) = error("Type $(typeof(S)) has no logicals.") @@ -1744,7 +2235,7 @@ promote_gauges_to_logical(::HasNoLogicals, S::AbstractSubsystemCode, pairs::Vect Swap the `X` and `Z` logicals specified by `pairs`. """ -swap_X_Z_logicals!(S::T, pairs::Vector{Int}) where {T <: AbstractSubsystemCode} = +swap_X_Z_logicals!(S::T, pairs::Vector{Int}) where {T<:AbstractSubsystemCode} = swap_X_Z_logicals!(LogicalTrait(T), S, pairs) function swap_X_Z_logicals!(::HasLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) # let indexing check for inbounds naturally @@ -1755,7 +2246,7 @@ function swap_X_Z_logicals!(::HasLogicals, S::AbstractSubsystemCode, pairs::Vect S.logicals[i][1] = S.logicals[i][2] S.logicals[i][2] = temp end - S.logs_mat = reduce(vcat, [reduce(vcat, S.logicals[i]) for i in 1:length(S.logicals)]) + S.logs_mat = reduce(vcat, [reduce(vcat, S.logicals[i]) for i = 1:length(S.logicals)]) return nothing end swap_X_Z_logicals!(::HasNoLogicals, S::AbstractSubsystemCode, pairs::Vector{Int}) = @@ -1766,9 +2257,13 @@ swap_X_Z_logicals!(::HasNoLogicals, S::AbstractSubsystemCode, pairs::Vector{Int} Swap the `X` and `Z` gauge operators specified by `pairs`. """ -swap_X_Z_gauge_operators!(S::T, pairs::Vector{Int}) where {T <: AbstractSubsystemCode} = +swap_X_Z_gauge_operators!(S::T, pairs::Vector{Int}) where {T<:AbstractSubsystemCode} = swap_X_Z_gauge_operators!(GaugeTrait(T), S, pairs) -function swap_X_Z_gauge_operators!(::HasGauges, S::AbstractSubsystemCode, pairs::Vector{Int}) +function swap_X_Z_gauge_operators!( + ::HasGauges, + S::AbstractSubsystemCode, + pairs::Vector{Int}, +) # let indexing check for inbounds naturally pairs = sort!(unique!(pairs)) temp::typeof(S.logicals[1][1]) @@ -1777,7 +2272,7 @@ function swap_X_Z_gauge_operators!(::HasGauges, S::AbstractSubsystemCode, pairs: S.gauge_ops[i][1] = S.gauge_ops[i][2] S.gauge_ops[i][2] = temp end - S.g_ops_mat = reduce(vcat, [reduce(vcat, S.gauge_ops[i]) for i in 1:length(S.gauge_ops)]) + S.g_ops_mat = reduce(vcat, [reduce(vcat, S.gauge_ops[i]) for i = 1:length(S.gauge_ops)]) return nothing end swap_X_Z_gauge_operators!(::HasNoGauges, S::AbstractSubsystemCode, pairs::Vector{Int}) = @@ -1791,7 +2286,7 @@ Return `true` if the codes are equivalent as symplectic vector spaces. # Note * This is not intended to detect if `S1` and `S2` are permutation equivalent. """ -function are_equivalent(S1::T, S2::T) where {T <: AbstractSubsystemCode} +function are_equivalent(S1::T, S2::T) where {T<:AbstractSubsystemCode} (S1.n == S2.n && S1.k == S2.k) || return false # can't compare fields directly because they are compared based on ptr addresses Int(order(S1.F)) == Int(order(S2.F)) || return false @@ -1804,12 +2299,18 @@ function are_equivalent(S1::T, S2::T) where {T <: AbstractSubsystemCode} if LogicalTrait(T) == HasLogicals() # test logicals - _has_equivalent_row_spaces(vcat(S1.logs_mat, S1.stabs), vcat(S2.logs_mat, S2.stabs)) || return false + _has_equivalent_row_spaces( + vcat(S1.logs_mat, S1.stabs), + vcat(S2.logs_mat, S2.stabs), + ) || return false end if GaugeTrait(T) == HasGauges() # test gauge operators - return _has_equivalent_row_spaces(vcat(S1.g_ops_mat, S1.stabs), vcat(S2.g_ops_mat, S2.stabs)) + return _has_equivalent_row_spaces( + vcat(S1.g_ops_mat, S1.stabs), + vcat(S2.g_ops_mat, S2.stabs), + ) else return true end @@ -1821,7 +2322,7 @@ end Return the code induced by adding either the first of `gauge_operators(S)[pair]` to the stabilizers if `which = :X` or the second if `which = :Z`. """ -fix_gauge(S::T, pair::Int, which::Symbol) where {T <: AbstractSubsystemCode} = +fix_gauge(S::T, pair::Int, which::Symbol) where {T<:AbstractSubsystemCode} = fix_gauge(GaugeTrait(T), S, pair, which) function fix_gauge(::HasGauges, S::AbstractSubsystemCode, pair::Int, which::Symbol) if which == :X @@ -1871,10 +2372,12 @@ function show(io::IO, S::AbstractSubsystemCode) println(io, " subsystem code") end end - + if get(io, :compact, true) && S.n <= 30 - if isa(S, SubsystemCodeCSS) || isa(S, StabilizerCodeCSS) || - isa(S, GraphStateStabilizerCSS) || isa(S, GraphStateSubsystemCSS) + if isa(S, SubsystemCodeCSS) || + isa(S, StabilizerCodeCSS) || + isa(S, GraphStateStabilizerCSS) || + isa(S, GraphStateSubsystemCSS) num_X = num_X_stabs(S) if S.overcomplete @@ -1882,9 +2385,9 @@ function show(io::IO, S::AbstractSubsystemCode) else println(io, "X-stabilizer matrix: $num_X × $(S.n)") end - for r in 1:num_X + for r = 1:num_X print(io, "\t chi($(S.X_signs[r])) ") - for c in 1:S.n + for c = 1:S.n if c != S.n print(io, "$(S.X_stabs[r, c]) ") elseif c == S.n && r != num_X @@ -1902,9 +2405,9 @@ function show(io::IO, S::AbstractSubsystemCode) else println(io, "Z-stabilizer matrix: $num_Z × $(S.n)") end - for r in 1:num_Z + for r = 1:num_Z print(io, "\t chi($(S.Z_signs[r])) ") - for c in 1:S.n + for c = 1:S.n if c != S.n print(io, "$(S.Z_stabs[r, c]) ") elseif c == S.n && r != num_Z @@ -1921,9 +2424,9 @@ function show(io::IO, S::AbstractSubsystemCode) else println(io, "Stabilizer matrix: $num_stabs × $(2 * S.n)") end - for r in 1:num_stabs + for r = 1:num_stabs print(io, "\t chi($(S.signs[r])) ") - for c in 1:2 * S.n + for c = 1:(2*S.n) if c != 2 * S.n print(io, "$(S.stabs[r, c]) ") elseif c == 2 * S.n && r != num_stabs @@ -1947,11 +2450,11 @@ function _all_stabilizers(S::AbstractStabilizerCode, only_print::Bool = false) E = quadraticfield(S) all = Vector{typeof(S.stabs)}() stabs = S.stabs - for iter in Base.Iterators.product([0:(Int64(characteristic(S.F)) - 1) - for _ in 1:nrows(stabs)]...) + for iter in + Base.Iterators.product([0:(Int64(characteristic(S.F))-1) for _ = 1:nrows(stabs)]...) stab = E(iter[1]) * stabs[1, :] - for r in 2:nrows(stabs) + for r = 2:nrows(stabs) if !iszero(iter[r]) stab += E(iter[r]) * stabs[r, :] end @@ -2003,7 +2506,10 @@ Return the code permuted by `σ`. # Notes * If `σ` is a vector, it is interpreted as the desired column order for the stabilizers of `S`. """ -function permute_code!(S::AbstractSubsystemCode, σ::Union{PermGroupElem, Perm{Int}, Vector{Int}}) +function permute_code!( + S::AbstractSubsystemCode, + σ::Union{PermGroupElem,Perm{Int},Vector{Int}}, +) perm1 = transpose(permutation_matrix(S.F, typeof(σ) <: Perm ? σ.d : σ)) perm = perm1 ⊕ perm1 S.stabs = S.stabs * perm @@ -2032,7 +2538,7 @@ function permute_code!(S::AbstractSubsystemCode, σ::Union{PermGroupElem, Perm{I end return nothing end -permute_code(S::AbstractSubsystemCode, σ::Union{PermGroupElem, Perm{Int}, Vector{Int}}) = +permute_code(S::AbstractSubsystemCode, σ::Union{PermGroupElem,Perm{Int},Vector{Int}}) = (S_new = copy(S); permute_code!(S_new, σ); return S_new) """ @@ -2045,29 +2551,38 @@ Return the code created by added `row` to the stabilizers of `S`. The unaffected logical operators are kept during the update and only those which don't commute with the new stabilizer are recomputed. """ -function augment(S::AbstractSubsystemCode, row::CTMatrixTypes; verbose::Bool = true, logs_alg::Symbol = :sys_eqs) +function augment( + S::AbstractSubsystemCode, + row::CTMatrixTypes; + verbose::Bool = true, + logs_alg::Symbol = :sys_eqs, +) logs_alg ∈ (:sys_eqs, :VS) || throw(ArgumentError("Unrecognized logicals algorithm")) - typeof(S.stabs) == typeof(row) || throw(ArgumentError("Vector of different (Julia) type than stabilizers")) + typeof(S.stabs) == typeof(row) || + throw(ArgumentError("Vector of different (Julia) type than stabilizers")) iszero(row) && return S - nrows(row) == 1 || throw(ArgumentError("Only one stabilizer may be passed in at a time.")) + nrows(row) == 1 || + throw(ArgumentError("Only one stabilizer may be passed in at a time.")) # stabilizers - prod = hcat(S.stabs[:, S.n + 1:end], -S.stabs[:, 1:S.n]) * transpose(row) + prod = hcat(S.stabs[:, (S.n+1):end], -S.stabs[:, 1:S.n]) * transpose(row) if iszero(prod) - verbose && println("Vector is already in the stabilizer group. Nothing to update.") + verbose && println("Vector is already in the stabilizer group. Nothing to update.") S_new = deepcopy(S) S_new.stabs = vcat(S.stabs, row) S_new.overcomplete = true return S_new else stabs_to_keep = Vector{Int}() - for i in 1:nrows(S.stabs) + for i = 1:nrows(S.stabs) iszero(prod[i]) && append!(stabs_to_keep, i, i + 1) end if isempty(stabs_to_keep) - verbose && println("The vector anticommutes with all stabilizers. The new stabilizer group is just the vector.") + verbose && println( + "The vector anticommutes with all stabilizers. The new stabilizer group is just the vector.", + ) stabs = row else update = setdiff(1:nrows(S.stabs), stabs_to_keep) @@ -2085,14 +2600,14 @@ function augment(S::AbstractSubsystemCode, row::CTMatrixTypes; verbose::Bool = t # logicals if LogicalTrait(typeof(S)) == HasLogicals() - prod = hcat(S.logs_mat[:, S.n + 1:end], -S.logs_mat[:, 1:S.n]) * transpose(row) + prod = hcat(S.logs_mat[:, (S.n+1):end], -S.logs_mat[:, 1:S.n]) * transpose(row) logs_to_keep = Vector{Int}() log_pairs_to_keep = Vector{Int}() pair = 1 - for i in 1:2:nrows(S.logs_mat) + for i = 1:2:nrows(S.logs_mat) # this is predicated on the idea that the pairs are stacked together in this matrix # TODO: write a unit test checking this never changes - if iszero(prod[i]) && iszero(prod[i + 1]) + if iszero(prod[i]) && iszero(prod[i+1]) append!(logs_to_keep, i, i + 1) append!(log_pairs_to_keep, pair) end @@ -2120,14 +2635,14 @@ function augment(S::AbstractSubsystemCode, row::CTMatrixTypes; verbose::Bool = t # gauges if GaugeTrait(typeof(S)) == HasGauges() - prod = hcat(S.g_ops_mat[:, S.n + 1:end], -S.g_ops_mat[:, 1:S.n]) * transpose(row) + prod = hcat(S.g_ops_mat[:, (S.n+1):end], -S.g_ops_mat[:, 1:S.n]) * transpose(row) g_ops_to_keep = Vector{Int}() g_op_pairs_to_keep = Vector{Int}() pair = 1 - for i in 1:2:nrows(S.g_ops_mat) + for i = 1:2:nrows(S.g_ops_mat) # this is predicated on the idea that the pairs are stacked together in this matrix # TODO: write a unit test checking this never changes - if iszero(prod[i]) && iszero(prod[i + 1]) + if iszero(prod[i]) && iszero(prod[i+1]) append!(g_ops_to_keep, i, i + 1) append!(g_op_pairs_to_keep, pair) end @@ -2147,7 +2662,8 @@ function augment(S::AbstractSubsystemCode, row::CTMatrixTypes; verbose::Bool = t display(update) end end - isempty(update) ? (gauge_ops = S.gauge_ops;) : (gauge_ops = S.gauge_ops[g_ops_to_keep, :];) + isempty(update) ? (gauge_ops = S.gauge_ops;) : + (gauge_ops = S.gauge_ops[g_ops_to_keep, :];) end else gauge_ops = zero_matrix(S.F, 1, 2 * S.n) @@ -2155,7 +2671,7 @@ function augment(S::AbstractSubsystemCode, row::CTMatrixTypes; verbose::Bool = t # compute newly opened degrees of freedom temp = _remove_empty(vcat(stabs, logs, gauge_ops), :rows) - temp = kernel(hcat(temp[:, S.n + 1:end], -temp[:, 1:S.n]), side = :right) + temp = kernel(hcat(temp[:, (S.n+1):end], -temp[:, 1:S.n]), side = :right) rnk_temp = rank(temp) if ncols(temp) == rnk_temp temp = transpose(temp) @@ -2163,8 +2679,8 @@ function augment(S::AbstractSubsystemCode, row::CTMatrixTypes; verbose::Bool = t # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(temp) temp_tr = zero_matrix(base_ring(temp), rnk_temp, nr) - for r in 1:nr - for c in 1:rnk_temp + for r = 1:nr + for c = 1:rnk_temp !iszero(temp[r, c]) && (temp_tr[c, r] = temp[r, c];) end end @@ -2185,11 +2701,17 @@ Return the code created by removing the stabilizers indexed by `rows`. * The goal of this function is to track how the logical operators update through this process. Here, the original logical pairs are kept and an appropriate number of new pairs are added. """ -function expurgate(S::AbstractSubsystemCode, rows::Vector{Int}; verbose::Bool = true, logs_alg::Symbol = :sys_eqs) +function expurgate( + S::AbstractSubsystemCode, + rows::Vector{Int}; + verbose::Bool = true, + logs_alg::Symbol = :sys_eqs, +) logs_alg ∈ (:sys_eqs, :VS) || throw(ArgumentError("Unrecognized logicals algorithm")) num_stabs = nrows(S.stabs) - rows ⊆ 1:num_stabs || throw(ArgumentError("Argument `rows` not a subset of the number of stabilizers.")) + rows ⊆ 1:num_stabs || + throw(ArgumentError("Argument `rows` not a subset of the number of stabilizers.")) rows == 1:num_stabs && throw(ArgumentError("Cannot remove all stabilizers")) verbose && println("Removing stabilizers: $rows") @@ -2201,7 +2723,7 @@ function expurgate(S::AbstractSubsystemCode, rows::Vector{Int}; verbose::Bool = if GaugeTrait(typeof(S)) == HasGauges() temp = vcat(temp, S.g_ops_mat) end - H = kernel(hcat(temp[:, S.n + 1:end], -temp[:, 1:S.n]), side = :right) + H = kernel(hcat(temp[:, (S.n+1):end], -temp[:, 1:S.n]), side = :right) rnk_H = rank(H) if ncols(H) == rnk_H H_tr = transpose(H) @@ -2209,8 +2731,8 @@ function expurgate(S::AbstractSubsystemCode, rows::Vector{Int}; verbose::Bool = # remove empty columns for flint objects https://github.com/oscar-system/Oscar.jl/issues/1062 nr = nrows(H) H_tr = zero_matrix(base_ring(H), rnk_H, nr) - for r in 1:nr - for c in 1:rnk_H + for r = 1:nr + for c = 1:rnk_H !iszero(H[r, c]) && (H_tr[c, r] = H[r, c];) end end @@ -2221,17 +2743,26 @@ function expurgate(S::AbstractSubsystemCode, rows::Vector{Int}; verbose::Bool = verbose && println("No new logicals need to be add") S_new = deepcopy(S) S_new.stabs = new_stabs - rank(new_stabs) == nrows(new_stabs) ? (S.overcomplete = false;) : (S.overcomplete = true;) + rank(new_stabs) == nrows(new_stabs) ? (S.overcomplete = false;) : + (S.overcomplete = true;) return S_new else new_log_pairs = _make_pairs(new_logs) verbose && println("New logical pairs:") verbose && display(new_log_pairs) if GaugeTrait(typeof(S)) == HasGauges() - return SubsystemCode(new_stabs, vcat(S.logs_mat, reduce(vcat, reduce(vcat, new_log_pairs))), S.g_ops_mat, char_vec = S.char_vec) + return SubsystemCode( + new_stabs, + vcat(S.logs_mat, reduce(vcat, reduce(vcat, new_log_pairs))), + S.g_ops_mat, + char_vec = S.char_vec, + ) else S_new = StabilizerCode(new_stabs, char_vec = S.char_vec) - set_logicals!(S_new, vcat(S.logs_mat, reduce(vcat, reduce(vcat, new_log_pairs)))) + set_logicals!( + S_new, + vcat(S.logs_mat, reduce(vcat, reduce(vcat, new_log_pairs))), + ) return S_new end end @@ -2242,7 +2773,7 @@ function _standard_form_stabilizer(M::CTMatrixTypes) # if the stabilizer is overdetermined, remove unnecessary rows _rref_no_col_swap!(stabs, 1:size(stabs, 1), 1:size(stabs, 2)) nr = size(stabs, 1) - for i in size(stabs, 1):-1:1 + for i = size(stabs, 1):-1:1 nr = i iszero(stabs[i, :]) || break end @@ -2254,7 +2785,7 @@ function _standard_form_stabilizer(M::CTMatrixTypes) k = n - nr # put S in standard form r, P1 = _rref_symp_col_swap!(stabs, 1:nr, 1:n) - _, P2 = _rref_symp_col_swap!(stabs, (r + 1):nr, (n + r + 1):2n) + _, P2 = _rref_symp_col_swap!(stabs, (r+1):nr, (n+r+1):2n) P = if ismissing(P1) && ismissing(P2) missing @@ -2268,31 +2799,36 @@ function _standard_form_stabilizer(M::CTMatrixTypes) return stabs, P, r, k, n - k end -function _logicals_standard_form(stabs::CTMatrixTypes, n::Int, k::Int, r::Int, P::Union{Missing, - CTMatrixTypes}) +function _logicals_standard_form( + stabs::CTMatrixTypes, + n::Int, + k::Int, + r::Int, + P::Union{Missing,CTMatrixTypes}, +) F = base_ring(stabs) F_one = F(1) logs = zero_matrix(F, 2k, 2n) - E = stabs[r + 1:n - k, 2n - k + 1:2n] - C1 = stabs[1:r, n + r + 1:2n - k] + E = stabs[(r+1):(n-k), (2n-k+1):2n] + C1 = stabs[1:r, (n+r+1):(2n-k)] C1_E = C1 * E - for i in 1:k + for i = 1:k # put I in a couple of places - logs[i, n - k + i] = F_one - logs[k + i, 2n - k + i] = F_one + logs[i, n-k+i] = F_one + logs[k+i, 2n-k+i] = F_one # put in E^T - for j in 1:(n - k - r) - logs[i, j + r] = stabs[r + j, 2n - k + i] + for j = 1:(n-k-r) + logs[i, j+r] = stabs[r+j, 2n-k+i] end - for j in 1:r + for j = 1:r # put in E^T * C1^T + C2^T - logs[i, n + j] = C1_E[j, i] + stabs[j, 2n - k + i] + logs[i, n+j] = C1_E[j, i] + stabs[j, 2n-k+i] # put in A2^T - logs[k + i, n + j] = stabs[j, n - k + i] + logs[k+i, n+j] = stabs[j, n-k+i] end end return ismissing(P) ? logs : logs * P diff --git a/src/Quantum/types.jl b/src/Quantum/types.jl index 40e98f22..f932c569 100644 --- a/src/Quantum/types.jl +++ b/src/Quantum/types.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # abstract types +# abstract types ############################# abstract type AbstractSubsystemCode <: AbstractAdditiveCode end @@ -28,272 +28,272 @@ abstract type AbstractGeneralizedToricCode <: AbstractStabilizerCodeCSS end abstract type AbstractQuantumNoiseChannel <: AbstractNoiseChannel end ############################# - # concrete types +# concrete types ############################# ############################# - # subsystemcode.jl +# subsystemcode.jl ############################# # TODO: make sure these have the same info and are in the same order mutable struct SubsystemCodeCSS <: AbstractSubsystemCodeCSS - F::CTFieldTypes - n::Int - k::Union{Int, Rational{BigInt}} - r::Int - d_bare::Union{Int, Missing} - d_dressed::Union{Int, Missing} - dx_bare::Union{Int, Missing} - dx_dressed::Union{Int, Missing} - dz_bare::Union{Int, Missing} - dz_dressed::Union{Int, Missing} - l_bound_bare::Int # lower bound on d_bare - u_bound_bare::Int # upper bound on d_bare - l_bound_dressed::Int # lower bound on d_dressed - u_bound_dressed::Int # upper bound on d_dressed - l_bound_dx_bare::Int # lower bound on dx_bare - u_bound_dx_bare::Int # upper bound on dx_bare - l_bound_dz_bare::Int # lower bound on dz_bare - u_bound_dz_bare::Int # upper bound on dz_bare - l_bound_dx_dressed::Int # lower bound on dz_dressed - u_bound_dx_dressed::Int # upper bound on dz_dressed - l_bound_dz_dressed::Int # lower bound on dz_dressed - u_bound_dz_dressed::Int # upper bound on dz_dressed - stabs::CTMatrixTypes - X_stabs::CTMatrixTypes - Z_stabs::CTMatrixTypes - X_orig_code::Union{S, Missing} where S <: AbstractLinearCode - Z_orig_code::Union{S, Missing} where S <: AbstractLinearCode - signs::Vector{zzModRingElem} - X_signs::Vector{zzModRingElem} - Z_signs::Vector{zzModRingElem} - logicals::Vector{Tuple{T, T}} where T <: CTMatrixTypes - logs_mat::CTMatrixTypes - char_vec::Vector{zzModRingElem} - gauge_ops::Vector{Tuple{T, T}} where T <: CTMatrixTypes - g_ops_mat::CTMatrixTypes - overcomplete::Bool - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - X_metacheck::Union{CTMatrixTypes, Missing} - Z_metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Int + k::Union{Int,Rational{BigInt}} + r::Int + d_bare::Union{Int,Missing} + d_dressed::Union{Int,Missing} + dx_bare::Union{Int,Missing} + dx_dressed::Union{Int,Missing} + dz_bare::Union{Int,Missing} + dz_dressed::Union{Int,Missing} + l_bound_bare::Int # lower bound on d_bare + u_bound_bare::Int # upper bound on d_bare + l_bound_dressed::Int # lower bound on d_dressed + u_bound_dressed::Int # upper bound on d_dressed + l_bound_dx_bare::Int # lower bound on dx_bare + u_bound_dx_bare::Int # upper bound on dx_bare + l_bound_dz_bare::Int # lower bound on dz_bare + u_bound_dz_bare::Int # upper bound on dz_bare + l_bound_dx_dressed::Int # lower bound on dz_dressed + u_bound_dx_dressed::Int # upper bound on dz_dressed + l_bound_dz_dressed::Int # lower bound on dz_dressed + u_bound_dz_dressed::Int # upper bound on dz_dressed + stabs::CTMatrixTypes + X_stabs::CTMatrixTypes + Z_stabs::CTMatrixTypes + X_orig_code::Union{S,Missing} where {S<:AbstractLinearCode} + Z_orig_code::Union{S,Missing} where {S<:AbstractLinearCode} + signs::Vector{zzModRingElem} + X_signs::Vector{zzModRingElem} + Z_signs::Vector{zzModRingElem} + logicals::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + logs_mat::CTMatrixTypes + char_vec::Vector{zzModRingElem} + gauge_ops::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + g_ops_mat::CTMatrixTypes + overcomplete::Bool + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + X_metacheck::Union{CTMatrixTypes,Missing} + Z_metacheck::Union{CTMatrixTypes,Missing} end mutable struct SubsystemCode <: AbstractSubsystemCode - F::CTFieldTypes - n::Int - k::Union{Int, Rational{BigInt}} - r::Int - d_bare::Union{Int, Missing} - d_dressed::Union{Int, Missing} - l_bound_bare::Int # lower bound on d_bare - u_bound_bare::Int # upper bound on d_bare - l_bound_dressed::Int # lower bound on d_dressed - u_bound_dressed::Int # upper bound on d_dressed - stabs::CTMatrixTypes - logicals::Vector{Tuple{T, T}} where T <: CTMatrixTypes - logs_mat::CTMatrixTypes - char_vec::Vector{zzModRingElem} - signs::Vector{zzModRingElem} - gauge_ops::Vector{Tuple{T, T}} where T <: CTMatrixTypes - g_ops_mat::CTMatrixTypes - overcomplete::Bool - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Int + k::Union{Int,Rational{BigInt}} + r::Int + d_bare::Union{Int,Missing} + d_dressed::Union{Int,Missing} + l_bound_bare::Int # lower bound on d_bare + u_bound_bare::Int # upper bound on d_bare + l_bound_dressed::Int # lower bound on d_dressed + u_bound_dressed::Int # upper bound on d_dressed + stabs::CTMatrixTypes + logicals::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + logs_mat::CTMatrixTypes + char_vec::Vector{zzModRingElem} + signs::Vector{zzModRingElem} + gauge_ops::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + g_ops_mat::CTMatrixTypes + overcomplete::Bool + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + metacheck::Union{CTMatrixTypes,Missing} end ############################# - # stabilizercode.jl +# stabilizercode.jl ############################# mutable struct StabilizerCodeCSS <: AbstractStabilizerCodeCSS - F::CTFieldTypes - n::Int - k::Union{Int, Rational{BigInt}} - d::Union{Int, Missing} - dx::Union{Int, Missing} - dz::Union{Int, Missing} - l_bound::Int # lower bound on d - u_bound::Int # upper bound on d - l_bound_dx::Int # lower bound on dx - u_bound_dx::Int # upper bound on dx - l_bound_dz::Int # lower bound on dz - u_bound_dz::Int # upper bound on dz - stabs::CTMatrixTypes - X_stabs::CTMatrixTypes - Z_stabs::CTMatrixTypes - X_orig_code::Union{S, Missing} where S <: AbstractLinearCode - Z_orig_code::Union{S, Missing} where S <: AbstractLinearCode - signs::Vector{zzModRingElem} - X_signs::Vector{zzModRingElem} - Z_signs::Vector{zzModRingElem} - logicals::Vector{Tuple{T, T}} where T <: CTMatrixTypes - logs_mat::CTMatrixTypes - char_vec::Vector{zzModRingElem} - sgn_CWE_stabs::Union{WeightEnumerator, Missing} # signed complete weight enumerator - sgn_CWE_dual::Union{WeightEnumerator, Missing} # S^⟂ - sgn_CWE_logs::Union{WeightEnumerator, Missing} - overcomplete::Bool - pure::Union{Bool, Missing} - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - X_metacheck::Union{CTMatrixTypes, Missing} - Z_metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Int + k::Union{Int,Rational{BigInt}} + d::Union{Int,Missing} + dx::Union{Int,Missing} + dz::Union{Int,Missing} + l_bound::Int # lower bound on d + u_bound::Int # upper bound on d + l_bound_dx::Int # lower bound on dx + u_bound_dx::Int # upper bound on dx + l_bound_dz::Int # lower bound on dz + u_bound_dz::Int # upper bound on dz + stabs::CTMatrixTypes + X_stabs::CTMatrixTypes + Z_stabs::CTMatrixTypes + X_orig_code::Union{S,Missing} where {S<:AbstractLinearCode} + Z_orig_code::Union{S,Missing} where {S<:AbstractLinearCode} + signs::Vector{zzModRingElem} + X_signs::Vector{zzModRingElem} + Z_signs::Vector{zzModRingElem} + logicals::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + logs_mat::CTMatrixTypes + char_vec::Vector{zzModRingElem} + sgn_CWE_stabs::Union{WeightEnumerator,Missing} # signed complete weight enumerator + sgn_CWE_dual::Union{WeightEnumerator,Missing} # S^⟂ + sgn_CWE_logs::Union{WeightEnumerator,Missing} + overcomplete::Bool + pure::Union{Bool,Missing} + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + X_metacheck::Union{CTMatrixTypes,Missing} + Z_metacheck::Union{CTMatrixTypes,Missing} end mutable struct StabilizerCode <: AbstractStabilizerCode - F::CTFieldTypes - n::Int - k::Union{Int, Rational{BigInt}} - d::Union{Int, Missing} - l_bound::Int # lower bound on d - u_bound::Int # upper bound on d - stabs::CTMatrixTypes - logicals::Vector{Tuple{T, T}} where T <: CTMatrixTypes - logs_mat::CTMatrixTypes - char_vec::Vector{zzModRingElem} - signs::Vector{zzModRingElem} - sgn_CWE_stabs::Union{WeightEnumerator, Missing} # signed complete weight enumerator - sgn_CWE_dual::Union{WeightEnumerator, Missing} # S^⟂ - sgn_CWE_logs::Union{WeightEnumerator, Missing} - overcomplete::Bool - pure::Union{Bool, Missing} - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Int + k::Union{Int,Rational{BigInt}} + d::Union{Int,Missing} + l_bound::Int # lower bound on d + u_bound::Int # upper bound on d + stabs::CTMatrixTypes + logicals::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + logs_mat::CTMatrixTypes + char_vec::Vector{zzModRingElem} + signs::Vector{zzModRingElem} + sgn_CWE_stabs::Union{WeightEnumerator,Missing} # signed complete weight enumerator + sgn_CWE_dual::Union{WeightEnumerator,Missing} # S^⟂ + sgn_CWE_logs::Union{WeightEnumerator,Missing} + overcomplete::Bool + pure::Union{Bool,Missing} + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + metacheck::Union{CTMatrixTypes,Missing} end ############################# - # graphstate.jl +# graphstate.jl ############################# mutable struct GraphStateSubsystem <: AbstractGraphStateSubsystem - F::CTFieldTypes - n::Int - k::Int - r::Int - d_bare::Union{Int, Missing} - d_dressed::Union{Int, Missing} - l_bound_bare::Int # lower bound on d_bare - u_bound_bare::Int # upper bound on d_bare - l_bound_dressed::Int # lower bound on d_dressed - u_bound_dressed::Int # upper bound on d_dressed - stabs::CTMatrixTypes - char_vec::Vector{zzModRingElem} - signs::Vector{zzModRingElem} - wtenum::Union{WeightEnumerator, Missing} # signed complete weight enumerator - overcomplete::Bool - gauge_ops::Vector{Tuple{T, T}} where T <: CTMatrixTypes - g_ops_mat::CTMatrixTypes - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Int + k::Int + r::Int + d_bare::Union{Int,Missing} + d_dressed::Union{Int,Missing} + l_bound_bare::Int # lower bound on d_bare + u_bound_bare::Int # upper bound on d_bare + l_bound_dressed::Int # lower bound on d_dressed + u_bound_dressed::Int # upper bound on d_dressed + stabs::CTMatrixTypes + char_vec::Vector{zzModRingElem} + signs::Vector{zzModRingElem} + wtenum::Union{WeightEnumerator,Missing} # signed complete weight enumerator + overcomplete::Bool + gauge_ops::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + g_ops_mat::CTMatrixTypes + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + metacheck::Union{CTMatrixTypes,Missing} end mutable struct GraphStateSubsystemCSS <: AbstractGraphStateSubsystemCSS - F::CTFieldTypes - n::Int - k::Int - r::Int - d_bare::Union{Int, Missing} - d_dressed::Union{Int, Missing} - dx_bare::Union{Int, Missing} - dx_dressed::Union{Int, Missing} - dz_bare::Union{Int, Missing} - dz_dressed::Union{Int, Missing} - l_bound_bare::Int # lower bound on d_bare - u_bound_bare::Int # upper bound on d_bare - l_bound_dressed::Int # lower bound on d_dressed - u_bound_dressed::Int # upper bound on d_dressed - l_bound_dx_bare::Int # lower bound on dx_bare - u_bound_dx_bare::Int # upper bound on dx_bare - l_bound_dz_bare::Int # lower bound on dz_bare - u_bound_dz_bare::Int # upper bound on dz_bare - l_bound_dx_dressed::Int # lower bound on dz_dressed - u_bound_dx_dressed::Int # upper bound on dz_dressed - l_bound_dz_dressed::Int # lower bound on dz_dressed - u_bound_dz_dressed::Int # upper bound on dz_dressed - stabs::CTMatrixTypes - X_stabs::CTMatrixTypes - Z_stabs::CTMatrixTypes - X_orig_code::Union{S, Missing} where S <: AbstractLinearCode - Z_orig_code::Union{S, Missing} where S <: AbstractLinearCode - signs::Vector{zzModRingElem} - X_signs::Vector{zzModRingElem} - Z_signs::Vector{zzModRingElem} - char_vec::Vector{zzModRingElem} - sgn_CWE_stabs::Union{WeightEnumerator, Missing} # signed complete weight enumerator - overcomplete::Bool - gauge_ops::Vector{Tuple{T, T}} where T <: CTMatrixTypes - g_ops_mat::CTMatrixTypes - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - X_metacheck::Union{CTMatrixTypes, Missing} - Z_metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Int + k::Int + r::Int + d_bare::Union{Int,Missing} + d_dressed::Union{Int,Missing} + dx_bare::Union{Int,Missing} + dx_dressed::Union{Int,Missing} + dz_bare::Union{Int,Missing} + dz_dressed::Union{Int,Missing} + l_bound_bare::Int # lower bound on d_bare + u_bound_bare::Int # upper bound on d_bare + l_bound_dressed::Int # lower bound on d_dressed + u_bound_dressed::Int # upper bound on d_dressed + l_bound_dx_bare::Int # lower bound on dx_bare + u_bound_dx_bare::Int # upper bound on dx_bare + l_bound_dz_bare::Int # lower bound on dz_bare + u_bound_dz_bare::Int # upper bound on dz_bare + l_bound_dx_dressed::Int # lower bound on dz_dressed + u_bound_dx_dressed::Int # upper bound on dz_dressed + l_bound_dz_dressed::Int # lower bound on dz_dressed + u_bound_dz_dressed::Int # upper bound on dz_dressed + stabs::CTMatrixTypes + X_stabs::CTMatrixTypes + Z_stabs::CTMatrixTypes + X_orig_code::Union{S,Missing} where {S<:AbstractLinearCode} + Z_orig_code::Union{S,Missing} where {S<:AbstractLinearCode} + signs::Vector{zzModRingElem} + X_signs::Vector{zzModRingElem} + Z_signs::Vector{zzModRingElem} + char_vec::Vector{zzModRingElem} + sgn_CWE_stabs::Union{WeightEnumerator,Missing} # signed complete weight enumerator + overcomplete::Bool + gauge_ops::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + g_ops_mat::CTMatrixTypes + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + X_metacheck::Union{CTMatrixTypes,Missing} + Z_metacheck::Union{CTMatrixTypes,Missing} end mutable struct GraphStateStabilizer <: AbstractGraphStateStabilizer - F::CTFieldTypes - n::Int - k::Int - d::Union{Int, Missing} - l_bound::Int # lower bound on d - u_bound::Int # upper bound on d - stabs::CTMatrixTypes - char_vec::Vector{zzModRingElem} - signs::Vector{zzModRingElem} - sgn_CWE_stabs::Union{WeightEnumerator, Missing} # signed complete weight enumerator - overcomplete::Bool - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Int + k::Int + d::Union{Int,Missing} + l_bound::Int # lower bound on d + u_bound::Int # upper bound on d + stabs::CTMatrixTypes + char_vec::Vector{zzModRingElem} + signs::Vector{zzModRingElem} + sgn_CWE_stabs::Union{WeightEnumerator,Missing} # signed complete weight enumerator + overcomplete::Bool + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + metacheck::Union{CTMatrixTypes,Missing} end mutable struct GraphStateStabilizerCSS <: AbstractGraphStateStabilizerCSS - F::CTFieldTypes - n::Int - k::Int - d::Union{Int, Missing} - dx::Union{Int, Missing} - dz::Union{Int, Missing} - l_bound::Int # lower bound on d - u_bound::Int # upper bound on d - l_bound_dx::Int # lower bound on dx - u_bound_dx::Int # upper bound on dx - l_bound_dz::Int # lower bound on dz - u_bound_dz::Int # upper bound on dz - stabs::CTMatrixTypes - X_stabs::CTMatrixTypes - Z_stabs::CTMatrixTypes - X_orig_code::Union{S, Missing} where S <: AbstractLinearCode - Z_orig_code::Union{S, Missing} where S <: AbstractLinearCode - signs::Vector{zzModRingElem} - X_signs::Vector{zzModRingElem} - Z_signs::Vector{zzModRingElem} - char_vec::Vector{zzModRingElem} - sgn_CWE_stabs::Union{WeightEnumerator,Missing} # signed complete weight enumerator - overcomplete::Bool - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - X_metacheck::Union{CTMatrixTypes, Missing} - Z_metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Int + k::Int + d::Union{Int,Missing} + dx::Union{Int,Missing} + dz::Union{Int,Missing} + l_bound::Int # lower bound on d + u_bound::Int # upper bound on d + l_bound_dx::Int # lower bound on dx + u_bound_dx::Int # upper bound on dx + l_bound_dz::Int # lower bound on dz + u_bound_dz::Int # upper bound on dz + stabs::CTMatrixTypes + X_stabs::CTMatrixTypes + Z_stabs::CTMatrixTypes + X_orig_code::Union{S,Missing} where {S<:AbstractLinearCode} + Z_orig_code::Union{S,Missing} where {S<:AbstractLinearCode} + signs::Vector{zzModRingElem} + X_signs::Vector{zzModRingElem} + Z_signs::Vector{zzModRingElem} + char_vec::Vector{zzModRingElem} + sgn_CWE_stabs::Union{WeightEnumerator,Missing} # signed complete weight enumerator + overcomplete::Bool + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + X_metacheck::Union{CTMatrixTypes,Missing} + Z_metacheck::Union{CTMatrixTypes,Missing} end ############################# @@ -303,38 +303,38 @@ end # J. Tillich, G. Zémor. "Quantum LDPC codes with positive rate and minimum distance # proportional to n^(1/2)". (2013) arXiv:0903.0566v2 mutable struct HypergraphProductCode <: AbstractHypergraphProductCode - F::CTFieldTypes - n::Integer - k::Union{Integer, Rational{BigInt}} - d::Union{Integer, Missing} - dx::Union{Integer, Missing} - dz::Union{Integer, Missing} - l_bound::Int # lower bound on d - u_bound::Int # upper bound on d - l_bound_dx::Int # lower bound on dx - u_bound_dx::Int # upper bound on dx - l_bound_dz::Int # lower bound on dz - u_bound_dz::Int # upper bound on dz - stabs::CTMatrixTypes - X_stabs::CTMatrixTypes - Z_stabs::CTMatrixTypes - C1::Union{S, Missing} where S <: AbstractLinearCode - C2::Union{S, Missing} where S <: AbstractLinearCode - signs::Vector{zzModRingElem} - X_signs::Vector{zzModRingElem} - Z_signs::Vector{zzModRingElem} - logicals::Vector{Tuple{T, T}} where T <: CTMatrixTypes - logs_mat::CTMatrixTypes - char_vec::Vector{zzModRingElem} - overcomplete::Bool - stabs_stand::CTMatrixTypes - stand_r::Int - stand_k::Int - P_stand::Union{CTMatrixTypes, Missing} - sgn_CWE_stabs::Union{WeightEnumerator, Missing} # signed complete weight enumerator - sgn_CWE_dual::Union{WeightEnumerator, Missing} # S^⟂ - X_metacheck::Union{CTMatrixTypes, Missing} - Z_metacheck::Union{CTMatrixTypes, Missing} + F::CTFieldTypes + n::Integer + k::Union{Integer,Rational{BigInt}} + d::Union{Integer,Missing} + dx::Union{Integer,Missing} + dz::Union{Integer,Missing} + l_bound::Int # lower bound on d + u_bound::Int # upper bound on d + l_bound_dx::Int # lower bound on dx + u_bound_dx::Int # upper bound on dx + l_bound_dz::Int # lower bound on dz + u_bound_dz::Int # upper bound on dz + stabs::CTMatrixTypes + X_stabs::CTMatrixTypes + Z_stabs::CTMatrixTypes + C1::Union{S,Missing} where {S<:AbstractLinearCode} + C2::Union{S,Missing} where {S<:AbstractLinearCode} + signs::Vector{zzModRingElem} + X_signs::Vector{zzModRingElem} + Z_signs::Vector{zzModRingElem} + logicals::Vector{Tuple{T,T}} where {T<:CTMatrixTypes} + logs_mat::CTMatrixTypes + char_vec::Vector{zzModRingElem} + overcomplete::Bool + stabs_stand::CTMatrixTypes + stand_r::Int + stand_k::Int + P_stand::Union{CTMatrixTypes,Missing} + sgn_CWE_stabs::Union{WeightEnumerator,Missing} # signed complete weight enumerator + sgn_CWE_dual::Union{WeightEnumerator,Missing} # S^⟂ + X_metacheck::Union{CTMatrixTypes,Missing} + Z_metacheck::Union{CTMatrixTypes,Missing} end ############################# @@ -342,42 +342,53 @@ end ############################# struct GeneralizedToricCode <: AbstractGeneralizedToricCode - LR::AbstractAlgebra.Generic.LaurentMPolyWrapRing{fpFieldElem, fpMPolyRing} - F::CTFieldTypes - f::CTLRPolyElem - g::CTLRPolyElem + LR::AbstractAlgebra.Generic.LaurentMPolyWrapRing{fpFieldElem,fpMPolyRing} + F::CTFieldTypes + f::CTLRPolyElem + g::CTLRPolyElem end struct FiniteGeneralizedToricCode <: AbstractGeneralizedToricCode - LR::AbstractAlgebra.Generic.LaurentMPolyWrapRing{fpFieldElem, fpMPolyRing} - F::CTFieldTypes - f::CTLRPolyElem - g::CTLRPolyElem - a1::Tuple{Int, Int} - a2::Tuple{Int, Int} + LR::AbstractAlgebra.Generic.LaurentMPolyWrapRing{fpFieldElem,fpMPolyRing} + F::CTFieldTypes + f::CTLRPolyElem + g::CTLRPolyElem + a1::Tuple{Int,Int} + a2::Tuple{Int,Int} end ############################# - # traits +# traits ############################# -const CSSTypes = Union{AbstractSubsystemCodeCSS, AbstractStabilizerCodeCSS, AbstractGraphStateStabilizerCSS, AbstractGraphStateSubsystemCSS, AbstractHypergraphProductCode} -const GraphStateTypes = Union{AbstractGraphStateSubsystem, AbstractGraphStateSubsystemCSS, AbstractGraphStateStabilizer, AbstractGraphStateStabilizerCSS} +const CSSTypes = Union{ + AbstractSubsystemCodeCSS, + AbstractStabilizerCodeCSS, + AbstractGraphStateStabilizerCSS, + AbstractGraphStateSubsystemCSS, + AbstractHypergraphProductCode, +} +const GraphStateTypes = Union{ + AbstractGraphStateSubsystem, + AbstractGraphStateSubsystemCSS, + AbstractGraphStateStabilizer, + AbstractGraphStateStabilizerCSS, +} abstract type LogicalTrait end struct HasLogicals <: LogicalTrait end struct HasNoLogicals <: LogicalTrait end -LogicalTrait(::Type{T}) where {T <: AbstractSubsystemCode} = HasLogicals() -LogicalTrait(::Type{T}) where {T <: GraphStateTypes} = HasNoLogicals() +LogicalTrait(::Type{T}) where {T<:AbstractSubsystemCode} = HasLogicals() +LogicalTrait(::Type{T}) where {T<:GraphStateTypes} = HasNoLogicals() abstract type GaugeTrait end struct HasGauges <: GaugeTrait end struct HasNoGauges <: GaugeTrait end -GaugeTrait(::Type{T}) where {T <: AbstractSubsystemCode} = HasGauges() -GaugeTrait(::Type{T}) where {T <: AbstractStabilizerCode} = HasNoGauges() +GaugeTrait(::Type{T}) where {T<:AbstractSubsystemCode} = HasGauges() +GaugeTrait(::Type{T}) where {T<:AbstractStabilizerCode} = HasNoGauges() abstract type CSSTrait end struct IsCSS <: CSSTrait end struct IsNotCSS <: CSSTrait end -CSSTrait(::Type{T}) where {T <: AbstractSubsystemCode} = IsNotCSS() -CSSTrait(::Type{T}) where {T <: CSSTypes} = IsCSS() +CSSTrait(::Type{T}) where {T<:AbstractSubsystemCode} = IsNotCSS() +CSSTrait(::Type{T}) where {T<:CSSTypes} = IsCSS() diff --git a/src/Quantum/weight_dist.jl b/src/Quantum/weight_dist.jl index 505b2d8d..98322eab 100644 --- a/src/Quantum/weight_dist.jl +++ b/src/Quantum/weight_dist.jl @@ -5,19 +5,24 @@ # LICENSE file in the root directory of this source tree. ############################# - # Weight Enumerators +# Weight Enumerators ############################# # TODO: test with other iterator # TODO: remove quadratic extension -function _weight_enumerator_BF_Q(G::CTMatrixTypes, char_vec::Vector{zzModRingElem}, - R::Union{AbsSimpleNumFieldElem, Missing}) +function _weight_enumerator_BF_Q( + G::CTMatrixTypes, + char_vec::Vector{zzModRingElem}, + R::Union{AbsSimpleNumFieldElem,Missing}, +) # this should be the quadratic extension field E = base_ring(G) - is_even(Int(degree(E))) || error("Matrix passed to weight enumerator does not appear to be over the quadratic extension.") + is_even(Int(degree(E))) || error( + "Matrix passed to weight enumerator does not appear to be over the quadratic extension.", + ) ord_E = Int(order(E)) lookup = Dict(value => key for (key, value) in enumerate(collect(E))) - + p = Int(characteristic(E)) is_even(p) ? nth = 2 * p : nth = p if ismissing(R) @@ -31,9 +36,9 @@ function _weight_enumerator_BF_Q(G::CTMatrixTypes, char_vec::Vector{zzModRingEle nr, nc = size(G) # Nemo.AbstractAlgebra.ProductIterator - for iter in Base.Iterators.product([0:(p - 1) for _ in 1:nr]...) + for iter in Base.Iterators.product([0:(p-1) for _ = 1:nr]...) row = E(iter[1]) * G[1, :] - for r in 2:nr + for r = 2:nr if !iszero(iter[r]) row += E(iter[r]) * G[r, :] end @@ -42,7 +47,7 @@ function _weight_enumerator_BF_Q(G::CTMatrixTypes, char_vec::Vector{zzModRingEle # to do process signs here parity = 0 - for c in 1:2 * nc + for c = 1:(2*nc) iszero(row_sym[c]) || (parity += data(char_vec[c]);) end @@ -53,7 +58,7 @@ function _weight_enumerator_BF_Q(G::CTMatrixTypes, char_vec::Vector{zzModRingEle end # println(term, ", ", typeof(term)) term_poly = ω^parity - for i in 1:ord_E + for i = 1:ord_E term_poly *= vars[i]^term[i] end poly += term_poly @@ -66,15 +71,21 @@ end # formulas from # "Weight enumerators for nonbinary asymmetric quantum codes and their applications" # by Chuangqiang Hu, Shudi Yang, Stephen S.-T.Yau -function MacWilliams_identity(S::AbstractStabilizerCode, W::WeightEnumerator; dual::Bool = false) +function MacWilliams_identity( + S::AbstractStabilizerCode, + W::WeightEnumerator; + dual::Bool = false, +) dual ? (card = BigInt(characteristic(S.F))^(S.n + S.k);) : (card = cardinality(S);) if W.type == :Hamming # (1/(q^n|S|))W(y - x, y + (q^2 - 1)x) R = parent(W.polynomial) vars = gens(R) q = Int(order(S.F)) - return WeightEnumerator(divexact(W.polynomial(vars[2] - vars[1], vars[2] + - (q^2 - 1) * vars[1]), card), :Hamming) + return WeightEnumerator( + divexact(W.polynomial(vars[2] - vars[1], vars[2] + (q^2 - 1) * vars[1]), card), + :Hamming, + ) # could probably put the /q under each variable and remove the q^n end @@ -85,14 +96,22 @@ function MacWilliams_identity(S::AbstractStabilizerCode, W::WeightEnumerator; du vars = gens(R) # this is the same as the classical Hermitian dual formula # switched lines 2 and 3 from citation for our basis - return WeightEnumerator(divexact(W.polynomial( - vars[1] + vars[2] + vars[3] + vars[4], - vars[1] + vars[2] - vars[3] - vars[4], - vars[1] - vars[2] + vars[3] - vars[4], - vars[1] - vars[2] - vars[3] + vars[4]), - card), :complete) # need the /2 to connect to the original Shor-Laflamme def + return WeightEnumerator( + divexact( + W.polynomial( + vars[1] + vars[2] + vars[3] + vars[4], + vars[1] + vars[2] - vars[3] - vars[4], + vars[1] - vars[2] + vars[3] - vars[4], + vars[1] - vars[2] - vars[3] + vars[4], + ), + card, + ), + :complete, + ) # need the /2 to connect to the original Shor-Laflamme def else - error("The quantum MacWilliams identity for higher fields has a bug and is currently unavailable.") + error( + "The quantum MacWilliams identity for higher fields has a bug and is currently unavailable.", + ) # BUG: in the below it's unclear what the proper permutation is given the paper # the various combinations I've tried always fix one but break the dual # need to set ω ↦ ω^2 and then match the equations above (try Q15RM()) @@ -127,12 +146,25 @@ function MacWilliams_identity(S::AbstractStabilizerCode, W::WeightEnumerator; du end end -function weight_enumerator(S::AbstractStabilizerCode; type::Symbol = :complete, - alg::Symbol = :auto, set::Symbol = :all) - - type ∈ (:complete, :Hamming) || throw(ArgumentError("Unsupported weight enumerator type '$type'. Expected ':complete' or ':Hamming'.")) - alg ∈ (:auto, :trellis, :bruteforce) || throw(ArgumentError("Algorithm `$alg` is not implemented in weight_enumerator.")) - set ∈ (:all, :stabilizers, :logicals, :quotient) || throw(ArgumentError("Unsupported set type '$set'. Expected ':all', ':stabilizers', ':logicals', ':quotient'.")) +function weight_enumerator( + S::AbstractStabilizerCode; + type::Symbol = :complete, + alg::Symbol = :auto, + set::Symbol = :all, +) + + type ∈ (:complete, :Hamming) || throw( + ArgumentError( + "Unsupported weight enumerator type '$type'. Expected ':complete' or ':Hamming'.", + ), + ) + alg ∈ (:auto, :trellis, :bruteforce) || + throw(ArgumentError("Algorithm `$alg` is not implemented in weight_enumerator.")) + set ∈ (:all, :stabilizers, :logicals, :quotient) || throw( + ArgumentError( + "Unsupported set type '$set'. Expected ':all', ':stabilizers', ':logicals', ':quotient'.", + ), + ) if set ∈ (:all, :logicals) && ismissing(S.sgn_CWE_logs) logs_mat = logicals_matrix(S) @@ -141,8 +173,11 @@ function weight_enumerator(S::AbstractStabilizerCode; type::Symbol = :complete, if set != :logicals && ismissing(S.sgn_CWE_stabs) if alg == :bruteforce || cardinality(S) <= 1e6 - S.sgn_CWE_stabs = _weight_enumerator_BF_Q(S.stabs, S.char_vec, - parent(S.sgn_CWE_logs.polynomial)) + S.sgn_CWE_stabs = _weight_enumerator_BF_Q( + S.stabs, + S.char_vec, + parent(S.sgn_CWE_logs.polynomial), + ) else # trellis solution here end @@ -150,19 +185,32 @@ function weight_enumerator(S::AbstractStabilizerCode; type::Symbol = :complete, if set ∈ (:all, :quotient) && ismissing(S.sgn_CWE_dual) if alg == :bruteforce || BigInt(characteristic(S.F))^(S.n + S.k) <= 3e6 - S.sgn_CWE_dual = _weight_enumerator_BF_Q(vcat(S.stabs, logicals_matrix(S)), S.char_vec, - parent(S.sgn_CWE_logs.polynomial)) + S.sgn_CWE_dual = _weight_enumerator_BF_Q( + vcat(S.stabs, logicals_matrix(S)), + S.char_vec, + parent(S.sgn_CWE_logs.polynomial), + ) else # trellis solution here end end - + if !ismissing(S.sgn_CWE_stabs) && !ismissing(S.sgn_CWE_dual) # compute minimum distance here - poly = WeightEnumerator(S.sgn_CWE_dual.polynomial - S.sgn_CWE_stabs.polynomial, :complete) + poly = WeightEnumerator( + S.sgn_CWE_dual.polynomial - S.sgn_CWE_stabs.polynomial, + :complete, + ) HWE = CWE_to_HWE(poly) - S.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(HWE.polynomial))[i][1] - for i in 1:length(HWE.polynomial)])) + S.d = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(HWE.polynomial))[i][1] for + i = 1:length(HWE.polynomial) + ], + ), + ) end if type == :complete @@ -171,7 +219,10 @@ function weight_enumerator(S::AbstractStabilizerCode; type::Symbol = :complete, set == :logicals && return S.sgn_CWE_logs return poly else - set == :all && return CWE_to_HWE(S.sgn_CWE_stabs), CWE_to_HWE(S.sgn_CWE_dual), CWE_to_HWE(S.sgn_CWE_logs), CWE_to_HWE(poly) + set == :all && return CWE_to_HWE(S.sgn_CWE_stabs), + CWE_to_HWE(S.sgn_CWE_dual), + CWE_to_HWE(S.sgn_CWE_logs), + CWE_to_HWE(poly) set == :stabilizers && return CWE_to_HWE(S.sgn_CWE_stabs) set == :logicals && return CWE_to_HWE(S.sgn_CWE_logs) return HWE @@ -180,27 +231,47 @@ end # MAGMA returns this format # [ <0, 1>, <4, 105>, <6, 280>, <8, 435>, <10, 168>, <12, 35> ] -function weight_distribution(S::AbstractStabilizerCode; alg::Symbol = :auto, compact::Bool = true, set::Symbol = :all) - - alg ∈ (:auto, :trellis, :bruteforce) || throw(ArgumentError("Algorithm `$alg` is not implemented in weight_enumerator.")) - set ∈ (:all, :stabilizers, :logicals, :quotient) || throw(ArgumentError("Unsupported set type '$set'. Expected ':all', ':stabilizers', ':logicals', ':quotient'.")) +function weight_distribution( + S::AbstractStabilizerCode; + alg::Symbol = :auto, + compact::Bool = true, + set::Symbol = :all, +) + + alg ∈ (:auto, :trellis, :bruteforce) || + throw(ArgumentError("Algorithm `$alg` is not implemented in weight_enumerator.")) + set ∈ (:all, :stabilizers, :logicals, :quotient) || throw( + ArgumentError( + "Unsupported set type '$set'. Expected ':all', ':stabilizers', ':logicals', ':quotient'.", + ), + ) wt_enums = weight_enumerator(S, type = :Hamming, alg = alg, set = set) if compact if length(wt_enums) == 1 wt_dist = Vector{Tuple}() - for i in 1:length(wt_enums.polynomial) - push!(wt_dist, (exponent_vector(wt_enums.polynomial, i)[1], - coeff(wt_enums.polynomial, i))) + for i = 1:length(wt_enums.polynomial) + push!( + wt_dist, + ( + exponent_vector(wt_enums.polynomial, i)[1], + coeff(wt_enums.polynomial, i), + ), + ) end else wt_dist = Vector{Vector{Tuple}}() for wt_enum in wt_enums wt_dist_inner = Vector{Tuple}() - for i in 1:length(wt_enum.polynomial) - push!(wt_dist_inner, (exponent_vector(wt_enum.polynomial, i)[1], - coeff(wt_enum.polynomial, i))) + for i = 1:length(wt_enum.polynomial) + push!( + wt_dist_inner, + ( + exponent_vector(wt_enum.polynomial, i)[1], + coeff(wt_enum.polynomial, i), + ), + ) end push!(wt_dist, wt_dist_inner) end @@ -209,17 +280,19 @@ function weight_distribution(S::AbstractStabilizerCode; alg::Symbol = :auto, com if length(wt_enums) == 1 K = base_ring(wt_enums.polynomial) wt_dist = zero_matrix(K, 1, S.n + 1) - for i in 1:length(wt_enums.polynomial) - wt_dist[1, exponent_vector(wt_enums.polynomial, i)[1] + 1] = coeff(wt_enums.polynomial, i) + for i = 1:length(wt_enums.polynomial) + wt_dist[1, exponent_vector(wt_enums.polynomial, i)[1]+1] = + coeff(wt_enums.polynomial, i) end else K = base_ring(wt_enums[1].polynomial) wt_dist = [] #Vector{Vector{K}}() for wt_enum in wt_enums wt_dist_inner = zero_matrix(K, 1, S.n + 1) - for i in 1:length(wt_enum.polynomial) + for i = 1:length(wt_enum.polynomial) # println(coeff(wt_enum.polynomial, i)) - wt_dist_inner[1, exponent_vector(wt_enum.polynomial, i)[1] + 1] = coeff(wt_enum.polynomial, i) + wt_dist_inner[1, exponent_vector(wt_enum.polynomial, i)[1]+1] = + coeff(wt_enum.polynomial, i) end push!(wt_dist, wt_dist_inner) end @@ -229,7 +302,11 @@ function weight_distribution(S::AbstractStabilizerCode; alg::Symbol = :auto, com end function weight_enumerator_quantum(T::Trellis; type::Symbol = :complete) - type ∈ (:complete, :Hamming) || throw(ArgumentError("Unsupported weight enumerator type '$type'. Expected ':complete' or ':Hamming'.")) + type ∈ (:complete, :Hamming) || throw( + ArgumentError( + "Unsupported weight enumerator type '$type'. Expected ':complete' or ':Hamming'.", + ), + ) if type == :complete && !ismissing(T.CWE) return T.CWE @@ -252,12 +329,12 @@ function weight_enumerator_quantum(T::Trellis; type::Symbol = :complete) E = T.edges V[1][1].polynomial = R(1) bit = 1 - for i in 2:length(V) + for i = 2:length(V) # for (j, v) in enumerate(V[i]) - Threads.@threads for j in 1:length(V[i]) + Threads.@threads for j = 1:length(V[i]) v = V[i][j] outer = R(0) - for e in E[i - 1][j] + for e in E[i-1][j] inner_bit = deepcopy(bit) parity = 0 for k in e.label @@ -265,12 +342,12 @@ function weight_enumerator_quantum(T::Trellis; type::Symbol = :complete) parity += data(char_vec[inner_bit]) end if !iszero(coeff(k, 1)) - parity += data(char_vec[inner_bit + n]) + parity += data(char_vec[inner_bit+n]) end inner_bit += 1 end - inner = deepcopy(V[i - 1][e.outvertex].polynomial) + inner = deepcopy(V[i-1][e.outvertex].polynomial) for k in e.label inner *= ω^parity * vars[lookup[k]] end @@ -278,7 +355,7 @@ function weight_enumerator_quantum(T::Trellis; type::Symbol = :complete) end v.polynomial = outer end - bit += length(E[i - 1][1][1].label) + bit += length(E[i-1][1][1].label) end T.CWE = WeightEnumerator(V[end][1].polynomial, :complete) @@ -363,7 +440,7 @@ support(S::AbstractStabilizerCode; alg::Symbol = :auto, type::Symbol = :stabiliz [i for (i, _) in weight_distribution(S, alg = alg, set = type, compact = true)] ############################# - # Minimum Distance +# Minimum Distance ############################# # TODO @@ -394,7 +471,8 @@ function minimum_distance_upper_bound!(S::AbstractSubsystemCode) S.u_bound_dx_dressed = u_bound_dx_dressed S.u_bound_dz_dressed = u_bound_dz_dressed - S.u_bound_dressed = minimum([u_bound_dx_dressed, u_bound_dz_dressed, S.u_bound_bare]) + S.u_bound_dressed = + minimum([u_bound_dx_dressed, u_bound_dz_dressed, S.u_bound_bare]) else # bare _, mat = _rref_symp_col_swap(vcat(S.stabs, S.logs_mat)) @@ -406,7 +484,7 @@ function minimum_distance_upper_bound!(S::AbstractSubsystemCode) u_bound_dressed, _ = _min_wt_row(mat) S.u_bound_dressed = u_bound_dressed end - # stabilizer code + # stabilizer code else # is a CSS code if CSSTrait(typeof(S)) == IsCSS() @@ -419,7 +497,7 @@ function minimum_distance_upper_bound!(S::AbstractSubsystemCode) S.u_bound_dx = u_bound_dx S.u_bound_dz = u_bound_dz S.u_bound = min(u_bound_dx, u_bound_dz) - # is not a CSS code + # is not a CSS code else _, mat = _rref_symp_col_swap(vcat(S.stabs, S.logs_mat)) u_bound, _ = _min_wt_row(mat) @@ -437,11 +515,16 @@ end Return the minimum distance of the stabilizer code if known, otherwise computes it. """ -function minimum_distance_Gray(S::AbstractStabilizerCode; alg::Symbol = :auto, verbose::Bool = false) +function minimum_distance_Gray( + S::AbstractStabilizerCode; + alg::Symbol = :auto, + verbose::Bool = false, +) !ismissing(S.d) && return S.d # these should be different? weight? auto? BZ? - alg ∈ (:auto, :trellis, :bruteforce) || throw(ArgumentError("Algorithm `$alg` is not implemented in weight_enumerator.")) + alg ∈ (:auto, :trellis, :bruteforce) || + throw(ArgumentError("Algorithm `$alg` is not implemented in weight_enumerator.")) if iszero(S.k) # "Quantum Error Correction Via Codes Over GF(4)" @@ -455,7 +538,8 @@ function minimum_distance_Gray(S::AbstractStabilizerCode; alg::Symbol = :auto, v TOF_norm = trellis_oriented_form_additive(S.dualgens) boundaries, num_E_sect_primal = optimal_sectionalization_Q(TOF_stabs, TOF_norm) verbose && println("Primal edges: $num_E_sect_primal") - profiles_primal = trellis_profiles(TOF_stabs, TOF_norm, boundaries, "symplectic") + profiles_primal = + trellis_profiles(TOF_stabs, TOF_norm, boundaries, "symplectic") boundaries, num_E_sect_dual = optimal_sectionalization_Q(TOF_norm, TOF_stabs) verbose && println("Dual edges: $num_E_sect_dual") profiles_dual = trellis_profiles(TOF_norm, TOF_stabs, boundaries, "symplectic") @@ -464,15 +548,23 @@ function minimum_distance_Gray(S::AbstractStabilizerCode; alg::Symbol = :auto, v T_primal_HWE = weight_enumerator_quantum(T_primal, type = :complete) T_dual_HWE = MacWilliams_identity(S, T_primal_HWE, dual = true) poly = T_dual_HWE.polynomial - T_primal_HWE.polynomial - S.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(poly))[i][1] - for i in 1:length(poly)])) + S.d = minimum( + filter( + x -> x != 0, + [collect(exponent_vectors(poly))[i][1] for i = 1:length(poly)], + ), + ) else T_dual = sect(S, "dual", true, false) T_dual_HWE = weight_enumerator_quantum(T_dual, type = :Hamming) T_primal_HWE = MacWilliams_identity(S, T_dual_HWE) poly = T_dual_HWE.polynomial - T_primal_HWE.polynomial - S.d = minimum(filter(x -> x != 0, [collect(exponent_vectors(poly))[i][1] - for i in 1:length(poly)])) + S.d = minimum( + filter( + x -> x != 0, + [collect(exponent_vectors(poly))[i][1] for i = 1:length(poly)], + ), + ) end # T_dual = syndrome_trellis(S, "primal", true, true) @@ -488,7 +580,7 @@ function minimum_distance_Gray(S::AbstractStabilizerCode; alg::Symbol = :auto, v else # brute force solution here end - #TODO: purity - + #TODO: purity - end return S.d end @@ -512,12 +604,26 @@ function XZ_minimum_distance(S::AbstractStabilizerCodeCSS) C1_dual_wt_enum = MacWilliams_identity(C1, C1_wt_enum) C2_dual_wt_enum = MacWilliams_identity(C2, C2_wt_enum) C1_set_diff_C2_wt_enum = C1_dual_wt_enum.polynomial - C2_dual_wt_enum.polynomial - C2_dual_set_diff_C1_dual_wt_enum = C2_dual_wt_enum.polynomial - C1_dual_wt_enum.polynomial - S.dz = minimum(filter(x -> x != 0, [collect(exponent_vectors(C1_set_diff_C2_wt_enum))[i][1] - for i in 1:length(C1_set_diff_C2_wt_enum)])) - S.dx = minimum(filter(x -> x != 0, [collect(exponent_vectors( - C2_dual_set_diff_C1_dual_wt_enum))[i][1] for i in eachindex( - C2_dual_set_diff_C1_dual_wt_enum)])) + C2_dual_set_diff_C1_dual_wt_enum = + C2_dual_wt_enum.polynomial - C1_dual_wt_enum.polynomial + S.dz = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(C1_set_diff_C2_wt_enum))[i][1] for + i = 1:length(C1_set_diff_C2_wt_enum) + ], + ), + ) + S.dx = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(C2_dual_set_diff_C1_dual_wt_enum))[i][1] for + i in eachindex(C2_dual_set_diff_C1_dual_wt_enum) + ], + ), + ) # the above commands will set Ci.d (S.dx == C2.d && S.d_z == C1.d) ? (S.pure = true;) : (S.pure = false;) return S.dz, S.dx @@ -534,9 +640,9 @@ end function X_minimum_distance(S::AbstractStabilizerCodeCSS) ismissing(S.dx) || return S.dx - - # need to make these if they are missing - if !ismissing(S.Z_orig_code) + + # need to make these if they are missing + if !ismissing(S.Z_orig_code) C1 = S.Z_orig_code C2 = S.X_orig_code else @@ -547,10 +653,17 @@ function X_minimum_distance(S::AbstractStabilizerCodeCSS) C2_wt_enum = weight_enumerator(C2, type = :Hamming) C1_dual_wt_enum = MacWilliams_identity(C1, C1_wt_enum) C2_dual_wt_enum = MacWilliams_identity(C2, C2_wt_enum) - C2_dual_set_diff_C1_dual_wt_enum = C2_dual_wt_enum.polynomial - C1_dual_wt_enum.polynomial - S.dx = minimum(filter(x -> x != 0, [collect(exponent_vectors( - C2_dual_set_diff_C1_dual_wt_enum))[i][1] for i in eachindex( - C2_dual_set_diff_C1_dual_wt_enum)])) + C2_dual_set_diff_C1_dual_wt_enum = + C2_dual_wt_enum.polynomial - C1_dual_wt_enum.polynomial + S.dx = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(C2_dual_set_diff_C1_dual_wt_enum))[i][1] for + i in eachindex(C2_dual_set_diff_C1_dual_wt_enum) + ], + ), + ) return S.dx end @@ -570,8 +683,15 @@ function Z_minimum_distance(S::AbstractStabilizerCodeCSS) C1_dual_wt_enum = MacWilliams_identity(C1, C1_wt_enum) C2_dual_wt_enum = MacWilliams_identity(C2, C2_wt_enum) C1_set_diff_C2_wt_enum = C1_dual_wt_enum.polynomial - C2_dual_wt_enum.polynomial - S.d_z = minimum(filter(x -> x != 0, [collect(exponent_vectors(C1_set_diff_C2_wt_enum))[i][1] - for i in eachindex(C1_set_diff_C2_wt_enum)])) + S.d_z = minimum( + filter( + x -> x != 0, + [ + collect(exponent_vectors(C1_set_diff_C2_wt_enum))[i][1] for + i in eachindex(C1_set_diff_C2_wt_enum) + ], + ), + ) return S.d_z end @@ -608,8 +728,15 @@ Wrapper for the QDistRnd function DistRandCSS. - `max_av` (Options stack): if set, terminate when `` greater than `max_av`, see Section Emprirical. Not set by default. """ -function _QDistRndCSS_GAP(H_X::Matrix{Int}, H_Z::Matrix{Int}, num::Int; min_dist::Int = 0, - debug::Int = 0, field::GapObj = GAP.Globals.GF(2), max_av = missing) +function _QDistRndCSS_GAP( + H_X::Matrix{Int}, + H_Z::Matrix{Int}, + num::Int; + min_dist::Int = 0, + debug::Int = 0, + field::GapObj = GAP.Globals.GF(2), + max_av = missing, +) # this requires a check on the install and load flags but since this is being moved to private # we will ignore it for now @@ -641,23 +768,57 @@ algorithm finishes normally. - `dressed` - set to `true` to bound the dressed distance and `false` to bound the bare distance; this parameter is ignored for stabilizer codes - `max_iters` - the number of random iterations """ -function random_information_set_minimum_distance_bound!(S::T, which::Symbol = :full; - dressed::Bool = true, max_iters::Int = 10000, verbose::Bool = false) where T <: AbstractSubsystemCode - - which ∈ (:full, :X, :Z) || throw(DomainError(which, "Must choose `:full`, `:X` or `:Z`.")) - order(field(S)) == 2 || throw(DomainError(S, "Currently only implemented for binary codes.")) - is_positive(max_iters) || throw(DomainError(max_iters, "The number of iterations must be a positive integer.")) - - return random_information_set_minimum_distance_bound!(GaugeTrait(T), CSSTrait(T), - LogicalTrait(T), S, which, dressed, max_iters, verbose) +function random_information_set_minimum_distance_bound!( + S::T, + which::Symbol = :full; + dressed::Bool = true, + max_iters::Int = 10000, + verbose::Bool = false, +) where {T<:AbstractSubsystemCode} + + which ∈ (:full, :X, :Z) || + throw(DomainError(which, "Must choose `:full`, `:X` or `:Z`.")) + order(field(S)) == 2 || + throw(DomainError(S, "Currently only implemented for binary codes.")) + is_positive(max_iters) || throw( + DomainError(max_iters, "The number of iterations must be a positive integer."), + ) + + return random_information_set_minimum_distance_bound!( + GaugeTrait(T), + CSSTrait(T), + LogicalTrait(T), + S, + which, + dressed, + max_iters, + verbose, + ) end -QDistRnd!(S::T, which::Symbol = :full; dressed::Bool = true, max_iters::Int = 10000, - verbose::Bool = false) where T <: AbstractSubsystemCode = - random_information_set_minimum_distance_bound!(S, which; dressed = dressed, max_iters = - max_iters, verbose = verbose) - -function random_information_set_minimum_distance_bound!(::HasGauges, ::IsCSS, ::HasLogicals, - S::AbstractSubsystemCode, which::Symbol, dressed::Bool, max_iters::Int, verbose::Bool) +QDistRnd!( + S::T, + which::Symbol = :full; + dressed::Bool = true, + max_iters::Int = 10000, + verbose::Bool = false, +) where {T<:AbstractSubsystemCode} = random_information_set_minimum_distance_bound!( + S, + which; + dressed = dressed, + max_iters = max_iters, + verbose = verbose, +) + +function random_information_set_minimum_distance_bound!( + ::HasGauges, + ::IsCSS, + ::HasLogicals, + S::AbstractSubsystemCode, + which::Symbol, + dressed::Bool, + max_iters::Int, + verbose::Bool, +) # CSS subsystem code n = S.n @@ -669,7 +830,7 @@ function random_information_set_minimum_distance_bound!(::HasGauges, ::IsCSS, :: println("Bare distance already known") return S.d_bare end - + stabs = _Flint_matrix_to_Julia_T_matrix(stabilizers(S), UInt8) if dressed verbose && println("Bounding the full dressed distance") @@ -686,13 +847,15 @@ function random_information_set_minimum_distance_bound!(::HasGauges, ::IsCSS, :: stabs = _remove_empty(stabs, :rows) logs = _Flint_matrix_to_Julia_T_matrix(logicals_matrix(S), UInt8) operators_to_reduce = vcat(stabs, logs) - check_against = permutedims(logs[:, [n + 1:2n; 1:n]]) + check_against = permutedims(logs[:, [(n+1):2n; 1:n]]) # this is done in the constructor but the logical is not stored at the time # so must redo here mat = _rref_no_col_swap_binary(operators_to_reduce) anti = mat * check_against - curr_u_bound, index = findmin(row_wts_symplectic(mat[findall(!iszero(anti[i, :]) for i in axes(anti, 1)), :])) + curr_u_bound, index = findmin( + row_wts_symplectic(mat[findall(!iszero(anti[i, :]) for i in axes(anti, 1)), :]), + ) found = operators_to_reduce[index, :] verbose && println("Starting upper bound: $curr_u_bound") else @@ -714,17 +877,29 @@ function random_information_set_minimum_distance_bound!(::HasGauges, ::IsCSS, :: end end - stabs = _Flint_matrix_to_Julia_T_matrix(stabilizers(S)[:, (which == :X ? (1:n) : (n + 1:2n))], UInt8) + stabs = _Flint_matrix_to_Julia_T_matrix( + stabilizers(S)[:, (which == :X ? (1:n) : ((n+1):2n))], + UInt8, + ) if dressed - gauges = _Flint_matrix_to_Julia_T_matrix(gauge_operators_matrix(S)[:, (which == :X ? (1:n) : (n + 1:2n))], UInt8) + gauges = _Flint_matrix_to_Julia_T_matrix( + gauge_operators_matrix(S)[:, (which == :X ? (1:n) : ((n+1):2n))], + UInt8, + ) stabs = vcat(stabs, gauges) end _rref_no_col_swap_binary!(stabs) stabs = _remove_empty(stabs, :rows) - logs = _Flint_matrix_to_Julia_T_matrix(logicals_matrix(S)[:, (which == :X ? (1:n) : (n + 1:2n))], UInt8) + logs = _Flint_matrix_to_Julia_T_matrix( + logicals_matrix(S)[:, (which == :X ? (1:n) : ((n+1):2n))], + UInt8, + ) logs = _remove_empty(logs, :rows) operators_to_reduce = vcat(stabs, logs) - check_against = _Flint_matrix_to_Julia_T_matrix(logicals_matrix(S)[:, (which == :X ? (n + 1:2n) : (1:n))], UInt8) + check_against = _Flint_matrix_to_Julia_T_matrix( + logicals_matrix(S)[:, (which == :X ? ((n+1):2n) : (1:n))], + UInt8, + ) check_against = permutedims(_remove_empty(check_against, :rows)) curr_l_bound = if dressed which == :X ? S.l_bound_dx_dressed : S.l_bound_dz_dressed @@ -732,13 +907,21 @@ function random_information_set_minimum_distance_bound!(::HasGauges, ::IsCSS, :: which == :X ? S.l_bound_dx_bare : S.l_bound_dz_bare end verbose && println("Starting lower bound: $curr_l_bound") - curr_u_bound, index = findmin(count(!iszero, logs[i, :]) for i in 1:size(logs, 1)) + curr_u_bound, index = findmin(count(!iszero, logs[i, :]) for i = 1:size(logs, 1)) found = logs[index, :] verbose && println("Starting upper bound: $curr_u_bound") end - uppers, founds = _RIS_bound_loop!(operators_to_reduce, check_against, curr_l_bound, - curr_u_bound, found, max_iters, n, verbose) + uppers, founds = _RIS_bound_loop!( + operators_to_reduce, + check_against, + curr_l_bound, + curr_u_bound, + found, + max_iters, + n, + verbose, + ) loc = argmin(uppers) verbose && println("Ending $max_iters iterations with an upper bound of $(uppers[loc])") if dressed @@ -764,12 +947,20 @@ function random_information_set_minimum_distance_bound!(::HasGauges, ::IsCSS, :: flint_mat_found = matrix(field(S), [zeros(Int, 1, n) permutedims(founds[loc])]) end end - + return uppers[loc], flint_mat_found end -function random_information_set_minimum_distance_bound!(::HasNoGauges, ::IsCSS, ::HasLogicals, - S::AbstractSubsystemCode, which::Symbol, dressed::Bool, max_iters::Int, verbose::Bool) +function random_information_set_minimum_distance_bound!( + ::HasNoGauges, + ::IsCSS, + ::HasLogicals, + S::AbstractSubsystemCode, + which::Symbol, + dressed::Bool, + max_iters::Int, + verbose::Bool, +) # CSS stabilizer code n = S.n @@ -784,7 +975,7 @@ function random_information_set_minimum_distance_bound!(::HasNoGauges, ::IsCSS, check_against = permutedims(logs) curr_l_bound = S.l_bound verbose && println("Starting lower bound: $curr_l_bound") - curr_u_bound, index = findmin(count(!iszero, logs[i, :]) for i in 1:size(logs, 1)) + curr_u_bound, index = findmin(count(!iszero, logs[i, :]) for i = 1:size(logs, 1)) found = logs[index, :] verbose && println("Starting upper bound: $curr_u_bound") else @@ -793,27 +984,52 @@ function random_information_set_minimum_distance_bound!(::HasNoGauges, ::IsCSS, elseif verbose && which == :Z verbose && println("Bounding the Z-distance") end - stabs = _Flint_matrix_to_Julia_T_matrix(stabilizers(S)[:, (which == :X ? (1:n) : (n + 1:2n))], UInt8) + stabs = _Flint_matrix_to_Julia_T_matrix( + stabilizers(S)[:, (which == :X ? (1:n) : ((n+1):2n))], + UInt8, + ) _rref_no_col_swap_binary!(stabs) stabs = _remove_empty(stabs, :rows) - logs = _Flint_matrix_to_Julia_T_matrix(logicals_matrix(S)[:, (which == :X ? (1:n) : (n + 1:2n))], UInt8) + logs = _Flint_matrix_to_Julia_T_matrix( + logicals_matrix(S)[:, (which == :X ? (1:n) : ((n+1):2n))], + UInt8, + ) logs = _remove_empty(logs, :rows) operators_to_reduce = vcat(stabs, logs) - check_against = _Flint_matrix_to_Julia_T_matrix(logicals_matrix(S)[:, (which == :X ? (n + 1:2n) : (1:n))], UInt8) + check_against = _Flint_matrix_to_Julia_T_matrix( + logicals_matrix(S)[:, (which == :X ? ((n+1):2n) : (1:n))], + UInt8, + ) check_against = permutedims(_remove_empty(check_against, :rows)) which == :X ? (curr_l_bound = S.l_bound_dx;) : (curr_l_bound = S.l_bound_dz;) verbose && println("Starting lower bound: $curr_l_bound") - curr_u_bound, index = findmin(count(!iszero, logs[i, :]) for i in 1:size(logs, 1)) + curr_u_bound, index = findmin(count(!iszero, logs[i, :]) for i = 1:size(logs, 1)) found = logs[index, :] verbose && println("Starting upper bound: $curr_u_bound") end uppers, founds = if which == :full - _RIS_bound_loop_symp!(operators_to_reduce, check_against, curr_l_bound, - curr_u_bound, found, max_iters, n, verbose) + _RIS_bound_loop_symp!( + operators_to_reduce, + check_against, + curr_l_bound, + curr_u_bound, + found, + max_iters, + n, + verbose, + ) else - _RIS_bound_loop!(operators_to_reduce, check_against, curr_l_bound, - curr_u_bound, found, max_iters, n, verbose) + _RIS_bound_loop!( + operators_to_reduce, + check_against, + curr_l_bound, + curr_u_bound, + found, + max_iters, + n, + verbose, + ) end loc = argmin(uppers) verbose && println("Ending $max_iters iterations with an upper bound of $(uppers[loc])") @@ -833,11 +1049,20 @@ function random_information_set_minimum_distance_bound!(::HasNoGauges, ::IsCSS, return uppers[loc], flint_mat_found end -function random_information_set_minimum_distance_bound!(::HasGauges, ::IsNotCSS, ::HasLogicals, - S::AbstractSubsystemCode, which::Symbol, dressed::Bool, max_iters::Int, verbose::Bool) +function random_information_set_minimum_distance_bound!( + ::HasGauges, + ::IsNotCSS, + ::HasLogicals, + S::AbstractSubsystemCode, + which::Symbol, + dressed::Bool, + max_iters::Int, + verbose::Bool, +) # non-CSS subsystem code - which == :full || throw(ArguementError(which, "Parameter is not valid for non-CSS codes.")) + which == :full || + throw(ArguementError(which, "Parameter is not valid for non-CSS codes.")) n = S.n if dressed && !ismissing(S.d_dressed) @@ -863,18 +1088,28 @@ function random_information_set_minimum_distance_bound!(::HasGauges, ::IsNotCSS, verbose && println("Starting lower bound: $curr_l_bound") logs = _Flint_matrix_to_Julia_T_matrix(logicals_matrix(S), UInt8) operators_to_reduce = vcat(stabs, logs) - check_against = permutedims(logs[:, [n + 1:2n; 1:n]]) + check_against = permutedims(logs[:, [(n+1):2n; 1:n]]) # this is done in the constructor but the logical is not stored at the time # so must redo here mat = _rref_no_col_swap_binary(operators_to_reduce) anti = mat * check_against - curr_u_bound, index = findmin(row_wts_symplectic(mat[findall(!iszero(anti[i, :]) for i in axes(anti, 1)), :])) + curr_u_bound, index = findmin( + row_wts_symplectic(mat[findall(!iszero(anti[i, :]) for i in axes(anti, 1)), :]), + ) found = operators_to_reduce[index, :] verbose && println("Starting upper bound: $curr_u_bound") - uppers, founds = _RIS_bound_loop_symp!(operators_to_reduce, check_against, curr_l_bound, - curr_u_bound, found, max_iters, n, verbose) + uppers, founds = _RIS_bound_loop_symp!( + operators_to_reduce, + check_against, + curr_l_bound, + curr_u_bound, + found, + max_iters, + n, + verbose, + ) loc = argmin(uppers) if dressed S.u_bound_dressed = uppers[loc] @@ -885,11 +1120,20 @@ function random_information_set_minimum_distance_bound!(::HasGauges, ::IsNotCSS, return uppers[loc], matrix(field(S), permutedims(founds[loc])) end -function random_information_set_minimum_distance_bound!(::HasNoGauges, ::IsNotCSS, ::HasLogicals, - S::AbstractSubsystemCode, which::Symbol, dressed::Bool, max_iters::Int, verbose::Bool) +function random_information_set_minimum_distance_bound!( + ::HasNoGauges, + ::IsNotCSS, + ::HasLogicals, + S::AbstractSubsystemCode, + which::Symbol, + dressed::Bool, + max_iters::Int, + verbose::Bool, +) # non-CSS stabilizer code - which == :full || throw(ArguementError(which, "Parameter is not valid for non-CSS codes.")) + which == :full || + throw(ArguementError(which, "Parameter is not valid for non-CSS codes.")) n = S.n !ismissing(S.d) && (println("Distance already known"); return S.d;) @@ -903,7 +1147,7 @@ function random_information_set_minimum_distance_bound!(::HasNoGauges, ::IsNotCS # println(" ") # display(operators_to_reduce) # println(" ") - check_against = permutedims(logs[:, [n + 1:2n; 1:n]]) + check_against = permutedims(logs[:, [(n+1):2n; 1:n]]) curr_l_bound = S.l_bound verbose && println("Starting lower bound: $curr_l_bound") @@ -911,29 +1155,50 @@ function random_information_set_minimum_distance_bound!(::HasNoGauges, ::IsNotCS # so must redo here mat = _rref_no_col_swap_binary(operators_to_reduce) anti = mat * check_against - curr_u_bound, index = findmin(row_wts_symplectic(mat[findall(!iszero(anti[i, :]) for i in axes(anti, 1)), :])) + curr_u_bound, index = findmin( + row_wts_symplectic(mat[findall(!iszero(anti[i, :]) for i in axes(anti, 1)), :]), + ) found = operators_to_reduce[index, :] verbose && println("Starting upper bound: $curr_u_bound") - uppers, founds = _RIS_bound_loop_symp!(operators_to_reduce, check_against, curr_l_bound, - curr_u_bound, found, max_iters, n, verbose) + uppers, founds = _RIS_bound_loop_symp!( + operators_to_reduce, + check_against, + curr_l_bound, + curr_u_bound, + found, + max_iters, + n, + verbose, + ) loc = argmin(uppers) S.u_bound = uppers[loc] verbose && println("Ending $max_iters iterations with an upper bound of $(uppers[loc])") return uppers[loc], matrix(field(S), permutedims(founds[loc])) end -function random_information_set_minimum_distance_bound(::HasGauges, ::IsNotCSS, ::HasNoLogicals, S::AbstractSubsystemCode, which::Symbol, dressed::Bool, max_iters::Int, verbose::Bool) +function random_information_set_minimum_distance_bound( + ::HasGauges, + ::IsNotCSS, + ::HasNoLogicals, + S::AbstractSubsystemCode, + which::Symbol, + dressed::Bool, + max_iters::Int, + verbose::Bool, +) # non-CSS subsystem graph state - which == :full || throw(ArguementError(which, "Parameter is not valid for non-CSS codes.")) + which == :full || + throw(ArguementError(which, "Parameter is not valid for non-CSS codes.")) n = S.n stabs = _Flint_matrix_to_Julia_T_matrix(stabilizers(S), UInt8) _rref_no_col_swap_binary!(stabs) stabs = _remove_empty(stabs, :rows) if dressed - !ismissing(S.d_dressed) && (println("Dressed distance already known"); return S.d_dressed;) + !ismissing(S.d_dressed) && + (println("Dressed distance already known"); return S.d_dressed;) verbose && println("Bounding the full dressed distance") gauges = _Flint_matrix_to_Julia_T_matrix(gauge_operators_matrix(S), UInt8) stabs = vcat(stabs, gauges) @@ -953,8 +1218,15 @@ function random_information_set_minimum_distance_bound(::HasGauges, ::IsNotCSS, found = stabs[index, :] verbose && println("Starting upper bound: $curr_u_bound") - uppers, founds = _RIS_bound_loop_symp!(stabs, curr_l_bound, curr_u_bound, found, max_iters, n, - verbose) + uppers, founds = _RIS_bound_loop_symp!( + stabs, + curr_l_bound, + curr_u_bound, + found, + max_iters, + n, + verbose, + ) loc = argmin(uppers) if dressed S.u_bound_dressed = uppers[loc] @@ -965,12 +1237,22 @@ function random_information_set_minimum_distance_bound(::HasGauges, ::IsNotCSS, return uppers[loc], matrix(field(S), permutedims(founds[loc])) end -function random_information_set_minimum_distance_bound(::HasGauges, ::IsCSS, ::HasNoLogicals, S::AbstractSubsystemCode, which::Symbol, dressed::Bool, max_iters::Int, verbose::Bool) +function random_information_set_minimum_distance_bound( + ::HasGauges, + ::IsCSS, + ::HasNoLogicals, + S::AbstractSubsystemCode, + which::Symbol, + dressed::Bool, + max_iters::Int, + verbose::Bool, +) # CSS subsystem graph state n = S.n if which == :full - !ismissing(S.d_dressed) && (println("Dressed distance already known"); return S.d_dressed;) + !ismissing(S.d_dressed) && + (println("Dressed distance already known"); return S.d_dressed;) verbose && println("Bounding the full dressed distance") stabs = _Flint_matrix_to_Julia_T_matrix(stabilizers(S), UInt8) if dressed @@ -992,9 +1274,15 @@ function random_information_set_minimum_distance_bound(::HasGauges, ::IsCSS, ::H found = stabs[index, :] verbose && println("Starting upper bound: $curr_u_bound") else - stabs = _Flint_matrix_to_Julia_T_matrix(stabilizers(S)[:, (which == :X ? (1:n) : (n + 1:2n))], UInt8) + stabs = _Flint_matrix_to_Julia_T_matrix( + stabilizers(S)[:, (which == :X ? (1:n) : ((n+1):2n))], + UInt8, + ) if dressed - gauges = _Flint_matrix_to_Julia_T_matrix(gauge_operators_matrix(S)[:, (which == :X ? (1:n) : (n + 1:2n))], UInt8) + gauges = _Flint_matrix_to_Julia_T_matrix( + gauge_operators_matrix(S)[:, (which == :X ? (1:n) : ((n+1):2n))], + UInt8, + ) stabs = vcat(stabs, gauges) end _rref_no_col_swap_binary!(stabs) @@ -1010,8 +1298,8 @@ function random_information_set_minimum_distance_bound(::HasGauges, ::IsCSS, ::H verbose && println("Starting upper bound: $curr_u_bound") end - uppers, founds = _RIS_bound_loop!(stabs, curr_l_bound, curr_u_bound, found, max_iters, n, - verbose) + uppers, founds = + _RIS_bound_loop!(stabs, curr_l_bound, curr_u_bound, found, max_iters, n, verbose) loc = argmin(uppers) verbose && println("Ending $max_iters iterations with an upper bound of $(uppers[loc])") if dressed @@ -1037,14 +1325,24 @@ function random_information_set_minimum_distance_bound(::HasGauges, ::IsCSS, ::H flint_mat_found = matrix(field(S), [zeros(Int, 1, n) permutedims(founds[loc])]) end end - + return uppers[loc], flint_mat_found end -function random_information_set_minimum_distance_bound(::HasNoGauges, ::IsNotCSS, ::HasNoLogicals, S::AbstractSubsystemCode, which::Symbol, dressed::Bool, max_iters::Int, verbose::Bool) +function random_information_set_minimum_distance_bound( + ::HasNoGauges, + ::IsNotCSS, + ::HasNoLogicals, + S::AbstractSubsystemCode, + which::Symbol, + dressed::Bool, + max_iters::Int, + verbose::Bool, +) # non-CSS stabilizer graph state - which == :full || throw(ArguementError(which, "Parameter is not valid for non-CSS codes.")) + which == :full || + throw(ArguementError(which, "Parameter is not valid for non-CSS codes.")) n = S.n !ismissing(S.d) && (println("Distance already known"); return S.d;) @@ -1062,15 +1360,31 @@ function random_information_set_minimum_distance_bound(::HasNoGauges, ::IsNotCSS verbose && println("Starting upper bound: $curr_u_bound") # TODO write - uppers, founds = _RIS_bound_loop_symp!(stabs, curr_l_bound, curr_u_bound, found, max_iters, n, - verbose) + uppers, founds = _RIS_bound_loop_symp!( + stabs, + curr_l_bound, + curr_u_bound, + found, + max_iters, + n, + verbose, + ) loc = argmin(uppers) S.u_bound = uppers[loc] verbose && println("Ending $max_iters iterations with an upper bound of $(uppers[loc])") return uppers[loc], matrix(field(S), permutedims(founds[loc])) end -function random_information_set_minimum_distance_bound(::HasNoGauges, ::IsCSS, ::HasNoLogicals, S::AbstractSubsystemCode, which::Symbol, dressed::Bool, max_iters::Int, verbose::Bool) +function random_information_set_minimum_distance_bound( + ::HasNoGauges, + ::IsCSS, + ::HasNoLogicals, + S::AbstractSubsystemCode, + which::Symbol, + dressed::Bool, + max_iters::Int, + verbose::Bool, +) # CSS stabilizer graph state n = S.n @@ -1094,7 +1408,10 @@ function random_information_set_minimum_distance_bound(::HasNoGauges, ::IsCSS, : elseif verbose && which == :Z verbose && println("Bounding the Z-distance") end - stabs = _Flint_matrix_to_Julia_T_matrix(stabilizers(S)[:, (which == :X ? (1:n) : (n + 1:2n))], UInt8) + stabs = _Flint_matrix_to_Julia_T_matrix( + stabilizers(S)[:, (which == :X ? (1:n) : ((n+1):2n))], + UInt8, + ) _rref_no_col_swap_binary!(stabs) stabs = _remove_empty(stabs, :rows) which == :X ? (curr_l_bound = S.l_bound_dx;) : (curr_l_bound = S.l_bound_dz;) @@ -1127,27 +1444,34 @@ function random_information_set_minimum_distance_bound(::HasNoGauges, ::IsCSS, : return uppers[loc], flint_mat_found end -function _RIS_bound_loop_symp!(operators_to_reduce::Matrix{T}, check_against::Matrix{T}, - curr_l_bound::Int, curr_u_bound::Int, found::Vector{T}, max_iters::Int, n::Int, - verbose::Bool) where T <: Integer +function _RIS_bound_loop_symp!( + operators_to_reduce::Matrix{T}, + check_against::Matrix{T}, + curr_l_bound::Int, + curr_u_bound::Int, + found::Vector{T}, + max_iters::Int, + n::Int, + verbose::Bool, +) where {T<:Integer} num_thrds = Threads.nthreads() verbose && println("Detected $num_thrds threads.") flag = Threads.Atomic{Bool}(true) - uppers = [curr_u_bound for _ in 1:num_thrds] - founds = [found for _ in 1:num_thrds] + uppers = [curr_u_bound for _ = 1:num_thrds] + founds = [found for _ = 1:num_thrds] thread_load = Int(floor(max_iters / num_thrds)) remaining = max_iters - thread_load * num_thrds verbose && (prog_meter = Progress(max_iters);) # Threads.@threads for t in 1:num_thrds - for t in 1:num_thrds + for t = 1:num_thrds orig_ops = deepcopy(operators_to_reduce) log_test = zeros(Int, size(orig_ops, 1), size(check_against, 2)) perm_ops = similar(orig_ops) ops = similar(orig_ops) perm = collect(1:n) - for _ in 1:(thread_load + (t <= remaining ? 1 : 0)) + for _ = 1:(thread_load+(t<=remaining ? 1 : 0)) if flag[] shuffle!(perm) # println("original") @@ -1164,8 +1488,8 @@ function _RIS_bound_loop_symp!(operators_to_reduce::Matrix{T}, check_against::Ma # then ops[i, :] is a logical if any(isodd, log_test[i, :]) w = 0 - @inbounds for j in 1:n - (isodd(ops[i, j]) || isodd(ops[i, j + n])) && (w += 1;) + @inbounds for j = 1:n + (isodd(ops[i, j]) || isodd(ops[i, j+n])) && (w += 1;) end if uppers[t] > w @@ -1173,7 +1497,9 @@ function _RIS_bound_loop_symp!(operators_to_reduce::Matrix{T}, check_against::Ma founds[t] .= ops[i, :] verbose && println("Adjusting (thread's local) upper bound: $w") if curr_l_bound == w - verbose && println("Found a logical that matched the lower bound of $curr_l_bound") + verbose && println( + "Found a logical that matched the lower bound of $curr_l_bound", + ) Threads.atomic_cas!(flag, true, false) break end @@ -1189,26 +1515,33 @@ function _RIS_bound_loop_symp!(operators_to_reduce::Matrix{T}, check_against::Ma return uppers, founds end -function _RIS_bound_loop!(operators_to_reduce::Matrix{T}, check_against::Matrix{T}, - curr_l_bound::Int, curr_u_bound::Int, found::Vector{T}, max_iters::Int, n::Int, - verbose::Bool) where T <: Integer +function _RIS_bound_loop!( + operators_to_reduce::Matrix{T}, + check_against::Matrix{T}, + curr_l_bound::Int, + curr_u_bound::Int, + found::Vector{T}, + max_iters::Int, + n::Int, + verbose::Bool, +) where {T<:Integer} num_thrds = Threads.nthreads() verbose && println("Detected $num_thrds threads.") flag = Threads.Atomic{Bool}(true) - uppers = [curr_u_bound for _ in 1:num_thrds] - founds = [found for _ in 1:num_thrds] + uppers = [curr_u_bound for _ = 1:num_thrds] + founds = [found for _ = 1:num_thrds] thread_load = Int(floor(max_iters / num_thrds)) remaining = max_iters - thread_load * num_thrds verbose && (prog_meter = Progress(max_iters);) - Threads.@threads for t in 1:num_thrds + Threads.@threads for t = 1:num_thrds orig_ops = deepcopy(operators_to_reduce) log_test = zeros(Int, size(orig_ops, 1), size(check_against, 2)) perm_ops = similar(orig_ops) ops = similar(orig_ops) perm = collect(1:n) - for _ in 1:(thread_load + (t <= remaining ? 1 : 0)) + for _ = 1:(thread_load+(t<=remaining ? 1 : 0)) if flag[] shuffle!(perm) _col_permutation!(perm_ops, orig_ops, perm) @@ -1220,7 +1553,7 @@ function _RIS_bound_loop!(operators_to_reduce::Matrix{T}, check_against::Matrix{ # then ops[i, :] is a logical if any(isodd, log_test[i, :]) w = 0 - @inbounds for j in 1:n + @inbounds for j = 1:n isodd(ops[i, j]) && (w += 1;) end @@ -1229,7 +1562,9 @@ function _RIS_bound_loop!(operators_to_reduce::Matrix{T}, check_against::Matrix{ founds[t] .= ops[i, :] verbose && println("Adjusting (thread's local) upper bound: $w") if curr_l_bound == w - verbose && println("Found a logical that matched the lower bound of $curr_l_bound") + verbose && println( + "Found a logical that matched the lower bound of $curr_l_bound", + ) Threads.atomic_cas!(flag, true, false) break end diff --git a/src/Quantum/weight_reduction.jl b/src/Quantum/weight_reduction.jl index bed3085f..78bdbb45 100644 --- a/src/Quantum/weight_reduction.jl +++ b/src/Quantum/weight_reduction.jl @@ -5,42 +5,42 @@ # LICENSE file in the root directory of this source tree. ############################# - # Copying +# Copying ############################# function _copying_Hastings(H_X::CTMatrixTypes, H_Z::CTMatrixTypes) nr, n = size(H_X) # get column weight - q_X = maximum(count(!iszero, H_X[:, j]) for j in 1:n) + q_X = maximum(count(!iszero, H_X[:, j]) for j = 1:n) # X stabilizers X = zero_matrix(base_ring(H_X), nr + (q_X - 1) * n, q_X * n) # copied X stabilizers - for j in 1:n + for j = 1:n for (k, i) in enumerate(getindex.(findall(isone, H_X[:, j]), 1)) - X[i, q_X * (j - 1) + k] = H_X[i, j] + X[i, q_X*(j-1)+k] = H_X[i, j] end end # new X stabilizers - for j in 1:n - for i in 1:q_X - 1 + for j = 1:n + for i = 1:(q_X-1) row = nr + i + (q_X - 1) * (j - 1) col = q_X * (j - 1) + i X[row, col] = 1 - X[row, col + 1] = 1 + X[row, col+1] = 1 end end # Z stabilizers nr = nrows(H_Z) Z = zero_matrix(base_ring(H_Z), nr, q_X * n) - for i in 1:nr - for j in 1:n - for k in 1:q_X - Z[i, (j - 1) * q_X + k] = H_Z[i, j] + for i = 1:nr + for j = 1:n + for k = 1:q_X + Z[i, (j-1)*q_X+k] = H_Z[i, j] end end end @@ -51,7 +51,7 @@ function _copying_reduced(H_X::CTMatrixTypes, H_Z::CTMatrixTypes) n_X, n = size(H_X) # get column weights - qubit_expansion = [count(!iszero, H_X[:, j]) for j in 1:n] + qubit_expansion = [count(!iszero, H_X[:, j]) for j = 1:n] q_X = maximum(qubit_expansion) # X stabilizers @@ -64,22 +64,22 @@ function _copying_reduced(H_X::CTMatrixTypes, H_Z::CTMatrixTypes) end # copy in the old X stabilizers - for i in 1:n_X - for j in 1:n + for i = 1:n_X + for j = 1:n iszero(H_X[i, j]) && continue k = findfirst(!iszero, qubits_available[:, j]) qubits_available[k, j] -= 1 - X[i, sum(qubit_expansion[1:j - 1]) + k] = H_X[i, j] + X[i, sum(qubit_expansion[1:(j-1)])+k] = H_X[i, j] end end # new X stabilizers row = n_X + 1 for (i, n) in enumerate(qubit_expansion) - for j in 1:n - 1 - a = sum(qubit_expansion[1:i - 1]) + j + for j = 1:(n-1) + a = sum(qubit_expansion[1:(i-1)]) + j X[row, a] = 1 - X[row, a + 1] = 1 + X[row, a+1] = 1 row += 1 end end @@ -87,9 +87,9 @@ function _copying_reduced(H_X::CTMatrixTypes, H_Z::CTMatrixTypes) # Z stabilizers n_Z = nrows(H_Z) Z = zero_matrix(base_ring(H_Z), n_Z, sum(qubit_expansion)) - for i in 1:n_Z - for j in 1:n - for k in sum(qubit_expansion[1:j - 1]) + 1:sum(qubit_expansion[1:j]) + for i = 1:n_Z + for j = 1:n + for k = (sum(qubit_expansion[1:(j-1)])+1):sum(qubit_expansion[1:j]) Z[i, k] = H_Z[i, j] end end @@ -99,14 +99,18 @@ function _copying_reduced(H_X::CTMatrixTypes, H_Z::CTMatrixTypes) end function _copying_target(H_X::CTMatrixTypes, H_Z::CTMatrixTypes, target_q_X::Int = 3) - target_q_X >= 3 || throw(DomainError(target_q_X, "Target column weight must be at least 3.")) + target_q_X >= 3 || + throw(DomainError(target_q_X, "Target column weight must be at least 3.")) n_X, n = size(H_X) # get column weights - q_Xs = [count(!iszero, H_X[:, j]) for j in 1:n] + q_Xs = [count(!iszero, H_X[:, j]) for j = 1:n] # repetition expansion of qubits - qubit_expansion = [q_X <= target_q_X ? 1 : 2 + cld(q_X - 2 * (target_q_X - 1), target_q_X - 2) for q_X in q_Xs] + qubit_expansion = [ + q_X <= target_q_X ? 1 : 2 + cld(q_X - 2 * (target_q_X - 1), target_q_X - 2) for + q_X in q_Xs + ] # X stabilizers X = zero_matrix(base_ring(H_X), n_X + sum(qubit_expansion .- 1), sum(qubit_expansion)) @@ -120,27 +124,27 @@ function _copying_target(H_X::CTMatrixTypes, H_Z::CTMatrixTypes, target_q_X::Int end qubits_available[unique([1, n2]), j] .= target_q_X - 1 if n2 > 2 - qubits_available[2:n2 - 1, j] .= target_q_X - 2 + qubits_available[2:(n2-1), j] .= target_q_X - 2 end end # copy in the old X stabilizers - for i in 1:n_X - for j in 1:n + for i = 1:n_X + for j = 1:n iszero(H_X[i, j]) && continue k = findfirst(!iszero, qubits_available[:, j]) qubits_available[k, j] -= 1 - X[i, sum(qubit_expansion[1:j - 1]) + k] = H_X[i, j] + X[i, sum(qubit_expansion[1:(j-1)])+k] = H_X[i, j] end end # new X stabilizers row = n_X + 1 for (i, n) in enumerate(qubit_expansion) - for j in 1:n - 1 - a = sum(qubit_expansion[1:i - 1]) + j + for j = 1:(n-1) + a = sum(qubit_expansion[1:(i-1)]) + j X[row, a] = 1 - X[row, a + 1] = 1 + X[row, a+1] = 1 row += 1 end end @@ -148,9 +152,9 @@ function _copying_target(H_X::CTMatrixTypes, H_Z::CTMatrixTypes, target_q_X::Int # Z stabilizers n_Z = nrows(H_Z) Z = zero_matrix(base_ring(H_Z), n_Z, sum(qubit_expansion)) - for i in 1:n_Z - for j in 1:n - for k in sum(qubit_expansion[1:j - 1]) + 1:sum(qubit_expansion[1:j]) + for i = 1:n_Z + for j = 1:n + for k = (sum(qubit_expansion[1:(j-1)])+1):sum(qubit_expansion[1:j]) Z[i, k] = H_Z[i, j] end end @@ -164,15 +168,19 @@ end Return the result of copying on `H_X` and `H_Z` using either the Hastings, reduced, or targeted methods. """ -function copying(H_X::CTMatrixTypes, H_Z::CTMatrixTypes; method::Symbol = :Hastings, - target_q_X::Int = 3) +function copying( + H_X::CTMatrixTypes, + H_Z::CTMatrixTypes; + method::Symbol = :Hastings, + target_q_X::Int = 3, +) method ∈ (:Hastings, :reduced, :target) || throw(ArgumentError("Unknown method type")) target_q_X >= 3 || throw(DomainError(target_q_X, "Target must be at least 3")) # should we check these commute or trust the user? if method == :Hastings - return _copying_Hastings(H_X, H_Z) + return _copying_Hastings(H_X, H_Z) elseif method == :reduced return _copying_reduced(H_X, H_Z) else @@ -185,8 +193,11 @@ end Return the result of copying on `S` using either the Hastings, reduced, or targeted methods. """ -copying(S::T; method::Symbol = :Hastings, target_q_X::Int = 3) where {T <: AbstractStabilizerCode} = - copying(CSSTrait(T), S, method, target_q_X) +copying( + S::T; + method::Symbol = :Hastings, + target_q_X::Int = 3, +) where {T<:AbstractStabilizerCode} = copying(CSSTrait(T), S, method, target_q_X) function copying(::IsCSS, S::AbstractStabilizerCode, method::Symbol, target_q_X::Int) method ∈ (:Hastings, :reduced, :target) || throw(ArgumentError("Unknown method type")) target_q_X >= 3 || throw(DomainError(target_q_X, "Target must be at least 3")) @@ -197,35 +208,52 @@ end copying(::IsNotCSS, S::AbstractStabilizerCode, method::Symbol, target_q_X::Int) = error("Only valid for CSS codes.") -function _copying_as_coning_Hastings(H_X::CTMatrixTypes, H_Z::CTMatrixTypes; permute = false, rng::AbstractRNG = Random.seed!()) - q_X = maximum(count(!iszero, H_X[:, j]) for j in 1:ncols(H_X)) +function _copying_as_coning_Hastings( + H_X::CTMatrixTypes, + H_Z::CTMatrixTypes; + permute = false, + rng::AbstractRNG = Random.seed!(), +) + q_X = maximum(count(!iszero, H_X[:, j]) for j = 1:ncols(H_X)) q_X == 1 && return H_X, H_Z n_X = nrows(H_X) F = base_ring(H_X) - for i in 1:ncols(H_X) + for i = 1:ncols(H_X) H = matrix(F, diagm(q_X - 1, q_X, 0 => ones(Int, q_X - 1), 1 => ones(Int, q_X - 1))) f_1 = zero_matrix(F, q_X, nrows(H_X)) for j in (permute ? shuffle(rng, 1:n_X) : 1:n_X) if H_X[j, 1] == 1 - f_1[count(!iszero, f_1) + 1, j] = 1 + f_1[count(!iszero, f_1)+1, j] = 1 end end H_X = H_X[:, 2:end] H_Z = H_Z[:, 2:end] - flag, f_2 = can_solve_with_solution(hcat(f_1, transpose(H)), hcat(H_Z * transpose(H_X), - zero_matrix(GF(2), nrows(H_Z), nrows(H))), side = :left) + flag, f_2 = can_solve_with_solution( + hcat(f_1, transpose(H)), + hcat(H_Z * transpose(H_X), zero_matrix(GF(2), nrows(H_Z), nrows(H))), + side = :left, + ) flag || error("there was no solution for f_2") - left_kernel(hcat(f_1, transpose(H)))[1] == 0 || @warn "there was more than one possible f_2, column $i" - H_X = hcat(vcat(H_X, zero_matrix(GF(2), nrows(H), ncols(H_X))), vcat(transpose(f_1), H)) + left_kernel(hcat(f_1, transpose(H)))[1] == 0 || + @warn "there was more than one possible f_2, column $i" + H_X = hcat( + vcat(H_X, zero_matrix(GF(2), nrows(H), ncols(H_X))), + vcat(transpose(f_1), H), + ) H_Z = hcat(H_Z, f_2) end return H_X, H_Z end -function _copying_as_coning_reduced(H_X::CTMatrixTypes, H_Z::CTMatrixTypes; permute = false, rng::AbstractRNG = Random.seed!()) +function _copying_as_coning_reduced( + H_X::CTMatrixTypes, + H_Z::CTMatrixTypes; + permute = false, + rng::AbstractRNG = Random.seed!(), +) F = base_ring(H_X) n_X = nrows(H_X) - for i in 1:ncols(H_X) + for i = 1:ncols(H_X) q = count(!iszero, H_X[:, 1]) if q <= 1 H_X = hcat(H_X[:, 2:end], H_X[:, 1:1]) @@ -236,41 +264,61 @@ function _copying_as_coning_reduced(H_X::CTMatrixTypes, H_Z::CTMatrixTypes; perm f_1 = zero_matrix(F, q, nrows(H_X)) for j in (permute ? shuffle(rng, 1:n_X) : 1:n_X) if H_X[j, 1] == 1 - f_1[count(!iszero, f_1) + 1, j] = 1 + f_1[count(!iszero, f_1)+1, j] = 1 end end H_X = H_X[:, 2:end] H_Z = H_Z[:, 2:end] - flag, f_2 = can_solve_with_solution(hcat(f_1, transpose(H)), hcat(H_Z * transpose(H_X), - zero_matrix(GF(2), nrows(H_Z), nrows(H))), side = :left) + flag, f_2 = can_solve_with_solution( + hcat(f_1, transpose(H)), + hcat(H_Z * transpose(H_X), zero_matrix(GF(2), nrows(H_Z), nrows(H))), + side = :left, + ) flag || error("there was no solution for f_2") - left_kernel(hcat(f_1, transpose(H)))[1] == 0 || @warn "there was more than one possible f_2" - H_X = hcat(vcat(H_X, zero_matrix(GF(2), nrows(H), ncols(H_X))), vcat(transpose(f_1), H)) + left_kernel(hcat(f_1, transpose(H)))[1] == 0 || + @warn "there was more than one possible f_2" + H_X = hcat( + vcat(H_X, zero_matrix(GF(2), nrows(H), ncols(H_X))), + vcat(transpose(f_1), H), + ) H_Z = hcat(H_Z, f_2) end return H_X, H_Z end -function _copying_as_coning_target(H_X::CTMatrixTypes, H_Z::CTMatrixTypes, target_q_X::Int = 3; - permute = false, rng::AbstractRNG = Random.seed!()) +function _copying_as_coning_target( + H_X::CTMatrixTypes, + H_Z::CTMatrixTypes, + target_q_X::Int = 3; + permute = false, + rng::AbstractRNG = Random.seed!(), +) target_q_X < 3 && throw(DomainError(target_q_X, "Must be at least 3")) F = base_ring(H_X) n_X = nrows(H_X) - for i in 1:ncols(H_X) + for i = 1:ncols(H_X) q = count(!iszero, H_X[:, 1]) if q <= target_q_X H_X = hcat(H_X[:, 2:end], H_X[:, 1:1]) H_Z = hcat(H_Z[:, 2:end], H_Z[:, 1:1]) continue end - H = matrix(F, diagm(q - target_q_X, q - target_q_X + 1, 0 => ones(Int, q - target_q_X), - 1 => ones(Int, q - target_q_X))) + H = matrix( + F, + diagm( + q - target_q_X, + q - target_q_X + 1, + 0 => ones(Int, q - target_q_X), + 1 => ones(Int, q - target_q_X), + ), + ) f_1 = zero_matrix(F, q - target_q_X + 1, nrows(H_X)) for j in (permute ? shuffle(rng, 1:n_X) : 1:n_X) if H_X[j, 1] == 1 k = 1 - while count(!iszero, f_1[k, :]) == target_q_X - 2 + isone(k) + (k == ncols(H)) + while count(!iszero, f_1[k, :]) == + target_q_X - 2 + isone(k) + (k == ncols(H)) k += 1 end f_1[k, j] = 1 @@ -278,10 +326,18 @@ function _copying_as_coning_target(H_X::CTMatrixTypes, H_Z::CTMatrixTypes, targe end H_X = H_X[:, 2:end] H_Z = H_Z[:, 2:end] - flag, f_2 = can_solve_with_solution(hcat(f_1, transpose(H)), hcat(H_Z * transpose(H_X), zero_matrix(GF(2), nrows(H_Z), nrows(H))), side = :left) + flag, f_2 = can_solve_with_solution( + hcat(f_1, transpose(H)), + hcat(H_Z * transpose(H_X), zero_matrix(GF(2), nrows(H_Z), nrows(H))), + side = :left, + ) flag || error("there was no solution for f_2") - left_kernel(hcat(f_1, transpose(H)))[1] == 0 || @warn "there was more than one possible solution for f_2" - H_X = hcat(vcat(H_X, zero_matrix(GF(2), nrows(H), ncols(H_X))), vcat(transpose(f_1), H)) + left_kernel(hcat(f_1, transpose(H)))[1] == 0 || + @warn "there was more than one possible solution for f_2" + H_X = hcat( + vcat(H_X, zero_matrix(GF(2), nrows(H), ncols(H_X))), + vcat(transpose(f_1), H), + ) H_Z = hcat(H_Z, f_2) end return H_X, H_Z @@ -293,15 +349,20 @@ end Return the result of copying on `H_X` and `H_Z` using either the Hastings, reduced, or targeted methods by using the mapping cone. """ -function copying_as_coning(H_X::CTMatrixTypes, H_Z::CTMatrixTypes; method::Symbol = :Hastings, - target_q_X::Int = 3, rng::AbstractRNG = Random.seed!()) +function copying_as_coning( + H_X::CTMatrixTypes, + H_Z::CTMatrixTypes; + method::Symbol = :Hastings, + target_q_X::Int = 3, + rng::AbstractRNG = Random.seed!(), +) method ∈ (:Hastings, :reduced, :target) || throw(ArgumentError("Unknown method type")) target_q_X >= 3 || throw(DomainError(target_q_X, "Target must be at least 3")) # should we check these commute or trust the user? if method == :Hastings - return _copying_as_coning_Hastings(H_X, H_Z, rng = rng) + return _copying_as_coning_Hastings(H_X, H_Z, rng = rng) elseif method == :reduced return _copying_as_coning_reduced(H_X, H_Z, rng = rng) else @@ -315,20 +376,42 @@ end Return the result of copying on `S` using either the Hastings, reduced, or targeted methods by using the mapping cone. """ -copying_as_coning(S::T; method::Symbol = :Hastings, target_q_X::Int = 3, rng::AbstractRNG = Random.seed!()) where - {T <: AbstractStabilizerCode} = copying_as_coning(CSSTrait(T), S, method, target_q_X, rng) -function copying_as_coning(::IsCSS, S::AbstractStabilizerCode, method::Symbol, target_q_X::Int, rng::AbstractRNG = Random.seed!()) +copying_as_coning( + S::T; + method::Symbol = :Hastings, + target_q_X::Int = 3, + rng::AbstractRNG = Random.seed!(), +) where {T<:AbstractStabilizerCode} = + copying_as_coning(CSSTrait(T), S, method, target_q_X, rng) +function copying_as_coning( + ::IsCSS, + S::AbstractStabilizerCode, + method::Symbol, + target_q_X::Int, + rng::AbstractRNG = Random.seed!(), +) method ∈ (:Hastings, :reduced, :target) || throw(ArgumentError("Unknown method type")) target_q_X >= 3 || throw(DomainError(target_q_X, "Target must be at least 3")) - H_X, H_Z = copying_as_coning(S.X_stabs, S.Z_stabs, method = method, target_q_X = target_q_X, rng = rng) + H_X, H_Z = copying_as_coning( + S.X_stabs, + S.Z_stabs, + method = method, + target_q_X = target_q_X, + rng = rng, + ) return CSSCode(H_X, H_Z) end -copying_as_coning(::IsNotCSS, S::AbstractStabilizerCode, method::Symbol, target_q_X::Int, rng::AbstractRNG = Random.seed!()) = - error("Only valid for CSS codes.") +copying_as_coning( + ::IsNotCSS, + S::AbstractStabilizerCode, + method::Symbol, + target_q_X::Int, + rng::AbstractRNG = Random.seed!(), +) = error("Only valid for CSS codes.") ############################# - # Gauging +# Gauging ############################# """ @@ -343,7 +426,7 @@ function gauging(H_X::CTMatrixTypes, H_Z::CTMatrixTypes) weights = zeros(Int, n_X) num_X = 0 num_new_qubits = 0 - for i in 1:n_X + for i = 1:n_X weights[i] = count(!iszero, H_X[i, :]) num_X += max(1, weights[i] - 2) num_new_qubits += max(0, weights[i] - 3) @@ -361,12 +444,12 @@ function gauging(H_X::CTMatrixTypes, H_Z::CTMatrixTypes) for (i, wt) in enumerate(weights) if wt < 4 # just copy in the old stabilizer - for j in 1:n + for j = 1:n X[i_new, j] = H_X[i, j] end i_new += 1 else - new_qubits = new_qubit_index:new_qubit_index + wt - 3 + new_qubits = new_qubit_index:(new_qubit_index+wt-3) # cut the X stabilizer up in to weight 3 stabilizers for (l, k) in enumerate(new_qubits) @@ -376,23 +459,23 @@ function gauging(H_X::CTMatrixTypes, H_Z::CTMatrixTypes) X[i_new, nonzeros[2]] = H_X[i, nonzeros[2]] X[i_new, k] = 1 elseif k == wt - 3 + new_qubit_index - X[i_new, nonzeros[end - 1]] = H_X[i, nonzeros[end - 1]] + X[i_new, nonzeros[end-1]] = H_X[i, nonzeros[end-1]] X[i_new, nonzeros[end]] = H_X[i, nonzeros[end]] - X[i_new, k - 1] = 1 + X[i_new, k-1] = 1 else - X[i_new, nonzeros[l + 1]] = H_X[i, nonzeros[l + 1]] - X[i_new, k - 1] = 1 + X[i_new, nonzeros[l+1]] = H_X[i, nonzeros[l+1]] + X[i_new, k-1] = 1 X[i_new, k] = 1 end i_new += 1 end # adjust the new qubits of the Z stabilizers so that they commute with the new X stabilizers - for j in 1:n_Z + for j = 1:n_Z Z_qubits = getindex.(findall(!iszero, Z[j, :]), 2) X_qubits = getindex.(findall(!iszero, H_X[i, :]), 2) - for m in 1:wt - 3 - if isodd(length(Z_qubits ∩ X_qubits[1:m + 1])) + for m = 1:(wt-3) + if isodd(length(Z_qubits ∩ X_qubits[1:(m+1)])) Z[j, new_qubits[m]] = 1 end end @@ -409,7 +492,7 @@ end Return the result of gauging on `S`. """ -gauging(S::T) where {T <: AbstractStabilizerCode} = gauging(CSSTrait(T), S) +gauging(S::T) where {T<:AbstractStabilizerCode} = gauging(CSSTrait(T), S) gauging(::IsCSS, S::AbstractStabilizerCode) = CSSCode(gauging(S.X_stabs, S.Z_stabs)...) gauging(::IsNotCSS, S::AbstractStabilizerCode) = error("Only valid for CSS codes.") @@ -419,25 +502,38 @@ gauging(::IsNotCSS, S::AbstractStabilizerCode) = error("Only valid for CSS codes Return the result of gauging on `H_X` and `H_Z` by using the mapping cone. """ -function gauging_as_coning(H_X::CTMatrixTypes, H_Z::CTMatrixTypes; target_w_X::Int = 3, - permute = false, rng::AbstractRNG = Random.seed!()) +function gauging_as_coning( + H_X::CTMatrixTypes, + H_Z::CTMatrixTypes; + target_w_X::Int = 3, + permute = false, + rng::AbstractRNG = Random.seed!(), +) target_w_X < 3 && throw(DomainError(target_w_X, "Must be at least 3")) F = base_ring(H_X) n = ncols(H_X) - for i in 1:nrows(H_X) + for i = 1:nrows(H_X) w = count(!iszero, H_X[1, :]) if w <= target_w_X H_X = vcat(H_X[2:end, :], H_X[1:1, :]) continue end - H = matrix(F, diagm(w - target_w_X, w - target_w_X + 1, 0 => ones(Int, w - target_w_X), - 1 => ones(Int, w - target_w_X))) + H = matrix( + F, + diagm( + w - target_w_X, + w - target_w_X + 1, + 0 => ones(Int, w - target_w_X), + 1 => ones(Int, w - target_w_X), + ), + ) f_1 = zero_matrix(F, w - target_w_X + 1, ncols(H_X)) for j in (permute ? shuffle(rng, 1:n) : 1:n) if isone(H_X[1, j]) k = 1 - while count(!iszero, f_1[k, :]) == target_w_X - 2 + isone(k) + (k == ncols(H)) + while count(!iszero, f_1[k, :]) == + target_w_X - 2 + isone(k) + (k == ncols(H)) k += 1 end f_1[k, j] = 1 @@ -445,8 +541,10 @@ function gauging_as_coning(H_X::CTMatrixTypes, H_Z::CTMatrixTypes; target_w_X::I end flag, f_2 = can_solve_with_solution(transpose(H), f_1 * transpose(H_Z)) flag || error("there was no solution for f_2") - H_X = vcat(hcat(H_X[2:end, :], zero_matrix(F, nrows(H_X) - 1, nrows(H))), - hcat(f_1, transpose(H))) + H_X = vcat( + hcat(H_X[2:end, :], zero_matrix(F, nrows(H_X) - 1, nrows(H))), + hcat(f_1, transpose(H)), + ) H_Z = hcat(H_Z, transpose(f_2)) end return H_X, H_Z @@ -457,10 +555,17 @@ end Return the result of gauging on `S` by using the mapping cone. """ -gauging_as_coning(S::T; rng::AbstractRNG = Random.seed!()) where {T <: AbstractStabilizerCode} = gauging_as_coning(CSSTrait(T), S, rng = rng) -gauging_as_coning(::IsCSS, S::AbstractStabilizerCode; rng::AbstractRNG = Random.seed!()) = CSSCode(gauging_as_coning(S.X_stabs, - S.Z_stabs, rng = rng)...) -gauging_as_coning(::IsNotCSS, S::AbstractStabilizerCode; rng::AbstractRNG = Random.seed!()) = error("Only valid for CSS codes.") +gauging_as_coning( + S::T; + rng::AbstractRNG = Random.seed!(), +) where {T<:AbstractStabilizerCode} = gauging_as_coning(CSSTrait(T), S, rng = rng) +gauging_as_coning(::IsCSS, S::AbstractStabilizerCode; rng::AbstractRNG = Random.seed!()) = + CSSCode(gauging_as_coning(S.X_stabs, S.Z_stabs, rng = rng)...) +gauging_as_coning( + ::IsNotCSS, + S::AbstractStabilizerCode; + rng::AbstractRNG = Random.seed!(), +) = error("Only valid for CSS codes.") ############################# # Thickening And Choosing Heights @@ -486,7 +591,12 @@ gauging_as_coning(::IsNotCSS, S::AbstractStabilizerCode; rng::AbstractRNG = Rand Return the result of thickening and choosing heights on `H_X` and `H_Z`. """ -function thickening_and_choose_heights(H_X::CTMatrixTypes, H_Z::CTMatrixTypes, l::Integer, heights::Vector{Int}) +function thickening_and_choose_heights( + H_X::CTMatrixTypes, + H_Z::CTMatrixTypes, + l::Integer, + heights::Vector{Int}, +) F = base_ring(H_X) n_Z = nrows(H_Z) @@ -506,19 +616,33 @@ end Return the result of thickening and choosing heights on `S`. """ -thickening_and_choose_heights(S::T, l::Integer, heights::Vector{Int}) where {T <: - AbstractStabilizerCode} = thickening_and_choose_heights(CSSTrait(T), S, l, heights) -thickening_and_choose_heights(::IsCSS, S::AbstractStabilizerCode, l::Integer, - heights::Vector{Int}) = CSSCode(thickening_and_choose_heights(S.X_stabs, S.Z_stabs, - l, heights)...) -thickening_and_choose_heights(::IsNotCSS, S::AbstractStabilizerCode, l::Integer, - heights::Vector{Int}) = error("Only valid for CSS codes.") +thickening_and_choose_heights( + S::T, + l::Integer, + heights::Vector{Int}, +) where {T<:AbstractStabilizerCode} = + thickening_and_choose_heights(CSSTrait(T), S, l, heights) +thickening_and_choose_heights( + ::IsCSS, + S::AbstractStabilizerCode, + l::Integer, + heights::Vector{Int}, +) = CSSCode(thickening_and_choose_heights(S.X_stabs, S.Z_stabs, l, heights)...) +thickening_and_choose_heights( + ::IsNotCSS, + S::AbstractStabilizerCode, + l::Integer, + heights::Vector{Int}, +) = error("Only valid for CSS codes.") ############################# - # Coning +# Coning ############################# -function _cycle_basis_decongestion(_edges::Vector{Tuple{T, T}}; rng::AbstractRNG = Random.seed!()) where T +function _cycle_basis_decongestion( + _edges::Vector{Tuple{T,T}}; + rng::AbstractRNG = Random.seed!(), +) where {T} edges = Vector{T}[[e...] for e in _edges] vertices = unique(union(_edges...)) degrees = zeros(Int, length(vertices)) @@ -546,7 +670,10 @@ function _cycle_basis_decongestion(_edges::Vector{Tuple{T, T}}; rng::AbstractRNG while 1 in degrees i = findfirst(isequal(1), degrees) j = findfirst(vertices[i] == first(e) || vertices[i] == last(e) for e in edges) - k = findfirst(isequal(setdiff([edges[j][1], edges[j][end]], vertices[i])[1]), vertices) + k = findfirst( + isequal(setdiff([edges[j][1], edges[j][end]], vertices[i])[1]), + vertices, + ) degrees[k] -= 1 degrees[i] -= 1 deleteat!(edges, j) @@ -556,7 +683,7 @@ function _cycle_basis_decongestion(_edges::Vector{Tuple{T, T}}; rng::AbstractRNG # note that this is modified from 2A in the paper, but it doesn't harm their proof. j = findall(e -> first(e) == last(e), edges) for k in j - push!(cycles, edges[k][1:end - 1]) + push!(cycles, edges[k][1:(end-1)]) degrees[findfirst(isequal(first(edges[k])), vertices)] -= 2 end isnothing(j) || deleteat!(edges, j) @@ -571,14 +698,17 @@ function _cycle_basis_decongestion(_edges::Vector{Tuple{T, T}}; rng::AbstractRNG deleteat!(edges, j[2]) degrees[i] -= 2 - # step 3: if all vertices have degree > 2 then find and save a short cycle, remove an edge of that cycle from the graph + # step 3: if all vertices have degree > 2 then find and save a short cycle, remove an edge of that cycle from the graph elseif maximum(degrees) > 2 && 1 ∉ degrees && 2 ∉ degrees # At this point, the graph does not have self-edges because I modified step 2A. # detect if there are any double-edges, if there are pick randomly: indices = nothing for e in shuffle(rng, edges) - j = findall(sort([first(e), last(e)]) == sort([first(e2), last(e2)]) for e2 in edges) + j = findall( + sort([first(e), last(e)]) == sort([first(e2), last(e2)]) for + e2 in edges + ) if length(j) > 1 indices = j[randperm(length(j))[1:2]] break @@ -586,8 +716,9 @@ function _cycle_basis_decongestion(_edges::Vector{Tuple{T, T}}; rng::AbstractRNG end if !isnothing(indices) # there is a double-edge, so add that cycle and remove one of the edges - last(edges[indices[1]]) == first(edges[indices[2]]) || reverse!(edges[indices[2]]) - push!(cycles, [edges[indices[1]]; edges[indices[2]][2:end - 1]]) + last(edges[indices[1]]) == first(edges[indices[2]]) || + reverse!(edges[indices[2]]) + push!(cycles, [edges[indices[1]]; edges[indices[2]][2:(end-1)]]) degrees[findfirst(isequal(first(edges[indices[1]])), vertices)] -= 1 degrees[findfirst(isequal(last(edges[indices[1]])), vertices)] -= 1 deleteat!(edges, indices[2]) @@ -597,15 +728,29 @@ function _cycle_basis_decongestion(_edges::Vector{Tuple{T, T}}; rng::AbstractRNG tempcycles = Grphs.cycle_basis(Grphs.SimpleGraph(Grphs.SimpleEdge.(temp))) _, i = findmin(length, tempcycles) c = tempcycles[i] - length(c) > 2log2(count(!iszero, degrees)) && @warn "cycle $(length(cycles) + 1) is longer than necessary" + length(c) > 2log2(count(!iszero, degrees)) && + @warn "cycle $(length(cycles) + 1) is longer than necessary" cycle = [c[1]] - for i in 2:length(c) - j = findfirst(sort([first(e), last(e)]) == sort([last(cycle), c[i]]) for e in edges) - append!(cycle, first(edges[j]) == last(cycle) ? edges[j][2:end] : edges[j][end - 1:-1:1]) + for i = 2:length(c) + j = findfirst( + sort([first(e), last(e)]) == sort([last(cycle), c[i]]) for + e in edges + ) + append!( + cycle, + first(edges[j]) == last(cycle) ? edges[j][2:end] : + edges[j][(end-1):-1:1], + ) end - j = findfirst(sort([first(e), last(e)]) == sort([last(cycle), c[1]]) for e in edges) + j = findfirst( + sort([first(e), last(e)]) == sort([last(cycle), c[1]]) for e in edges + ) if length(edges[j]) > 2 - append!(cycle, first(edges[j]) == last(cycle) ? edges[j][2:end - 1] : edges[j][end - 1:-1:2]) + append!( + cycle, + first(edges[j]) == last(cycle) ? edges[j][2:(end-1)] : + edges[j][(end-1):-1:2], + ) end push!(cycles, cycle) degrees[findfirst(isequal(first(edges[j])), vertices)] -= 1 @@ -625,13 +770,19 @@ end Return the result of coning on `H_X` and `H_Z` by reducing the `Z` stabilizers in `row_indices`. The optional argument `rng` can be used to make the output of this function reproducible. """ -function coning(H_X::T, H_Z::T, row_indices::AbstractVector{Int}; rng::AbstractRNG = Random.seed!()) where T <: CTMatrixTypes - +function coning( + H_X::T, + H_Z::T, + row_indices::AbstractVector{Int}; + rng::AbstractRNG = Random.seed!(), +) where {T<:CTMatrixTypes} + F = base_ring(H_X) n_X, n = size(H_X) n_Z = size(H_Z, 1) - issubset(row_indices, 1:n_Z) || throw(DomainError(row_indices, "Choice of Z stabilizers is out of bounds.")) + issubset(row_indices, 1:n_Z) || + throw(DomainError(row_indices, "Choice of Z stabilizers is out of bounds.")) hx = _Flint_matrix_to_Julia_int_matrix(H_X) hz = _Flint_matrix_to_Julia_int_matrix(H_Z) @@ -649,10 +800,15 @@ function coning(H_X::T, H_Z::T, row_indices::AbstractVector{Int}; rng::AbstractR end p1 = hx[:, Q] - zero_rows = findall(iszero, p1[i, :] for i in 1:n_X) + zero_rows = findall(iszero, p1[i, :] for i = 1:n_X) nonzero_rows = setdiff(1:n_X, zero_rows) p1 = p1[nonzero_rows, :] - all(2 == count(isone, p1[i, :]) for i in 1:size(p1, 1)) || throw(DomainError(row_indices, "Z stabilizers chosen for reducing must have overlap of at most 2 with all X stabilizers.")) + all(2 == count(isone, p1[i, :]) for i = 1:size(p1, 1)) || throw( + DomainError( + row_indices, + "Z stabilizers chosen for reducing must have overlap of at most 2 with all X stabilizers.", + ), + ) f0 = zeros(Int, n_X, length(nonzero_rows)) for (j, i) in enumerate(nonzero_rows) @@ -668,11 +824,11 @@ function coning(H_X::T, H_Z::T, row_indices::AbstractVector{Int}; rng::AbstractR # take care of length 2 cycles for (i, e) in enumerate(unique_edges) if count(isequal(e), edges) > 1 - repeats = findall(1 == p1[j, e[1]] == p1[j, e[2]] for j in 1:size(p1, 1)) + repeats = findall(1 == p1[j, e[1]] == p1[j, e[2]] for j = 1:size(p1, 1)) nr, nc = size(p0) p0 = vcat(p0, zeros(Int, length(repeats) - 1, nc)) - for j in 1:length(repeats) - 1 - p0[nr + j, repeats[j:j + 1]] .= 1 + for j = 1:(length(repeats)-1) + p0[nr+j, repeats[j:(j+1)]] .= 1 end end end @@ -684,15 +840,36 @@ function coning(H_X::T, H_Z::T, row_indices::AbstractVector{Int}; rng::AbstractR p0 = vcat(p0, zeros(Int, num_cells, cols)) if num_cells == 1 # i.e., if length(c) <= 4, don't cellulate if length(c) == 3 - e1 = rand(rng, findall(1 == p1[j, c[1]] == p1[j, c[2]] for j in 1:size(p1, 1))) - e2 = rand(rng, findall(1 == p1[j, c[2]] == p1[j, c[3]] for j in 1:size(p1, 1))) - e3 = rand(rng, findall(1 == p1[j, c[3]] == p1[j, c[1]] for j in 1:size(p1, 1))) + e1 = rand( + rng, + findall(1 == p1[j, c[1]] == p1[j, c[2]] for j = 1:size(p1, 1)), + ) + e2 = rand( + rng, + findall(1 == p1[j, c[2]] == p1[j, c[3]] for j = 1:size(p1, 1)), + ) + e3 = rand( + rng, + findall(1 == p1[j, c[3]] == p1[j, c[1]] for j = 1:size(p1, 1)), + ) p0[end, [e1, e2, e3]] .= 1 else - e1 = rand(rng, findall(1 == p1[j, c[1]] == p1[j, c[2]] for j in 1:size(p1, 1))) - e2 = rand(rng, findall(1 == p1[j, c[2]] == p1[j, c[3]] for j in 1:size(p1, 1))) - e3 = rand(rng, findall(1 == p1[j, c[3]] == p1[j, c[4]] for j in 1:size(p1, 1))) - e4 = rand(rng, findall(1 == p1[j, c[4]] == p1[j, c[1]] for j in 1:size(p1, 1))) + e1 = rand( + rng, + findall(1 == p1[j, c[1]] == p1[j, c[2]] for j = 1:size(p1, 1)), + ) + e2 = rand( + rng, + findall(1 == p1[j, c[2]] == p1[j, c[3]] for j = 1:size(p1, 1)), + ) + e3 = rand( + rng, + findall(1 == p1[j, c[3]] == p1[j, c[4]] for j = 1:size(p1, 1)), + ) + e4 = rand( + rng, + findall(1 == p1[j, c[4]] == p1[j, c[1]] for j = 1:size(p1, 1)), + ) p0[end, [e1, e2, e3, e4]] .= 1 end else # cellulate @@ -700,20 +877,38 @@ function coning(H_X::T, H_Z::T, row_indices::AbstractVector{Int}; rng::AbstractR p1rows = size(p1, 1) p1 = vcat(p1, zeros(Int, num_cells - 1, size(p1, 2))) f0 = hcat(f0, zeros(Int, size(f0, 1), num_cells - 1)) - for i in 1:num_cells - 1 - p0[rows + i:rows + i + 1, cols + i] .= 1 - p1[p1rows + i, c[[1 + i, end - i]]] .= 1 + for i = 1:(num_cells-1) + p0[(rows+i):(rows+i+1), cols+i] .= 1 + p1[p1rows+i, c[[1 + i, end - i]]] .= 1 end - for i in 1:num_cells - e1 = rand(rng, findall(1 == p1[j, c[i]] == p1[j, c[i + 1]] for j in 1:size(p1, 1))) - e2 = rand(rng, findall(1 == p1[j, c[end - i + 1]] == p1[j, c[end - i]] for j in 1:size(p1, 1))) - p0[rows + i, [e1, e2]] .= 1 + for i = 1:num_cells + e1 = rand( + rng, + findall(1 == p1[j, c[i]] == p1[j, c[i+1]] for j = 1:size(p1, 1)), + ) + e2 = rand( + rng, + findall( + 1 == p1[j, c[end-i+1]] == p1[j, c[end-i]] for j = 1:size(p1, 1) + ), + ) + p0[rows+i, [e1, e2]] .= 1 if i == 1 - e3 = rand(rng, findall(1 == p1[j, c[1]] == p1[j, c[end]] for j in 1:size(p1, 1))) - p0[rows + i, e3] = 1 + e3 = rand( + rng, + findall( + 1 == p1[j, c[1]] == p1[j, c[end]] for j = 1:size(p1, 1) + ), + ) + p0[rows+i, e3] = 1 elseif i == num_cells && iseven(length(c)) - e3 = rand(rng, findall(1 == p1[j, c[end - i]] == p1[j, c[i + 1]] for j in 1:size(p1, 1))) - p0[rows + i, e3] = 1 + e3 = rand( + rng, + findall( + 1 == p1[j, c[end-i]] == p1[j, c[i+1]] for j = 1:size(p1, 1) + ), + ) + p0[rows+i, e3] = 1 end end end @@ -732,7 +927,10 @@ function coning(H_X::T, H_Z::T, row_indices::AbstractVector{Int}; rng::AbstractR H_X_new = hcat(vcat(p0, f0), vcat(zero_matrix(F, size(p0, 1), n), H_X)) H_Z_remaining_tr = transpose(H_Z[setdiff(1:n_Z, row_indices), :]) - H_Z_new_tr = hcat(vcat(p1, f1), vcat(zero_matrix(F, size(p1, 1), size(H_Z_remaining_tr, 2)), H_Z_remaining_tr)) + H_Z_new_tr = hcat( + vcat(p1, f1), + vcat(zero_matrix(F, size(p1, 1), size(H_Z_remaining_tr, 2)), H_Z_remaining_tr), + ) return H_X_new, transpose(H_Z_new_tr) end @@ -744,16 +942,27 @@ end Return the result of coning on `S` by reducing the `Z` stabilizers in `row_indices`. The optional argument `rng` can be used to make the output of this function reproducible. """ -coning(S::T, row_indices::AbstractVector{Int}; rng::AbstractRNG = Random.seed!()) where {T <: - AbstractStabilizerCode} = coning(CSSTrait(T), S, row_indices, rng = rng) -coning(::IsCSS, S::AbstractStabilizerCode, row_indices::AbstractVector{Int}; - rng::AbstractRNG = Random.seed!()) = CSSCode(coning(S.X_stabs, S.Z_stabs, row_indices, rng = rng)...) -coning(::IsNotCSS, S::AbstractStabilizerCode, row_indices::AbstractVector{Int}; - rng::AbstractRNG = Random.seed!()) = error("Only valid for CSS codes.") +coning( + S::T, + row_indices::AbstractVector{Int}; + rng::AbstractRNG = Random.seed!(), +) where {T<:AbstractStabilizerCode} = coning(CSSTrait(T), S, row_indices, rng = rng) +coning( + ::IsCSS, + S::AbstractStabilizerCode, + row_indices::AbstractVector{Int}; + rng::AbstractRNG = Random.seed!(), +) = CSSCode(coning(S.X_stabs, S.Z_stabs, row_indices, rng = rng)...) +coning( + ::IsNotCSS, + S::AbstractStabilizerCode, + row_indices::AbstractVector{Int}; + rng::AbstractRNG = Random.seed!(), +) = error("Only valid for CSS codes.") ############################# - # All +# All ############################# """ @@ -762,16 +971,39 @@ coning(::IsNotCSS, S::AbstractStabilizerCode, row_indices::AbstractVector{Int}; Return the weight-reduced CSS code of `S`. """ -quantum_weight_reduction(S::T, l1::Int, heights::Vector{Int}; copying_type::Symbol = :Hastings, - copying_target::Int = 3, l2::Int = 1, - rng::AbstractRNG = Random.seed!()) where {T <: AbstractStabilizerCode} = - quantum_weight_reduction(CSSTrait(T), S, l1, heights, copying_type = copying_type, - copying_target = copying_target, l2 = l2, rng = rng) -function quantum_weight_reduction(::IsCSS, S::AbstractStabilizerCode, l1::Int, heights::Vector{Int}; - copying_type::Symbol, copying_target::Int, l2::Int, rng::AbstractRNG = Random.seed!()) - - copying_type ∈ (:Hastings, :reduced, :target) || throw(ArgumentError("Unknown copying method")) - H_X, H_Z = copying(S.X_stabs, S.Z_stabs, method = copying_type, target_q_X = copying_target) +quantum_weight_reduction( + S::T, + l1::Int, + heights::Vector{Int}; + copying_type::Symbol = :Hastings, + copying_target::Int = 3, + l2::Int = 1, + rng::AbstractRNG = Random.seed!(), +) where {T<:AbstractStabilizerCode} = quantum_weight_reduction( + CSSTrait(T), + S, + l1, + heights, + copying_type = copying_type, + copying_target = copying_target, + l2 = l2, + rng = rng, +) +function quantum_weight_reduction( + ::IsCSS, + S::AbstractStabilizerCode, + l1::Int, + heights::Vector{Int}; + copying_type::Symbol, + copying_target::Int, + l2::Int, + rng::AbstractRNG = Random.seed!(), +) + + copying_type ∈ (:Hastings, :reduced, :target) || + throw(ArgumentError("Unknown copying method")) + H_X, H_Z = + copying(S.X_stabs, S.Z_stabs, method = copying_type, target_q_X = copying_target) H_X, H_Z = gauging(H_X, H_Z) a = nrows(H_Z) H_X, H_Z = thickening_and_choose_heights(H_X, H_Z, l1, heights) @@ -784,26 +1016,51 @@ function quantum_weight_reduction(::IsCSS, S::AbstractStabilizerCode, l1::Int, h F = base_ring(H_X) H = matrix(F, diagm(l2 - 1, l2, 0 => ones(Int, l2 - 1), 1 => ones(Int, l2 - 1))) Z = hcat(identity_matrix(F, n_Z) ⊗ transpose(H), H_Z ⊗ identity_matrix(F, l2)) - X1 = hcat(transpose(H_Z) ⊗ identity_matrix(F, l2 - 1), identity_matrix(F, n) ⊗ H) - X2 = hcat(zero_matrix(F, l2 * n_X, (l2 - 1) * n_Z), H_X ⊗ identity_matrix(F, l2)) + X1 = + hcat(transpose(H_Z) ⊗ identity_matrix(F, l2 - 1), identity_matrix(F, n) ⊗ H) + X2 = + hcat(zero_matrix(F, l2 * n_X, (l2 - 1) * n_Z), H_X ⊗ identity_matrix(F, l2)) # TODO: figure out a good way to compute heights # choosing heights here is not done in the same way as before. We only choose heights for part of it. num_heights = n_X - n_X_precone heights = rand(1:l2, num_heights) - X3 = X2[[h + l2 * (i - 1) for (i, h) in enumerate(heights)] ∪ (num_heights * l2 + 1:size(X2, 1)), :] + X3 = X2[ + [h+l2*(i-1) for (i, h) in enumerate(heights)]∪((num_heights*l2+1):size(X2, 1)), + :, + ] vcat(X1, X3), Z else H_X, H_Z end return CSSCode(H_X, H_Z) end -quantum_weight_reduction(::IsNotCSS, S::AbstractStabilizerCode, l1::Int, heights::Vector{Int}; - copying_type::Symbol = :Hastings, copying_target::Int = 3, l2::Int = 1, - rng::AbstractRNG = Random.seed!()) = error("Only valid for CSS codes.") - -weight_reduction(S::AbstractStabilizerCode, l1::Int, heights::Vector{Int}; - copying_type::Symbol = :Hastings, copying_target::Int = 3, l2::Int = 1, - rng::AbstractRNG = Random.seed!()) = quantum_weight_reduction(S, l1, heights, - copying_type = copying_type, copying_target = copying_target, l2 = l2, rng = rng) +quantum_weight_reduction( + ::IsNotCSS, + S::AbstractStabilizerCode, + l1::Int, + heights::Vector{Int}; + copying_type::Symbol = :Hastings, + copying_target::Int = 3, + l2::Int = 1, + rng::AbstractRNG = Random.seed!(), +) = error("Only valid for CSS codes.") + +weight_reduction( + S::AbstractStabilizerCode, + l1::Int, + heights::Vector{Int}; + copying_type::Symbol = :Hastings, + copying_target::Int = 3, + l2::Int = 1, + rng::AbstractRNG = Random.seed!(), +) = quantum_weight_reduction( + S, + l1, + heights, + copying_type = copying_type, + copying_target = copying_target, + l2 = l2, + rng = rng, +) diff --git a/src/chain_complex.jl b/src/chain_complex.jl index c899fe4d..6bc575b7 100644 --- a/src/chain_complex.jl +++ b/src/chain_complex.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # constructors +# constructors ############################# # Base.zero(phi::AbstractAlgebra.Generic.ModuleHomomorphism) = hom(domain(phi), codomain(phi), [zero(codomain(phi)) for i in 1:ngens(domain(phi))]) @@ -16,12 +16,13 @@ Return the chain complex whose boundary maps are given by `∂s` and lowest degree by `lowest_degree`. """ -function chain_complex(∂s::Vector{T}; lowest_degree::Int=0) where T <: CTMatrixTypes +function chain_complex(∂s::Vector{T}; lowest_degree::Int = 0) where {T<:CTMatrixTypes} F = base_ring(∂s[1]) - all(x -> base_ring(x) == F, ∂s) || throw(ArgumentError("All inputs must be over the same base ring")) + all(x -> base_ring(x) == F, ∂s) || + throw(ArgumentError("All inputs must be over the same base ring")) spaces = [[vector_space(F, ncols(∂i)) for ∂i in ∂s]; vector_space(F, nrows(∂s[end]))] # need to transpose because they are forced into right multiplication for noncommuntative rings - morphisms = [hom(spaces[i], spaces[i + 1], transpose(∂i)) for (i, ∂i) in enumerate(∂s)] + morphisms = [hom(spaces[i], spaces[i+1], transpose(∂i)) for (i, ∂i) in enumerate(∂s)] # ComplexOfMorphisms(typeof(spaces[1]), morphisms, typ = :chain, seed = lowest_degree) return chain_complex(morphisms; seed = lowest_degree) end @@ -33,8 +34,10 @@ end Return the 3-term chain complex associated with the CSS code `S`. """ chain_complex(S::AbstractStabilizerCode) = chain_complex(CSSTrait(typeof(S)), S) -chain_complex(::IsCSS, S::AbstractStabilizerCode) = chain_complex([transpose(S.Z_stabs), S.X_stabs]) -chain_complex(::IsNotCSS, S::AbstractStabilizerCode) = throw(ArgumentError("This is only defined for CSS codes")) +chain_complex(::IsCSS, S::AbstractStabilizerCode) = + chain_complex([transpose(S.Z_stabs), S.X_stabs]) +chain_complex(::IsNotCSS, S::AbstractStabilizerCode) = + throw(ArgumentError("This is only defined for CSS codes")) """ chain_complex(C::AbstractLinearCode) @@ -44,7 +47,7 @@ Return the 2-term chain complex associated with the parity-check matrix of `C`. chain_complex(C::AbstractLinearCode) = chain_complex([parity_check_matrix(C)]) ############################# - # getter functions +# getter functions ############################# """ @@ -84,11 +87,11 @@ Return `:chain` if `chain` is a chain complex or `:cochain` if it is a cochain c type(chain::CTChainComplex) = chain.typ ############################# - # setter functions +# setter functions ############################# ############################# - # general functions +# general functions ############################# # TODO: redo @@ -97,7 +100,8 @@ type(chain::CTChainComplex) = chain.typ Return the dual of the chain complex. """ -cochain(chain::ChainComplex) = ChainComplex([transpose(∂) for ∂ in reverse(chain.boundaries)]) +cochain(chain::ChainComplex) = + ChainComplex([transpose(∂) for ∂ in reverse(chain.boundaries)]) """ ⊗(chain_A::ChainComplex{T}, chain_B::ChainComplex{T}) where T <: CTMatrixTypes @@ -110,13 +114,19 @@ double_complex(chain_A::CTChainComplex, chain_B::CTChainComplex) = chain_A ⊗ c bicomplex(chain_A::CTChainComplex, chain_B::CTChainComplex) = chain_A ⊗ chain_B -double_complex(C1::AbstractLinearCode, C2::AbstractLinearCode) = chain_complex(C1) ⊗ chain_complex(C2) -double_complex(S::AbstractStabilizerCodeCSS, C::AbstractLinearCode) = chain_complex(S) ⊗ chain_complex(C) -double_complex(S1::AbstractStabilizerCodeCSS, S2::AbstractStabilizerCodeCSS) = chain_complex(S1) ⊗ chain_complex(S2) +double_complex(C1::AbstractLinearCode, C2::AbstractLinearCode) = + chain_complex(C1) ⊗ chain_complex(C2) +double_complex(S::AbstractStabilizerCodeCSS, C::AbstractLinearCode) = + chain_complex(S) ⊗ chain_complex(C) +double_complex(S1::AbstractStabilizerCodeCSS, S2::AbstractStabilizerCodeCSS) = + chain_complex(S1) ⊗ chain_complex(S2) -total_complex(C1::AbstractLinearCode, C2::AbstractLinearCode) = total_complex(double_complex(C1, C2)) -total_complex(S::AbstractStabilizerCodeCSS, C::AbstractLinearCode) = total_complex(double_complex(S, C)) -total_complex(S1::AbstractStabilizerCodeCSS, S2::AbstractStabilizerCodeCSS) = total_complex(double_complex(S1, S2)) +total_complex(C1::AbstractLinearCode, C2::AbstractLinearCode) = + total_complex(double_complex(C1, C2)) +total_complex(S::AbstractStabilizerCodeCSS, C::AbstractLinearCode) = + total_complex(double_complex(S, C)) +total_complex(S1::AbstractStabilizerCodeCSS, S2::AbstractStabilizerCodeCSS) = + total_complex(double_complex(S1, S2)) """ distance_balancing(S::StabilizerCodeCSS, C::AbstractLinearCode) diff --git a/src/iterators.jl b/src/iterators.jl index 9c2705a4..b4fb90eb 100644 --- a/src/iterators.jl +++ b/src/iterators.jl @@ -13,14 +13,14 @@ struct SubsetGrayCode end Base.IteratorEltype(::SubsetGrayCode) = Base.HasEltype() -Base.eltype(::SubsetGrayCode) = Array{Int, 1} +Base.eltype(::SubsetGrayCode) = Array{Int,1} Base.IteratorSize(::SubsetGrayCode) = Base.HasLength() @inline function Base.length(G::SubsetGrayCode) return G.len end -Base.in(v::Vector{Int}, G::SubsetGrayCode) = length(v) == G.k +Base.in(v::Vector{Int}, G::SubsetGrayCode) = length(v) == G.k -@inline function Base.isdone(G::SubsetGrayCode, state) +@inline function Base.isdone(G::SubsetGrayCode, state) (_, rank, _) = state return rank == G.len end @@ -48,12 +48,12 @@ end =# subset_vec = zeros(Int, G.k) if G.init_rank == 1 - subset_vec = Int.(collect(1 : G.k)) + subset_vec = Int.(collect(1:G.k)) else CodingTheory._subset_unrank!(G.init_rank, UInt(G.n), subset_vec) end - inds = fill(-1, 3) + inds = fill(-1, 3) (inds, (subset_vec, 1, inds)) end @@ -62,7 +62,7 @@ end v, rank, inds = state if rank == G.len - return nothing + return nothing end rank += 1 @@ -77,41 +77,41 @@ end end if Base.rem(G.k - i, 2) != 0 if i == 1 - v[1] != (v[1] - 1) && _update_indices!(inds, v[1], v[1] - 1) + v[1] != (v[1] - 1) && _update_indices!(inds, v[1], v[1] - 1) v[1] = (v[1] - 1) - else - v[i - 1] != i && _update_indices!(inds,v[i - 1], i) - v[i - 1] = i + else + v[i-1] != i && _update_indices!(inds, v[i-1], i) + v[i-1] = i if i > 2 - v[i - 2] != (i - 1) && _update_indices!(inds,v[i - 2], i - 1) - v[i - 2] = (i - 1) + v[i-2] != (i - 1) && _update_indices!(inds, v[i-2], i - 1) + v[i-2] = (i - 1) end end - else + else if i == G.k if G.n != v[i] if (i > 1) - v[i - 1] != v[i] && _update_indices!(inds,v[i - 1], v[i]) - v[i - 1] = v[i] + v[i-1] != v[i] && _update_indices!(inds, v[i-1], v[i]) + v[i-1] = v[i] end - v[i] != (v[i] + 1) && _update_indices!(inds,v[i], v[i] + 1) + v[i] != (v[i] + 1) && _update_indices!(inds, v[i], v[i] + 1) v[i] = (v[i] + 1) else - v[i] != i && _update_indices!(inds, v[i], i) + v[i] != i && _update_indices!(inds, v[i], i) v[i] = i end else - if v[i + 1] != (v[i] + 1) + if v[i+1] != (v[i] + 1) if i > 1 - v[i - 1] != v[i] && _update_indices!(inds, v[i - 1], v[i]) - v[i - 1] = v[i] + v[i-1] != v[i] && _update_indices!(inds, v[i-1], v[i]) + v[i-1] = v[i] end - v[i] != (v[i] + 1) && _update_indices!(inds, v[i], v[i] + 1) + v[i] != (v[i] + 1) && _update_indices!(inds, v[i], v[i] + 1) v[i] = (v[i] + 1) else - v[i + 1] != v[i] && _update_indices!(inds, v[i + 1], v[i]) - v[i + 1] = v[i] - v[i] != i && _update_indices!(inds, v[i], i) + v[i+1] != v[i] && _update_indices!(inds, v[i+1], v[i]) + v[i+1] = v[i] + v[i] != i && _update_indices!(inds, v[i], i) v[i] = i end end @@ -139,7 +139,7 @@ function _update_indices!(indices::Vector{Int}, x::Int) indices[2] = x elseif indices[3] == -1 indices[3] = x - else + else error("No index positions remaining") end return nothing @@ -152,7 +152,7 @@ function _subset_rank(v::Vector{UInt}, k::UInt) =# r = UInt128(0) s = UInt128(1) - for i in k:-1:1 + for i = k:-1:1 r = r + extended_binomial(v[i], i) * s s = -s end @@ -175,25 +175,25 @@ end function _subset_unrank!(r::UInt128, n::UInt, T::Vector{Int}) # Based on Algorithm 2.12 in kreher1999combinatorial - r = r - 1 + r = r - 1 k = length(T) subset_size_str::String = "subset size k = $k must be smaller than the set size n = $n" k > n && throw(ArgumentError(subset_size_str)) - + x = 0 i = 0 - y = 0 + y = 0 x = n - for i::UInt in k:-1:1 + for i::UInt = k:-1:1 y = extended_binomial(x, i) while y > r - x = x - 1 - y = extended_binomial(x, i) - end + x = x - 1 + y = extended_binomial(x, i) + end T[i] = x + 1 r = extended_binomial(x + 1, i) - r - 1 - end + end end struct GrayCode @@ -209,12 +209,19 @@ end GrayCode(n::Int, k::Int; mutate::Bool = false) = GrayCode(n, k, Int[]; mutate = mutate) function GrayCode(n::Int, k::Int, prefix::Vector{Int}; mutate::Bool = false) - GrayCode(n, k, n - length(prefix), k - count(prefix .!= 0), prefix, - length(prefix), mutate) + GrayCode( + n, + k, + n - length(prefix), + k - count(prefix .!= 0), + prefix, + length(prefix), + mutate, + ) end Base.IteratorEltype(::GrayCode) = Base.HasEltype() -Base.eltype(::GrayCode) = Array{Int, 1} +Base.eltype(::GrayCode) = Array{Int,1} Base.IteratorSize(::GrayCode) = Base.HasLength() @inline function Base.length(G::GrayCode) if 0 <= G.ks <= G.ns @@ -223,17 +230,18 @@ Base.IteratorSize(::GrayCode) = Base.HasLength() 0 end end -Base.in(v::Vector{Int}, G::GrayCode) = length(v) == G.n && count(v .!= 0) == G.k && (view(v, 1:G.prefix_length) == G.prefix) +Base.in(v::Vector{Int}, G::GrayCode) = + length(v) == G.n && count(v .!= 0) == G.k && (view(v, 1:G.prefix_length) == G.prefix) @inline function Base.iterate(G::GrayCode) 0 <= G.ks <= G.ns || return nothing - g = [i <= G.ks ? 1 : 0 for i in 1:G.ns + 1] - τ = collect(2:G.ns + 2) + g = [i <= G.ks ? 1 : 0 for i = 1:(G.ns+1)] + τ = collect(2:(G.ns+2)) τ[1] = G.ks + 1 # to force stopping with returning the only valid vector when ks == 0 and ns > 0 iszero(G.ks) && (τ[1] = G.ns + 1;) - v = [G.prefix; g[end - 1:-1:1]] + v = [G.prefix; g[(end-1):-1:1]] ((G.mutate ? v : copy(v);), (g, τ, G.ks, v)) end @@ -253,25 +261,25 @@ end if t != 0 g[t] = g[t] == 0 ? 1 : 0 if t < G.ns + 1 - v[G.prefix_length + G.ns + 1 - t] = g[t] + v[G.prefix_length+G.ns+1-t] = g[t] end else - g[i - 1] = g[i - 1] == 0 ? 1 : 0 + g[i-1] = g[i-1] == 0 ? 1 : 0 if i - 1 < G.ns + 1 - v[G.prefix_length + G.ns + 2 - i] = g[i - 1] + v[G.prefix_length+G.ns+2-i] = g[i-1] end end t = t + 1 else if t != 1 - g[t - 1] = g[t - 1] == 0 ? 1 : 0 + g[t-1] = g[t-1] == 0 ? 1 : 0 if t - 1 < G.ns + 1 - v[G.prefix_length + G.ns + 2 - t] = g[t - 1] + v[G.prefix_length+G.ns+2-t] = g[t-1] end else - g[i - 1] = g[i - 1] == 0 ? 1 : 0 + g[i-1] = g[i-1] == 0 ? 1 : 0 if i - 1 < G.ns + 1 - v[G.prefix_length + G.ns + 2 - i] = g[i - 1] + v[G.prefix_length+G.ns+2-i] = g[i-1] end end t = t - 1 @@ -279,14 +287,14 @@ end g[i] = g[i] == 0 ? 1 : 0 if i < G.ns + 1 - v[G.prefix_length + G.ns + 1 - i] = g[i] + v[G.prefix_length+G.ns+1-i] = g[i] end if t == i - 1 || t == 0 t = t + 1 else - t = t - g[i - 1] - τ[i - 1] = τ[1] + t = t - g[i-1] + τ[i-1] = τ[1] if t == 0 τ[1] = i - 1 else diff --git a/src/tilings.jl b/src/tilings.jl index f863b6d3..15c27157 100644 --- a/src/tilings.jl +++ b/src/tilings.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # Hyperbolic +# Hyperbolic ############################# struct CoxeterMatrix <: AbstractMatrix{Int} @@ -50,7 +50,9 @@ function simplex_group(cox_mat::CoxeterMatrix) # relations = elem_type(f)[] for (i, g1) in enumerate(gen) for (j, g2) in enumerate(gen) - if j >= i append!(relations, [(g1 * g2)^cox_mat[i, j]]) end + if j >= i + append!(relations, [(g1 * g2)^cox_mat[i, j]]) + end end end g = f / GapObj(relations) @@ -87,10 +89,20 @@ Return the tetrahedron group with relations given by `orders`. """ function tetrahedron_group(orders::Vector{Int}) all(>=(0), orders) || throw(ArgumentError("Arguments must be non-negative.")) - f = Globals.FreeGroup(GapObj(["a", "b", "c", "d"]; recursive=true)) - g = f / GapObj([f.:1^2, f.:2^2, f.:3^2, f.:4^2, - (f.:1 * f.:2)^orders[1], (f.:1 * f.:3)^orders[2], (f.:1 * f.:4)^orders[3], - (f.:2 * f.:3)^orders[4], (f.:2 * f.:4)^orders[5], (f.:3 * f.:4)^orders[6]]) + f = Globals.FreeGroup(GapObj(["a", "b", "c", "d"]; recursive = true)) + g = + f / GapObj([ + f.:1^2, + f.:2^2, + f.:3^2, + f.:4^2, + (f.:1 * f.:2)^orders[1], + (f.:1 * f.:3)^orders[2], + (f.:1 * f.:4)^orders[3], + (f.:2 * f.:3)^orders[4], + (f.:2 * f.:4)^orders[5], + (f.:3 * f.:4)^orders[6], + ]) # BUG: call here is off, the dimension need not be saved but orders is not a CoxeterMatrix # return ReflectionGroup(g, [g.:1, g.:2, g.:3, g.:4], orders, 4) return ReflectionGroup(g, [g.:1, g.:2, g.:3, g.:4], CoxeterMatrix(4, orders)) @@ -107,7 +119,8 @@ o---o---o---o q r s ``` """ -q_r_s_group(q::Int, r::Int, s::Int) = simplex_group(CoxeterMatrix(4, [1, q, 2, 2, 1, r, 2, 1, s, 1])) +q_r_s_group(q::Int, r::Int, s::Int) = + simplex_group(CoxeterMatrix(4, [1, q, 2, 2, 1, r, 2, 1, s, 1])) """ star_tetrahedron_group(q::Int, r::Int, s::Int) @@ -123,7 +136,8 @@ o---o o ``` """ -star_tetrahedron_group(q::Int, r::Int, s::Int) = simplex_group(CoxeterMatrix(4, [1, q, r, s, 1, 2, 2, 1, 2, 1])) +star_tetrahedron_group(q::Int, r::Int, s::Int) = + simplex_group(CoxeterMatrix(4, [1, q, r, s, 1, 2, 2, 1, 2, 1])) """ cycle_tetrahedron_group(q::Int, r::Int, s::Int, t::Int) @@ -139,7 +153,8 @@ t| |r s ``` """ -cycle_tetrahedron_group(q::Int, r::Int, s::Int, t::Int) = simplex_group(CoxeterMatrix(4, [1, q, 2, t, 1, r, 2, 1, s, 1])) +cycle_tetrahedron_group(q::Int, r::Int, s::Int, t::Int) = + simplex_group(CoxeterMatrix(4, [1, q, 2, t, 1, r, 2, 1, s, 1])) """ normal_subgroups(g::ReflectionGroup, max_index::Int) @@ -163,12 +178,12 @@ function is_fixed_point_free(subgroup::GapObj, G::ReflectionGroup) h(g) = Globals.Image(hom, g) fixed_point = any(isone ∘ h, gens(G)) fixed_point && return false - + for (i, g1) in enumerate(gens(G)) for (j, g2) in enumerate(gens(G)) if j > i k = cox_mat(G)[i, j] - fixed_point = any(isone ∘ h, ((g1 * g2)^m for m in 1:k - 1)) + fixed_point = any(isone ∘ h, ((g1 * g2)^m for m = 1:(k-1))) fixed_point && return false end end @@ -193,15 +208,20 @@ end Return `true` if the group elements corresponding to `gen_idx` in `g/subgroup` are `k`-colorable; otherwise `false`. """ -function is_k_colorable(k::Int, gen_idx::AbstractVector{<: Int}, - translations::AbstractVector{<:GapObj}, subgroup::GapObj, G::ReflectionGroup) +function is_k_colorable( + k::Int, + gen_idx::AbstractVector{<: Int}, + translations::AbstractVector{<:GapObj}, + subgroup::GapObj, + G::ReflectionGroup, +) T_gens = Globals.List(Globals.GeneratorsOfGroup(subgroup)) Globals.Append(T_gens, gens(G)[gen_idx]) Globals.Append(T_gens, GapObj(translations)) subgroup_T = Globals.GroupByGenerators(T_gens) return Globals.Index(group(G), subgroup_T) ≤ k -end +end """ coset_intersection(gen_idx_A::Vector{Int}, gen_idx_B::Vector{Int}, subgroup::GapObj, g::ReflectionGroup) @@ -211,7 +231,13 @@ Return the intersection of the cosets of `g/subgroup` wrt `gen_idx_A` and wrt `g # Notes * This outputs a sparse matrix with rows indexing the `gen_idx_A` cosets and columns indexing the `gen_idx_B` cosets. """ -function coset_intersection(gen_idx_A::Vector{Int}, gen_idx_B::Vector{Int}, subgroup::GapObj, G::ReflectionGroup, transversal::Union{GapObj, Nothing} = nothing) +function coset_intersection( + gen_idx_A::Vector{Int}, + gen_idx_B::Vector{Int}, + subgroup::GapObj, + G::ReflectionGroup, + transversal::Union{GapObj,Nothing} = nothing, +) A, B = let S = Globals.List(Globals.GeneratorsOfGroup(subgroup)) map((gen_idx_A, gen_idx_B)) do idx diff --git a/src/trellis.jl b/src/trellis.jl index b2a36871..d474dcd2 100644 --- a/src/trellis.jl +++ b/src/trellis.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # General +# General ############################# mutable struct Vertex @@ -14,27 +14,27 @@ mutable struct Vertex next::Int64 value::Float64 edge_loc::Int64 - polynomial::Union{ZZMPolyRingElem, AbsSimpleNumFieldElem, Missing} + polynomial::Union{ZZMPolyRingElem,AbsSimpleNumFieldElem,Missing} end # could redo this for classical to remove sign # for a trellis with 10 million edges, this would save 10 MB # to do this, make EdgeC and EdgeQ and change all following functions to Union both mutable struct Edge - label::Union{FqFieldElem, fpFieldElem, fpMatrix, FqMatrix} + label::Union{FqFieldElem,fpFieldElem,fpMatrix,FqMatrix} weight::Float64 out_vertex::Int64 - sign::Union{Missing, zzModRingElem} + sign::Union{Missing,zzModRingElem} end mutable struct Trellis vertices::Vector{Vector{Vertex}} edges::Vector{Vector{Vector{Edge}}} - code::T where T <: AbstractCode + code::T where {T<:AbstractCode} # complete weight enumerator - CWE::Union{WeightEnumerator, Missing} + CWE::Union{WeightEnumerator,Missing} # shifted::Bool - shift::Union{FqMatrix, fpMatrix} + shift::Union{FqMatrix,fpMatrix} end """ @@ -60,8 +60,12 @@ code. is_shifted(T::Trellis) = !iszero(T.shift) function ==(a::Vertex, b::Vertex) - return a.label == b.label && a.prev == b.prev && a.next == b.next && - a.value == b.value && a.edge_loc == b.edge_loc && a.polynomial == b.polynomial + return a.label == b.label && + a.prev == b.prev && + a.next == b.next && + a.value == b.value && + a.edge_loc == b.edge_loc && + a.polynomial == b.polynomial end function ==(a::Vector{Vertex}, b::Vector{Vertex}) @@ -69,7 +73,7 @@ function ==(a::Vector{Vertex}, b::Vector{Vertex}) return false end - for i in 1:length(a) + for i = 1:length(a) if a[i] != b[i] return false end @@ -86,7 +90,7 @@ function ==(a::Vector{Edge}, b::Vector{Edge}) return false end - for i in 1:length(a) + for i = 1:length(a) if a[i] != b[i] return false end @@ -100,7 +104,7 @@ function ==(a::Vector{Vector{Edge}}, b::Vector{Vector{Edge}}) return false end - for i in 1:length(a) + for i = 1:length(a) if a[i] != b[i] return false end @@ -114,7 +118,7 @@ function ==(a::Vector{Vector{Vector{Edge}}}, b::Vector{Vector{Vector{Edge}}}) return false end - for i in 1:length(a) + for i = 1:length(a) if a[i] != b[i] return false end @@ -127,7 +131,7 @@ function is_isomorphic(V1::Vector{Vector{Vertex}}, V2::Vector{Vector{Vertex}}) if length(V1) != length(V2) return false else - for i in 1:length(V1) + for i = 1:length(V1) if length(V1[i]) != length(V2[i]) return false end @@ -140,7 +144,7 @@ function is_isomorphic(E1::Vector{Vector{Vector{Edge}}}, E2::Vector{Vector{Vecto if length(E1) != length(E2) return false else - for i in 1:length(E1) + for i = 1:length(E1) if length(E1[i]) != length(E2[i]) || length(E1[i][1]) != length(E2[i][1]) return false end @@ -149,8 +153,12 @@ function is_isomorphic(E1::Vector{Vector{Vector{Edge}}}, E2::Vector{Vector{Vecto end end -function is_isomorphic(V1::Vector{Vector{Vertex}}, E1::Vector{Vector{Vector{Edge}}}, - V2::Vector{Vector{Vertex}}, E2::Vector{Vector{Vector{Edge}}}) +function is_isomorphic( + V1::Vector{Vector{Vertex}}, + E1::Vector{Vector{Vector{Edge}}}, + V2::Vector{Vector{Vertex}}, + E2::Vector{Vector{Vector{Edge}}}, +) iso_V = is_isomorphic(V1, V2) if !iso_V @@ -159,14 +167,18 @@ function is_isomorphic(V1::Vector{Vector{Vertex}}, E1::Vector{Vector{Vector{Edge return is_isomorphic(E1, E2) end -function is_isomorphic(V1::Vector{Vector{Vertex}}, V2::Vector{Vector{Vertex}}, - E1::Vector{Vector{Vector{Edge}}}, E2::Vector{Vector{Vector{Edge}}}) +function is_isomorphic( + V1::Vector{Vector{Vertex}}, + V2::Vector{Vector{Vertex}}, + E1::Vector{Vector{Vector{Edge}}}, + E2::Vector{Vector{Vector{Edge}}}, +) return is_isomorphic(V1, E1, V2, E2) end # provide "sorted" option -function is_equal(V1::Vector{Vector{Vertex}}, V2::Vector{Vector{Vertex}}, verbose=false) +function is_equal(V1::Vector{Vector{Vertex}}, V2::Vector{Vector{Vertex}}, verbose = false) is_iso = is_isomorphic(V1, V2) verbose && println("V1 and V2 are isomorphic.") @@ -202,9 +214,14 @@ function ==(V1::Vector{Vector{Vertex}}, V2::Vector{Vector{Vertex}}) return is_equal(V1, V2, false) end -function is_equal(V1::Vector{Vector{Vertex}}, E1::Vector{Vector{Vector{Edge}}}, - V2::Vector{Vector{Vertex}}, E2::Vector{Vector{Vector{Edge}}}, - verbose=false, rhs_sorted=false) +function is_equal( + V1::Vector{Vector{Vertex}}, + E1::Vector{Vector{Vector{Edge}}}, + V2::Vector{Vector{Vertex}}, + E2::Vector{Vector{Vector{Edge}}}, + verbose = false, + rhs_sorted = false, +) is_iso = is_isomorphic(V1, E1, V2, E2) verbose && println("V1 and V2 and E1 and E2 are isomorphic, respectively.") @@ -253,18 +270,46 @@ function is_equal(V1::Vector{Vector{Vertex}}, E1::Vector{Vector{Vector{Edge}}}, else if i != 1 verbose && println("Checking for equality in corresponding edges") - for (k, e1) in enumerate(E1[i - 1][j]) + for (k, e1) in enumerate(E1[i-1][j]) found_e = false - for (l, e2) in enumerate(E2[i - 1][v_loc]) - if e1.label == e2.label && e1.weight == e2.weight && V1[i - 1][e1.out_vertex].label == V2[i - 1][e2.out_vertex].label + for (l, e2) in enumerate(E2[i-1][v_loc]) + if e1.label == e2.label && + e1.weight == e2.weight && + V1[i-1][e1.out_vertex].label == V2[i-1][e2.out_vertex].label found_e = true - verbose && println("E1[", i - 1, "][", j, "][", k, "] = E2[", i - 1, "][", v_loc, "][", l, "]") + verbose && println( + "E1[", + i - 1, + "][", + j, + "][", + k, + "] = E2[", + i - 1, + "][", + v_loc, + "][", + l, + "]", + ) break end end if !found_e - verbose && println("Edge E1[", i - 1, "][", j, "][", k, "] not found in E2[", i - 1, "][", v_loc, "]") + verbose && println( + "Edge E1[", + i - 1, + "][", + j, + "][", + k, + "] not found in E2[", + i - 1, + "][", + v_loc, + "]", + ) return false end end @@ -275,18 +320,23 @@ function is_equal(V1::Vector{Vector{Vertex}}, E1::Vector{Vector{Vector{Edge}}}, return true end -function is_equal(V1::Vector{Vector{Vertex}}, V2::Vector{Vector{Vertex}}, - E1::Vector{Vector{Vector{Edge}}}, E2::Vector{Vector{Vector{Edge}}}, - verbose=false, rhs_sorted=false) +function is_equal( + V1::Vector{Vector{Vertex}}, + V2::Vector{Vector{Vertex}}, + E1::Vector{Vector{Vector{Edge}}}, + E2::Vector{Vector{Vector{Edge}}}, + verbose = false, + rhs_sorted = false, +) return is_equal(V1, E1, V2, E2, verbose, rhs_sorted) end -function _sort_by_left_index(A::Union{FqMatrix, fpMatrix}) +function _sort_by_left_index(A::Union{FqMatrix,fpMatrix}) nr, nc = size(A) arr = [] - for r in 1:nr - for c in 1:nc + for r = 1:nr + for c = 1:nc if !iszero(A[r, c]) push!(arr, [c, A[r:r, :]]) break @@ -299,14 +349,14 @@ function _sort_by_left_index(A::Union{FqMatrix, fpMatrix}) # println("sort2: $arr") # vcat is faster and cheaper than the following # return A[[arr2[i][2] for i in 1:num_rows], :] - return vcat([arr[i][2] for i in 1:nr]...) + return vcat([arr[i][2] for i = 1:nr]...) end -function _sort_by_right_index(A::Union{FqMatrix, fpMatrix}) +function _sort_by_right_index(A::Union{FqMatrix,fpMatrix}) nr, nc = size(A) arr = [] - for r in 1:nr - for c in nc:-1:1 + for r = 1:nr + for c = nc:-1:1 if !iszero(A[r, c]) push!(arr, [c, A[r, :]]) break @@ -315,20 +365,20 @@ function _sort_by_right_index(A::Union{FqMatrix, fpMatrix}) # push!(arr, [1, A[r, :]]) end sort!(arr, by = x -> x[1]) #, rev=true - return vcat([arr[i][2] for i in 1:nr]...) + return vcat([arr[i][2] for i = 1:nr]...) end -function _left_right_indices(A::Union{FqMatrix, fpMatrix}) +function _left_right_indices(A::Union{FqMatrix,fpMatrix}) # iseven(size(A, 2)) || error("Vectors in leftrightindices must have even length.") # n = div(size(A, 2), 2) -#take quadratic only here + #take quadratic only here nr, nc = size(A) left = Vector{Int64}() right = Vector{Int64}() - for r in 1:nr - for c in 1:nc + for r = 1:nr + for c = 1:nc if !iszero(A[r, c]) push!(left, c) break @@ -336,8 +386,8 @@ function _left_right_indices(A::Union{FqMatrix, fpMatrix}) end end - for r in 1:nr - for c in nc:-1:1 + for r = 1:nr + for c = nc:-1:1 if !iszero(A[r, c]) push!(right, c) break @@ -347,12 +397,12 @@ function _left_right_indices(A::Union{FqMatrix, fpMatrix}) return left, right end -function _find_active(A::Union{FqMatrix, fpMatrix}, edges::Bool = false) +function _find_active(A::Union{FqMatrix,fpMatrix}, edges::Bool = false) # need to make sure quadratic extension nr, nc = size(A) - left_right = [[0, 0] for _ in 1:nr] - for r in 1:nr - for c in 1:nc + left_right = [[0, 0] for _ = 1:nr] + for r = 1:nr + for c = 1:nc if !iszero(A[r, c]) left_right[r][1] = c break @@ -360,8 +410,8 @@ function _find_active(A::Union{FqMatrix, fpMatrix}, edges::Bool = false) end end - for r in 1:nr - for c in nc:-1:1 + for r = 1:nr + for c = nc:-1:1 if !iszero(A[r, c]) left_right[r][2] = c break @@ -373,9 +423,9 @@ function _find_active(A::Union{FqMatrix, fpMatrix}, edges::Bool = false) active = Vector{Vector{Int64}}() if edges - for c in 1:nc + for c = 1:nc arr_c = Vector{Int64}() - for r in 1:nr + for r = 1:nr # c == 5 && println(c, ", ", r, ", ", left_right[r]) if left_right[r][1] <= c <= left_right[r][2] # c == 5 && println("added") @@ -387,9 +437,9 @@ function _find_active(A::Union{FqMatrix, fpMatrix}, edges::Bool = false) end end else - for c in 1:nc + for c = 1:nc arr_c = Vector{Int64}() - for r in 1:nr + for r = 1:nr if left_right[r][1] <= c < left_right[r][2] push!(arr_c, r) end @@ -404,10 +454,16 @@ function _find_active(A::Union{FqMatrix, fpMatrix}, edges::Bool = false) end # finds all elements of B which have zero symplectic inner product with all of A -function _kernel_inner_prod(A::Union{FqMatrix, fpMatrix}, B::Union{FqMatrix, fpMatrix}, - inner_prod::String="Euclidean", return_ker::Bool=false) - - inner_prod ∈ ["Euclidean", "symplectic"] || error("Unsupported inner product type in _kernel_inner_prod; expected: `Euclidean`, `symplectic`, received: $inner_prod.") +function _kernel_inner_prod( + A::Union{FqMatrix,fpMatrix}, + B::Union{FqMatrix,fpMatrix}, + inner_prod::String = "Euclidean", + return_ker::Bool = false, +) + + inner_prod ∈ ["Euclidean", "symplectic"] || error( + "Unsupported inner product type in _kernel_inner_prod; expected: `Euclidean`, `symplectic`, received: $inner_prod.", + ) size(A, 2) == size(B, 2) || error("Length mismatch in _kernel_inner_prod.") if inner_prod == "symplectic" iseven(size(A, 2)) || error("Vectors in symplectic_kernel must have even length.") @@ -423,8 +479,8 @@ function _kernel_inner_prod(A::Union{FqMatrix, fpMatrix}, B::Union{FqMatrix, fpM if inner_prod == "symplectic" if return_ker ker = [] - for rb in 1:nr_B - for ra in 1:nr_A + for rb = 1:nr_B + for ra = 1:nr_A @views if !iszero(symplectic_inner_product(A[ra, :], B[rb, :])) push!(ker, B[rb, :]) break @@ -433,12 +489,12 @@ function _kernel_inner_prod(A::Union{FqMatrix, fpMatrix}, B::Union{FqMatrix, fpM end return length(ker), reduce(vcat, ker) else - A_Euc = hcat(A[:, half_nc_A + 1:end], -A[:, 1:half_nc_A]) + A_Euc = hcat(A[:, (half_nc_A+1):end], -A[:, 1:half_nc_A]) prod = A_Euc * transpose(B) iszero(prod) && return 0 nc_prod = ncols(prod) count = 0 - for i in 1:nc_prod + for i = 1:nc_prod if !iszero(prod[:, i]) count += 1 end @@ -448,10 +504,10 @@ function _kernel_inner_prod(A::Union{FqMatrix, fpMatrix}, B::Union{FqMatrix, fpM else if return_ker ker = [] - for rb in 1:nr_B - for ra in 1:nr_A - @views if !iszero(sum([A[ra, i] * B[rb, i] for i in 1:ncols(A)])) - # @views if !iszero(A[ra, :] ⋅ B[rb, :]) + for rb = 1:nr_B + for ra = 1:nr_A + @views if !iszero(sum([A[ra, i] * B[rb, i] for i = 1:ncols(A)])) + # @views if !iszero(A[ra, :] ⋅ B[rb, :]) push!(ker, B[rb, :]) break end @@ -463,7 +519,7 @@ function _kernel_inner_prod(A::Union{FqMatrix, fpMatrix}, B::Union{FqMatrix, fpM iszero(prod) && return 0 nc_prod = ncols(prod) count = 0 - for i in 1:nc_prod + for i = 1:nc_prod if !iszero(prod[:, i]) count += 1 end @@ -473,16 +529,16 @@ function _kernel_inner_prod(A::Union{FqMatrix, fpMatrix}, B::Union{FqMatrix, fpM end end -function _past_future(A::Union{FqMatrix, fpMatrix}) +function _past_future(A::Union{FqMatrix,fpMatrix}) nr, nc = size(A) past = zeros(Int64, nc + 1) future = zeros(Int64, nc + 1) left, right = _left_right_indices(A) past[1] = 0 future[1] = nr - for i in 2:nc + 1 - past[i] = length(right[right .<= i - 1]) - future[i] = length(left[left .> i - 1]) + for i = 2:(nc+1) + past[i] = length(right[right .<= i-1]) + future[i] = length(left[left .> i-1]) end return past, future end @@ -506,7 +562,8 @@ function load_balanced_code(profile::Vector{Int64}) end function load_balanced_code(profiles::Vector{Vector{Int64}}) - length(profiles) == 4 || error("Expected a length 4 profile vector. Pass in all or just the edges.") + length(profiles) == 4 || + error("Expected a length 4 profile vector. Pass in all or just the edges.") return load_balanced_code(profiles[2]) end @@ -516,10 +573,10 @@ end Return the trellis oriented form of the matrix `A` assuming the row space is linear. """ -function trellis_oriented_form_linear(A::Union{FqMatrix, fpMatrix}) +function trellis_oriented_form_linear(A::Union{FqMatrix,fpMatrix}) A = _sort_by_left_index(A) nc = ncols(A) - for c in 1:nc + for c = 1:nc left, right = _left_right_indices(A) rows = findall(x -> x == c, left) if length(rows) == 1 @@ -543,7 +600,7 @@ function trellis_oriented_form_linear(A::Union{FqMatrix, fpMatrix}) #take first row, normalize to 1 @views A[rows[1]:rows[1], :] *= inv(A[rows[1], c]) # for rest of them, remove - for i in 2:length(rows) + for i = 2:length(rows) @views A[rows[i]:rows[i], :] -= A[rows[i], c] * A[rows[1]:rows[1], :] end end @@ -551,7 +608,7 @@ function trellis_oriented_form_linear(A::Union{FqMatrix, fpMatrix}) A = _sort_by_left_index(A) left, right = _left_right_indices(A) - for c in nc:-1:1 + for c = nc:-1:1 rows = findall(x -> x == c, right) if length(rows) == 1 @views A[rows[1]:rows[1], :] *= inv(A[rows[1], c]) @@ -575,7 +632,7 @@ function trellis_oriented_form_linear(A::Union{FqMatrix, fpMatrix}) #take last row, normalize to 1 @views A[rows[end]:rows[end], :] *= inv(A[rows[end], c]) # for rest of them, remove - for i in length(rows) - 1:-1:1 + for i = (length(rows)-1):-1:1 @views A[rows[i]:rows[i], :] -= A[rows[i], c] * A[rows[end]:rows[end], :] end end @@ -596,15 +653,17 @@ additive. # Note * So far this is only implemented for quadratic extensions over a prime subfield, i.e., `GF(p^2)`. """ -function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) +function trellis_oriented_form_additive(A::Union{FqMatrix,fpMatrix}) E = base_ring(A) - degree(E) == 2 || error("So far this is only implemented for quadratic extensions over a prime subfield.") + degree(E) == 2 || error( + "So far this is only implemented for quadratic extensions over a prime subfield.", + ) A = _sort_by_left_index(A) nc = ncols(A) # display(A) # println(" ") - @views for c in 1:nc + @views for c = 1:nc left, right = _left_right_indices(A) rows = findall(x -> x == c, left) if length(rows) == 1 @@ -632,7 +691,10 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) # println(Z_edges) # println(mixed_edges) - if length(X_edges) <= 1 && length(Z_edges) <= 1 && length(mixed_edges) <= 1 && (length(X_edges) + length(Z_edges) + length(mixed_edges)) <= 2 + if length(X_edges) <= 1 && + length(Z_edges) <= 1 && + length(mixed_edges) <= 1 && + (length(X_edges) + length(Z_edges) + length(mixed_edges)) <= 2 continue else X_pivot = false @@ -645,7 +707,7 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) # display(A) # println(" ") # no problems here if this is only length 1 - for i in 2:length(X_edges) + for i = 2:length(X_edges) A[X_edges[i][1], :] -= E(coeff(X_edges[i][2], 0)) * A[row, :] end end @@ -657,38 +719,54 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) # display(A) # println(" ") # no problems here if this is only length 1 - for i in 2:length(Z_edges) + for i = 2:length(Z_edges) A[Z_edges[i][1], :] -= E(coeff(Z_edges[i][2], 1)) * A[row, :] end end if !isempty(mixed_edges) if X_pivot && Z_pivot - for i in 1:length(mixed_edges) - A[mixed_edges[i][1], :] -= E(coeff(mixed_edges[i][2], 0)) * A[X_edges[1][1], :] + E(coeff(mixed_edges[i][2], 1)) * A[Z_edges[1][1], :] + for i = 1:length(mixed_edges) + A[mixed_edges[i][1], :] -= + E(coeff(mixed_edges[i][2], 0)) * A[X_edges[1][1], :] + + E(coeff(mixed_edges[i][2], 1)) * A[Z_edges[1][1], :] end elseif X_pivot - A[mixed_edges[1][1], :] -= E(coeff(mixed_edges[1][2], 0)) * A[X_edges[1][1], :] + A[mixed_edges[1][1], :] -= + E(coeff(mixed_edges[1][2], 0)) * A[X_edges[1][1], :] # no problems here if this is only length 1 - for i in 2:length(mixed_edges) - A[mixed_edges[i][1], :] -= E(coeff(mixed_edges[i][2], 0)) * A[X_edges[1][1], :] + E(coeff(mixed_edges[i][2], 1)) * A[mixed_edges[1][1], :] + for i = 2:length(mixed_edges) + A[mixed_edges[i][1], :] -= + E(coeff(mixed_edges[i][2], 0)) * A[X_edges[1][1], :] + + E(coeff(mixed_edges[i][2], 1)) * A[mixed_edges[1][1], :] end elseif Z_pivot - A[mixed_edges[1][1], :] -= E(coeff(mixed_edges[1][2], 1)) * A[Z_edges[1][1], :] + A[mixed_edges[1][1], :] -= + E(coeff(mixed_edges[1][2], 1)) * A[Z_edges[1][1], :] # no problems here if this is only length 1 - for i in 2:length(mixed_edges) - A[mixed_edges[i][1], :] -= E(coeff(mixed_edges[i][2], 0)) * A[mixed_edges[1][1], :] + E(coeff(mixed_edges[i][2], 1)) * A[Z_edges[1][1], :] + for i = 2:length(mixed_edges) + A[mixed_edges[i][1], :] -= + E(coeff(mixed_edges[i][2], 0)) * A[mixed_edges[1][1], :] + + E(coeff(mixed_edges[i][2], 1)) * A[Z_edges[1][1], :] end else A[mixed_edges[1][1], :] *= inv(E(coeff(mixed_edges[1][2], 0))) if length(mixed_edges) > 1 - A[mixed_edges[2][1], :] -= E(coeff(mixed_edges[2][2], 0)) * A[mixed_edges[1][1], :] - A[mixed_edges[2][1], :] *= inv(E(coeff(A[mixed_edges[2][1], c], 1))) + A[mixed_edges[2][1], :] -= + E(coeff(mixed_edges[2][2], 0)) * A[mixed_edges[1][1], :] + A[mixed_edges[2][1], :] *= + inv(E(coeff(A[mixed_edges[2][1], c], 1))) if length(mixed_edges) > 2 - A[mixed_edges[3][1], :] -= E(coeff(mixed_edges[3][2], 1)) * A[mixed_edges[2][1], :] - A[mixed_edges[3][1], :] *= inv(E(coeff(A[mixed_edges[3][1], c], 0))) + A[mixed_edges[3][1], :] -= + E(coeff(mixed_edges[3][2], 1)) * A[mixed_edges[2][1], :] + A[mixed_edges[3][1], :] *= + inv(E(coeff(A[mixed_edges[3][1], c], 0))) # no problems here if this is only length 3 - for i in 3:length(mixed_edges) - A[mixed_edges[i][1], :] -= E(coeff(mixed_edges[i][2], 0)) * A[mixed_edges[3][1], :] + E(coeff(mixed_edges[i][2], 1)) * A[mixed_edges[2][1], :] + for i = 3:length(mixed_edges) + A[mixed_edges[i][1], :] -= + E(coeff(mixed_edges[i][2], 0)) * + A[mixed_edges[3][1], :] + + E(coeff(mixed_edges[i][2], 1)) * + A[mixed_edges[2][1], :] end end end @@ -706,7 +784,7 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) # display(A) # println(" ") - @views for c in nc:-1:1 + @views for c = nc:-1:1 rows = findall(x -> x == c, right) if length(rows) == 1 if !iszero(coeff(A[rows[1], c], 0)) && !iszero(coeff(A[rows[1], c], 1)) @@ -730,7 +808,10 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) end end - if length(X_edges) <= 1 && length(Z_edges) <= 1 && length(mixed_edges) <= 1 && (length(X_edges) + length(Z_edges) + length(mixed_edges)) <= 2 + if length(X_edges) <= 1 && + length(Z_edges) <= 1 && + length(mixed_edges) <= 1 && + (length(X_edges) + length(Z_edges) + length(mixed_edges)) <= 2 continue else # need to determine if X and/or Z pivots are below Y and if not, use Y to @@ -739,24 +820,26 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) # can only set one coefficient of a + bω to 1 in additive, do a row, Y = mixed_edges[end] A[row, :] *= inv(E(coeff(Y, 0))) - for i in length(mixed_edges) - 1:-1:1 + for i = (length(mixed_edges)-1):-1:1 # can't use a + bω to eliminate a c + dω, so first use 1 + b'ω to eliminate c - A[mixed_edges[i][1], :] -= E(coeff(mixed_edges[i][2], 0)) * A[row, :] + A[mixed_edges[i][1], :] -= + E(coeff(mixed_edges[i][2], 0)) * A[row, :] # now turn d to 1 - these are all pure Z's now and some could be pivots if !iszero(coeff(A[mixed_edges[i][1], c], 1)) - A[mixed_edges[i][1], :] *= inv(E(coeff(A[mixed_edges[i][1], c], 1))) + A[mixed_edges[i][1], :] *= + inv(E(coeff(A[mixed_edges[i][1], c], 1))) append!(Z_edges, (mixed_edges[i][1], A[mixed_edges[i][1], c])) end end mixed_edges = [mixed_edges[end]] - sort!(Z_edges, by=x->x[1]) + sort!(Z_edges, by = x->x[1]) end if !isempty(X_edges) row, X = X_edges[end] A[row, :] *= inv(E(coeff(X, 0))) # no problems here if this is only length 1 - for i in length(X_edges) - 1:-1:1 + for i = (length(X_edges)-1):-1:1 A[X_edges[i][1], :] -= E(coeff(X_edges[i][2], 0)) * A[row, :] end X_edges = [X_edges[end]] @@ -765,7 +848,7 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) row, Z = Z_edges[end] A[row, :] *= inv(E(coeff(Z, 1))) # no problems here if this is only length 1 - for i in length(Z_edges) - 1:-1:1 + for i = (length(Z_edges)-1):-1:1 A[Z_edges[i][1], :] -= E(coeff(Z_edges[i][2], 1)) * A[row, :] end Z_edges = [Z_edges[end]] @@ -778,17 +861,21 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) # Y edge is top, apply both X and Z pivots to remove it # pivot to be removed is of the form 1 + bω A[mixed_edges[1][1], :] -= A[X_edges[1][1], :] - A[mixed_edges[1][1], :] -= E(coeff(A[mixed_edges[1][1], c], 1)) * A[Z_edges[1][1], :] + A[mixed_edges[1][1], :] -= + E(coeff(A[mixed_edges[1][1], c], 1)) * A[Z_edges[1][1], :] elseif loc == 2 # X edge is top, apply both Y and Z pivots to remove it A[X_edges[1][1], :] -= A[mixed_edges[1][1], :] # pivot to be remove is now of the form bω coming from the Y - A[X_edges[1][1], :] -= E(coeff(A[X_edges[1][1], c], 1)) * A[Z_edges[1][1], :] + A[X_edges[1][1], :] -= + E(coeff(A[X_edges[1][1], c], 1)) * A[Z_edges[1][1], :] else # Z edge is top, apply both Y and X pivots to remove it - A[Z_edges[1][1], :] -= inv(E(coeff(mixed_edges[1][2], 1))) * A[mixed_edges[1][1], :] + A[Z_edges[1][1], :] -= + inv(E(coeff(mixed_edges[1][2], 1))) * A[mixed_edges[1][1], :] # pivot to be remove is now of the form b^{-1} - A[Z_edges[1][1], :] -= E(coeff(A[Z_edges[1][1], c], 0)) * A[X_edges[1][1], :] + A[Z_edges[1][1], :] -= + E(coeff(A[Z_edges[1][1], c], 0)) * A[X_edges[1][1], :] end end end @@ -799,13 +886,19 @@ function trellis_oriented_form_additive(A::Union{FqMatrix, fpMatrix}) end # need to brainstorem parallel edges -function trellis_profiles(wrt_V::Union{FqMatrix, fpMatrix}, wrt_E::Union{FqMatrix, fpMatrix}, - boundaries::Union{Vector{Int64}, Missing}, inner_prod::String="Euclidean") +function trellis_profiles( + wrt_V::Union{FqMatrix,fpMatrix}, + wrt_E::Union{FqMatrix,fpMatrix}, + boundaries::Union{Vector{Int64},Missing}, + inner_prod::String = "Euclidean", +) - inner_prod ∈ ["Euclidean", "symplectic"] || error("Unsupported inner product type in _trellisprofiles; expected: `Euclidean`, `symplectic`, received: $inner_prod.") + inner_prod ∈ ["Euclidean", "symplectic"] || error( + "Unsupported inner product type in _trellisprofiles; expected: `Euclidean`, `symplectic`, received: $inner_prod.", + ) if ismissing(boundaries) - bds = [1:size(wrt_V, 2) + 1...] + bds = [1:(size(wrt_V, 2)+1)...] else bds = deepcopy(boundaries) if 0 ∈ bds @@ -831,7 +924,7 @@ function trellis_profiles(wrt_V::Union{FqMatrix, fpMatrix}, wrt_E::Union{FqMatri dim_ker = 0 p = Int64(characteristic(base_ring(wrt_V))) - for i in 1:n + 1 + for i = 1:(n+1) state_profile[i] = p^(size(wrt_V, 1) - past[i] - future[i] - dim_ker) end @@ -839,27 +932,33 @@ function trellis_profiles(wrt_V::Union{FqMatrix, fpMatrix}, wrt_E::Union{FqMatri past, future = _past_future(wrt_E) past = past[bds] future = future[bds] - for i in 1:n + for i = 1:n dim_parallel = 0 - branch_profile[i] = p^(size(wrt_E, 1) - past[i] - future[i + 1] - dim_ker - dim_parallel) - in_degrees[i] = div(branch_profile[i], state_profile[i + 1]) + branch_profile[i] = + p^(size(wrt_E, 1) - past[i] - future[i+1] - dim_ker - dim_parallel) + in_degrees[i] = div(branch_profile[i], state_profile[i+1]) out_degrees[i] = div(branch_profile[i], state_profile[i]) end return [state_profile, branch_profile, in_degrees, out_degrees] end ############################# - # Classical +# Classical ############################# # TODO: handle lookup table better - temporarily skipping # TODO: remove dictionaries, iterate once to find left, once for right # keep first bipartite structure and shift it as a coset to find the next ones - fix for sectionalization -function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=true, - verbose::Bool=false) +function syndrome_trellis( + C::AbstractCode, + type::String = "primal", + sect::Bool = true, + verbose::Bool = false, +) - (typeof(C) <: AbstractLinearCode || typeof(C) <: AbstractStabilizerCode) || - error("Syndrome trellises are so far only implemented for linear and stabilizer codes.") + (typeof(C) <: AbstractLinearCode || typeof(C) <: AbstractStabilizerCode) || error( + "Syndrome trellises are so far only implemented for linear and stabilizer codes.", + ) if typeof(C) <: AbstractLinearCode wrt_V = trellis_oriented_form_linear(parity_check_matrix(C)) @@ -940,18 +1039,21 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru end p = Int64(characteristic(K)) n = length(C) - V = Vector{Vertex}[Vertex[] for _ in 1:length(bds)] - Threads.@threads for i in 1:length(profiles[1]) - V[i] = [Vertex(999, 0, 0, 0.0, 0, missing) for _ in 1:profiles[1][i]] + V = Vector{Vertex}[Vertex[] for _ = 1:length(bds)] + Threads.@threads for i = 1:length(profiles[1]) + V[i] = [Vertex(999, 0, 0, 0.0, 0, missing) for _ = 1:profiles[1][i]] end V[1] = [Vertex(0, 0, 0, 0.0, 0, missing)] V[end] = [Vertex(0, 0, 0, 0.0, 0, missing)] verbose && println("Vertex preallocation completed.") - E = Vector{Vector{Edge}}[[Edge[]] for _ in 1:length(profiles[3])] - Threads.@threads for i in 1:length(profiles[3]) + E = Vector{Vector{Edge}}[[Edge[]] for _ = 1:length(profiles[3])] + Threads.@threads for i = 1:length(profiles[3]) # the j-th element of Ei is going to be all of the edges going into Vi[j] - E[i] = [[Edge(K(0), 0.0, 0, missing) for j in 1:profiles[3][i]] for _ in 1:profiles[1][i + 1]] + E[i] = [ + [Edge(K(0), 0.0, 0, missing) for j = 1:profiles[3][i]] for + _ = 1:profiles[1][i+1] + ] end verbose && println("Edge preallocation completed.") @@ -959,25 +1061,25 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru bio = BigInt(1) syn_len = size(wrt_V, 1) active = _find_active(wrt_V) - active = active[bds[2:end - 1]] - Threads.@threads for i in 2:length(bds) - 1 + active = active[bds[2:(end-1)]] + Threads.@threads for i = 2:(length(bds)-1) Vi_size = profiles[1][i] - for num in 0:Vi_size - 1 - bin = reverse(digits(num, base=2, pad=length(active[i - 1]))) + for num = 0:(Vi_size-1) + bin = reverse(digits(num, base = 2, pad = length(active[i-1]))) temp_label = zeros(Int64, syn_len) loc = 1 - for j in active[i - 1] + for j in active[i-1] temp_label[j] = bin[loc] loc += 1 end cur_label = biz - for (shift, val) in enumerate(reverse(temp_label, dims=1)) + for (shift, val) in enumerate(reverse(temp_label, dims = 1)) if val == 1 cur_label += bio << (shift - 1) end end - V[i][num + 1].label = cur_label + V[i][num+1].label = cur_label end end verbose && println("Vertex construction completed.") @@ -989,13 +1091,16 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru active_temp = active else active_temp = Vector{Vector{Int64}}() - for i in 1:length(bds) - 1 + for i = 1:(length(bds)-1) # temp = Vector{Int64}() # for j in bds[i] + 1:bds[i + 1] # append!(temp, active[j]) # end # push!(active_temp, sort!(unique!(temp))) - push!(active_temp, sort!(unique!(vcat([active[j] for j in bds[i] + 1:bds[i + 1]]...)))) + push!( + active_temp, + sort!(unique!(vcat([active[j] for j = (bds[i]+1):bds[i+1]]...))), + ) end end @@ -1003,18 +1108,20 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru H = _Flint_matrix_to_Julia_int_matrix(wrt_V) else sym_wrt_V = quadratic_to_symplectic(wrt_V) - H = _Flint_matrix_to_Julia_int_matrix(hcat(sym_wrt_V[:, n + 1:end], -sym_wrt_V[:, 1:n])) + H = _Flint_matrix_to_Julia_int_matrix( + hcat(sym_wrt_V[:, (n+1):end], -sym_wrt_V[:, 1:n]), + ) end # Threads.@threads - for i in length(bds) - 1:-1:1 + for i = (length(bds)-1):-1:1 verbose && println("Starting E[$i]") # seclen = bds[i + 1] - bds[i] valid_edges = Vector{FqMatrix}() - edge_contrib = Dict{FqMatrix, Vector{Int64}}() - contrib_edge = Dict{Vector{Int64}, FqMatrix}() + edge_contrib = Dict{FqMatrix,Vector{Int64}}() + contrib_edge = Dict{Vector{Int64},FqMatrix}() for a in active_temp[i] - temp = wrt_E[a, bds[i] + 1:bds[i + 1]] + temp = wrt_E[a, (bds[i]+1):bds[i+1]] if !iszero(temp) push!(valid_edges, temp) end @@ -1023,9 +1130,10 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru # i == 1 && display(valid_edges) # may need to use Oscar here now that the import is switched - for iter in Nemo.AbstractAlgebra.ProductIterator(collect(0:p - 1), length(valid_edges)) + for iter in + Nemo.AbstractAlgebra.ProductIterator(collect(0:(p-1)), length(valid_edges)) e = K(iter[1]) * valid_edges[1] - for r in 2:length(valid_edges) + for r = 2:length(valid_edges) if !iszero(iter[r]) e += K(iter[r]) * valid_edges[r] end @@ -1034,13 +1142,13 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru if typeof(C) <: AbstractLinearCode P = zeros(Int64, n) for (j, k) in enumerate(e) - P[bds[i] + j] = coeff(k, 0) + P[bds[i]+j] = coeff(k, 0) end else P = zeros(Int64, 2 * n) for (j, k) in enumerate(e) - P[bds[i] + j] = coeff(k, 0) - P[bds[i] + j + n] = coeff(k, 1) + P[bds[i]+j] = coeff(k, 0) + P[bds[i]+j+n] = coeff(k, 1) end end syn = H * P .% p @@ -1056,7 +1164,7 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru # display(contrib_edge) V_left = V[i] - V_right = V[i + 1] + V_right = V[i+1] len_left = length(V_left) len_right = length(V_right) V_right_locs = trues(len_right) @@ -1067,21 +1175,25 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru while starting_right_index <= len_right starting_right_v = V_right[starting_right_index].label - left_vertices = Vector{Tuple{Int64, BigInt, Vector{Int64}}}() - right_vertices = Vector{Tuple{Int64, BigInt, Vector{Int64}}}() + left_vertices = Vector{Tuple{Int64,BigInt,Vector{Int64}}}() + right_vertices = Vector{Tuple{Int64,BigInt,Vector{Int64}}}() sizehint!(left_vertices, profiles[4][i]) sizehint!(right_vertices, profiles[3][i]) - starting_right_v_syn = reverse(digits(starting_right_v, base=2, pad=syn_len)) + starting_right_v_syn = + reverse(digits(starting_right_v, base = 2, pad = syn_len)) # println("i: $i, syn_len: $syn_len, srsyn: $starting_right_v_syn, srv: $starting_right_v") - push!(right_vertices, (starting_right_index, starting_right_v, starting_right_v_syn)) + push!( + right_vertices, + (starting_right_index, starting_right_v, starting_right_v_syn), + ) connecting_starts = blank starting_left_v = biz # start with a fixed right vertex and find all left vertices for lab in keys(edge_contrib) temp = (starting_right_v_syn .- edge_contrib[lab]) - for t in 1:length(temp) + for t = 1:length(temp) if temp[t] < 0 temp[t] = p + temp[t] end @@ -1089,7 +1201,7 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru temp = temp .% p left_label = biz - for (shift, val) in enumerate(reverse(temp, dims=1)) + for (shift, val) in enumerate(reverse(temp, dims = 1)) if val == 1 left_label += bio << (shift - 1) end @@ -1124,7 +1236,7 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru if lab != connecting_starts temp = (starting_left_v .+ edge_contrib[lab]) .% p right_label = biz - for (shift, val) in enumerate(reverse(temp, dims=1)) + for (shift, val) in enumerate(reverse(temp, dims = 1)) if val == 1 right_label += bio << (shift - 1) end @@ -1158,7 +1270,7 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru count = 1 for (left_index, _, left_syn) in left_vertices temp = right_syn .- left_syn - for t in 1:length(temp) + for t = 1:length(temp) if temp[t] < 0 temp[t] = p + temp[t] end @@ -1172,10 +1284,10 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru sign = R(0) for (j, k) in enumerate(lab) if !iszero(coeff(k, 0)) - sign += character_vector(C)[bds[i] + j] + sign += character_vector(C)[bds[i]+j] end if !iszero(coeff(k, 1)) - sign += character_vector(C)[bds[i] + j + n] + sign += character_vector(C)[bds[i]+j+n] end end E[i][right_index][count].sign = sign @@ -1208,7 +1320,7 @@ function syndrome_trellis(C::AbstractCode, type::String="primal", sect::Bool=tru end # should probably return missing to unify if statements in the function below -function trellis_profiles(C::AbstractLinearCode, sect::Bool=false) +function trellis_profiles(C::AbstractLinearCode, sect::Bool = false) G_TOF = trellis_oriented_form_linear(generator_matrix(C)) H_TOF = trellis_oriented_form_linear(parity_check_matrix(C)) if sect @@ -1234,18 +1346,21 @@ end # end ############################# - # Quantum +# Quantum ############################# # only valid for quantum codes -function optimal_sectionalization_Q(wrt_V::Union{FqMatrix, fpMatrix}, wrt_E::Union{FqMatrix, fpMatrix}) +function optimal_sectionalization_Q( + wrt_V::Union{FqMatrix,fpMatrix}, + wrt_E::Union{FqMatrix,fpMatrix}, +) K = base_ring(wrt_E) base_ring(wrt_V) == K || error("Vertices and edges must have the same base ring.") n = size(wrt_V, 2) p = Int64(characteristic(K)) - V = [Vertex(i, 0, 0, 0.0, 0, missing) for i in 1:n + 1] - E = [[Edge(K(0), 0.0, 0, missing) for i in 1:j] for j in n:-1:1] + V = [Vertex(i, 0, 0, 0.0, 0, missing) for i = 1:(n+1)] + E = [[Edge(K(0), 0.0, 0, missing) for i = 1:j] for j = n:-1:1] sym_V = quadratic_to_symplectic(wrt_V) sym_E = quadratic_to_symplectic(wrt_E) @@ -1253,18 +1368,18 @@ function optimal_sectionalization_Q(wrt_V::Union{FqMatrix, fpMatrix}, wrt_E::Uni dim_ker = 0 # println(dim_ker) past, future = _past_future(wrt_E) - for i in 1:n - for j in i:n + for i = 1:n + for j = i:n # arbitrary size cutoff - if size(wrt_E, 1) - past[i] - future[j + 1] - dim_ker > 50 - E[i][j - i + 1].weight = Inf + if size(wrt_E, 1) - past[i] - future[j+1] - dim_ker > 50 + E[i][j-i+1].weight = Inf else - E[i][j - i + 1].weight = p^(size(wrt_E, 1) - past[i] - future[j + 1] - dim_ker) + E[i][j-i+1].weight = p^(size(wrt_E, 1) - past[i] - future[j+1] - dim_ker) end end end - for i in 1:n + for i = 1:n left_b = 1 right_b = i arr = [E[left_b][right_b].weight + V[left_b].value] @@ -1276,8 +1391,8 @@ function optimal_sectionalization_Q(wrt_V::Union{FqMatrix, fpMatrix}, wrt_E::Uni end m, arg = findmin(arr) - V[i + 1].prev = arg - V[i + 1].value = m + V[i+1].prev = arg + V[i+1].value = m end sect_boundaries = [n] @@ -1555,25 +1670,30 @@ end # Pauli == 'Z' # I -> I + Z # X -> X + Y -function weight_Q!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, err_models::Vector{Dict{String, Float64}}, - weight_type::String="additive") +function weight_Q!( + T::Trellis, + Ps::Union{FqMatrix,fpMatrix}, + err_models::Vector{Dict{String,Float64}}, + weight_type::String = "additive", +) - weight_type ∈ ["additive", "multiplicative"] || error("Weight type needs to be 'additive' or 'multiplicative'.") + weight_type ∈ ["additive", "multiplicative"] || + error("Weight type needs to be 'additive' or 'multiplicative'.") V = vertices(T) E = edges(T) - for i in 1:length(E) + for i = 1:length(E) model = err_models[i] - for j in 1:length(V[i + 1]) + for j = 1:length(V[i+1]) Threads.@threads for e in E[i][j] if weight_type == "additive" weight = 0.0 - for k in 1:length(e.label) + for k = 1:length(e.label) weight += model[e.label[k]] end else weight = 1.0 - for k in 1:length(e.label) + for k = 1:length(e.label) weight *= model[e.label[k]] end end @@ -1591,13 +1711,22 @@ end # I -> I + Z # X -> X + Y # remove wrt_V here -function shift_and_weight_Q!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundaries::Union{Vector{Int64}, Missing}, - err_models::Vector{Dict{String, Float64}}, char_vec::Vector{Int64}, Pauli::Char=' ', - weight_type::String="additive") - - Pauli ∈ [' ', 'X', 'Z'] || error("Pauli parameter needs to be ' ', 'X', or 'Z'; received $Pauli.") - weight_type ∈ ["additive", "multiplicative"] || error("Weight type needs to be 'additive' or 'multiplicative'.") - length(char_vec) == 2 * length(err_models) || error("Lengths of character vector and error models are not consistent.") +function shift_and_weight_Q!( + T::Trellis, + Ps::Union{FqMatrix,fpMatrix}, + boundaries::Union{Vector{Int64},Missing}, + err_models::Vector{Dict{String,Float64}}, + char_vec::Vector{Int64}, + Pauli::Char = ' ', + weight_type::String = "additive", +) + + Pauli ∈ [' ', 'X', 'Z'] || + error("Pauli parameter needs to be ' ', 'X', or 'Z'; received $Pauli.") + weight_type ∈ ["additive", "multiplicative"] || + error("Weight type needs to be 'additive' or 'multiplicative'.") + length(char_vec) == 2 * length(err_models) || + error("Lengths of character vector and error models are not consistent.") K = base_ring(Ps) V = vertices(T) @@ -1609,11 +1738,11 @@ function shift_and_weight_Q!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundari bds = deepcopy(boundaries) end - for i in 1:length(E) + for i = 1:length(E) model = err_models[i] - for j in 1:length(V[i + 1]) + for j = 1:length(V[i+1]) Threads.@threads for e in E[i][j] - e.label += Ps[bds[i] + 1:bds[i + 1]] + e.label += Ps[(bds[i]+1):bds[i+1]] if Pauli == 'X' for k in e.label k -= K(coeff(k, 0)) @@ -1632,10 +1761,10 @@ function shift_and_weight_Q!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundari end for (l, k) in enumerate(e.label) if !iszero(coeff(k, 0)) - sign *= char_vec[bds[i] + l] + sign *= char_vec[bds[i]+l] end if !iszero(coeff(k, 1)) - sign *= char_vec[bds[i] + l + code_n] + sign *= char_vec[bds[i]+l+code_n] end if weight_type == "additive" weight += model[k] @@ -1651,9 +1780,15 @@ function shift_and_weight_Q!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundari end # do I actually care about updating the signs here? -function shift_and_decode_Q!!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundaries::Union{Vector{Int64}, Missing}, - err_models::Vector{Dict{FqFieldElem, Float64}}, char_vec::Vector{Int64}, Pauli::Char=' ', - weight_type::String="additive") +function shift_and_decode_Q!!( + T::Trellis, + Ps::Union{FqMatrix,fpMatrix}, + boundaries::Union{Vector{Int64},Missing}, + err_models::Vector{Dict{FqFieldElem,Float64}}, + char_vec::Vector{Int64}, + Pauli::Char = ' ', + weight_type::String = "additive", +) # Pauli ∈ [' ', 'X', 'Z'] || error("Pauli parameter needs to be ' ', 'X', or 'Z'; received $Pauli.") # weight_type ∈ ["additive", "multiplicative"] || error("Weight type needs to be 'additive' or 'multiplicative'.") @@ -1669,12 +1804,12 @@ function shift_and_decode_Q!!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundar bds = deepcopy(boundaries) end - for i in 1:length(E) + for i = 1:length(E) model = err_models[i] - for (j, v) in enumerate(V[i + 1]) + for (j, v) in enumerate(V[i+1]) # don't Threads.@threads the below loop or you get a >100x slow down due to locking for e in E[i][j] - e.label += Ps[1, bds[i] + 1:bds[i + 1]] + e.label += Ps[1, (bds[i]+1):bds[i+1]] if Pauli == 'X' for k in e.label k -= K(coeff(k, 0)) @@ -1720,18 +1855,24 @@ function shift_and_decode_Q!!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundar path = zero_matrix(base_ring(Ps), 1, code_n) curr = code_n prev = 1 - for i in length(E) + 1:-1:2 - e_label = E[i - 1][prev][V[i][prev].edge_loc].label - path[1, (curr - length(e_label) + 1):curr] = e_label + for i = (length(E)+1):-1:2 + e_label = E[i-1][prev][V[i][prev].edge_loc].label + path[1, (curr-length(e_label)+1):curr] = e_label prev = V[i][prev].prev curr -= length(e_label) end return path end -function shift!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundaries::Union{Vector{Int64}, Missing}, - err_models::Vector{Dict{FqFieldElem, Float64}}, char_vec::Vector{Int64}, Pauli::Char=' ', - weight_type::String="additive") +function shift!( + T::Trellis, + Ps::Union{FqMatrix,fpMatrix}, + boundaries::Union{Vector{Int64},Missing}, + err_models::Vector{Dict{FqFieldElem,Float64}}, + char_vec::Vector{Int64}, + Pauli::Char = ' ', + weight_type::String = "additive", +) # Pauli ∈ [' ', 'X', 'Z'] || error("Pauli parameter needs to be ' ', 'X', or 'Z'; received $Pauli.") # weight_type ∈ ["additive", "multiplicative"] || error("Weight type needs to be 'additive' or 'multiplicative'.") @@ -1747,11 +1888,11 @@ function shift!(T::Trellis, Ps::Union{FqMatrix, fpMatrix}, boundaries::Union{Vec bds = deepcopy(boundaries) end - for i in 1:length(E) + for i = 1:length(E) model = err_models[i] - for j in 1:length(V[i + 1]) + for j = 1:length(V[i+1]) Threads.@threads for e in E[i][j] - e.label += Ps[1, bds[i] + 1:bds[i + 1]] + e.label += Ps[1, (bds[i]+1):bds[i+1]] if Pauli == 'X' for k in e.label k -= K(coeff(k, 0)) @@ -1790,12 +1931,17 @@ end # think of more scenarios # could allow general trellises given partial stabilizers for use in trellis product -function trellis_profiles(Q::AbstractStabilizerCode, type::String="weight", Pauli::Char=' ', - sect::Bool=false) +function trellis_profiles( + Q::AbstractStabilizerCode, + type::String = "weight", + Pauli::Char = ' ', + sect::Bool = false, +) type ∈ ["weight", "decoding"] || error("Unknown type parameter in trellis_profiles.") # (Pauli != ' ' && typeof(Q) <: CSSCode) && error("Pauli parameter is non-empty but the code is not CSS.") - Pauli ∈ [' ', 'X', 'Z'] || error("Unknown Pauli parameter $Pauli; must be ' ', 'X', or 'Z'.") + Pauli ∈ [' ', 'X', 'Z'] || + error("Unknown Pauli parameter $Pauli; must be ' ', 'X', or 'Z'.") if type == "weight" if Pauli == ' ' @@ -1808,8 +1954,14 @@ function trellis_profiles(Q::AbstractStabilizerCode, type::String="weight", Paul end return trellis_profiles(n_TOF, S_TOF, missing, "symplectic") elseif Pauli == 'X' - _, _, Z_perp, _, _, _ = split_symplectic_stabilizers(quadratic_to_symplectic(normalizermatrix(Q)), ones(Int64, size(normalizermatrix(Q), 1))) - X = hcat(X_stabilizers(Q), zero_matrix(field(Q), size(X_stabilizers(Q), 1), size(X_stabilizers(Q), 2))) + _, _, Z_perp, _, _, _ = split_symplectic_stabilizers( + quadratic_to_symplectic(normalizermatrix(Q)), + ones(Int64, size(normalizermatrix(Q), 1)), + ) + X = hcat( + X_stabilizers(Q), + zero_matrix(field(Q), size(X_stabilizers(Q), 1), size(X_stabilizers(Q), 2)), + ) Z_perp_TOF = trellis_oriented_form_additive(symplectic_to_quadratic(Z_perp)) X_TOF = trellis_oriented_form_additive(symplectic_to_quadratic(X)) if sect @@ -1818,8 +1970,14 @@ function trellis_profiles(Q::AbstractStabilizerCode, type::String="weight", Paul end return trellis_profiles(Z_perp_TOF, X_TOF, missing, "symplectic") else - X_perp, _, _, _, _, _ = split_symplectic_stabilizers(quadratic_to_symplectic(normalizermatrix(Q)), ones(Int64, size(normalizermatrix(Q), 1))) - Z = hcat(zero_matrix(field(Q), size(Z_stabilizers(Q), 1), size(Z_stabilizers(Q), 2)), Z_stabilizers(Q)) + X_perp, _, _, _, _, _ = split_symplectic_stabilizers( + quadratic_to_symplectic(normalizermatrix(Q)), + ones(Int64, size(normalizermatrix(Q), 1)), + ) + Z = hcat( + zero_matrix(field(Q), size(Z_stabilizers(Q), 1), size(Z_stabilizers(Q), 2)), + Z_stabilizers(Q), + ) X_perp_TOF = trellis_oriented_form_additive(symplectic_to_quadratic(X_perp)) Z_TOF = trellis_oriented_form_additive(symplectic_to_quadratic(Z)) if sect @@ -1838,8 +1996,14 @@ function trellis_profiles(Q::AbstractStabilizerCode, type::String="weight", Paul end return trellis_profiles(S_TOF, n_TOF, missing, "symplectic") elseif Pauli == 'X' - _, _, Z_perp, _, _, _ = split_symplectic_stabilizers(quadratic_to_symplectic(normalizermatrix(Q)), ones(Int64, size(normalizermatrix(Q), 1))) - X = hcat(X_stabilizers(Q), zero_matrix(field(Q), size(X_stabilizers(Q), 1), size(X_stabilizers(Q), 2))) + _, _, Z_perp, _, _, _ = split_symplectic_stabilizers( + quadratic_to_symplectic(normalizermatrix(Q)), + ones(Int64, size(normalizermatrix(Q), 1)), + ) + X = hcat( + X_stabilizers(Q), + zero_matrix(field(Q), size(X_stabilizers(Q), 1), size(X_stabilizers(Q), 2)), + ) Z_perp_TOF = trellis_oriented_form_additive(symplectic_to_quadratic(Z_perp)) X_TOF = trellis_oriented_form_additive(symplectic_to_quadratic(X)) if sect @@ -1848,8 +2012,14 @@ function trellis_profiles(Q::AbstractStabilizerCode, type::String="weight", Paul end return trellis_profiles(X_TOF, Z_perp_TOF, missing, "symplectic") else - X_perp, _, _, _, _, _ = split_symplectic_stabilizers(quadratic_to_symplectic(normalizermatrix(Q)), ones(Int64, size(normalizermatrix(Q), 1))) - Z = hcat(zero_matrix(field(Q), size(Z_stabilizers(Q), 1), size(Z_stabilizers(Q), 2)), Z_stabilizers(Q)) + X_perp, _, _, _, _, _ = split_symplectic_stabilizers( + quadratic_to_symplectic(normalizermatrix(Q)), + ones(Int64, size(normalizermatrix(Q), 1)), + ) + Z = hcat( + zero_matrix(field(Q), size(Z_stabilizers(Q), 1), size(Z_stabilizers(Q), 2)), + Z_stabilizers(Q), + ) X_perp_TOF = trellis_oriented_form_additive(symplectic_to_quadratic(X_perp)) Z_TOF = trellis_oriented_form_additive(symplectic_to_quadratic(Z)) if sect @@ -1945,10 +2115,16 @@ end -function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose::Bool=false) +function sect( + C::AbstractCode, + type::String = "primal", + sect::Bool = true, + verbose::Bool = false, +) - (typeof(C) <: AbstractLinearCode || typeof(C) <: AbstractStabilizerCode) || - error("Syndrome trellises are so far only implemented for linear and stabilizer codes.") + (typeof(C) <: AbstractLinearCode || typeof(C) <: AbstractStabilizerCode) || error( + "Syndrome trellises are so far only implemented for linear and stabilizer codes.", + ) if typeof(C) <: AbstractLinearCode wrt_V = trellis_oriented_form_linear(parity_check_matrix(C)) @@ -1981,7 +2157,7 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: else if type == "primal" wrt_V = trellis_oriented_form_additive(stabilizers(C)) - wrt_E = trellis_oriented_form_additive(normalizermatrix(C)) + wrt_E = trellis_oriented_form_additive(normalizermatrix(C)) else wrt_V = trellis_oriented_form_additive(normalizermatrix(C)) wrt_E = trellis_oriented_form_additive(stabilizers(C)) @@ -2030,44 +2206,47 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: end p = Int64(characteristic(K)) n = C.n - V = Vector{Vertex}[Vertex[] for _ in 1:length(bds)] - Threads.@threads for i in 1:length(profiles[1]) - V[i] = [Vertex(999, 0, 0, 0.0, 0, missing) for _ in 1:profiles[1][i]] + V = Vector{Vertex}[Vertex[] for _ = 1:length(bds)] + Threads.@threads for i = 1:length(profiles[1]) + V[i] = [Vertex(999, 0, 0, 0.0, 0, missing) for _ = 1:profiles[1][i]] end V[1] = [Vertex(0, 0, 0, 0.0, 0, missing)] V[end] = [Vertex(0, 0, 0, 0.0, 0, missing)] verbose && println("Vertex preallocation completed.") - E = Vector{Vector{Edge}}[[Edge[]] for _ in 1:length(profiles[3])] - Threads.@threads for i in 1:length(profiles[3]) + E = Vector{Vector{Edge}}[[Edge[]] for _ = 1:length(profiles[3])] + Threads.@threads for i = 1:length(profiles[3]) # the j-th element of Ei is going to be all of the edges going into Vi[j] - E[i] = [[Edge(K(0), 0.0, 0, missing) for _ in 1:profiles[3][i]] for _ in 1:profiles[1][i + 1]] + E[i] = [ + [Edge(K(0), 0.0, 0, missing) for _ = 1:profiles[3][i]] for + _ = 1:profiles[1][i+1] + ] end verbose && println("Edge preallocation completed.") bio = BigInt(1) syn_len = nrows(wrt_V) active_Vs = _find_active(wrt_V) - active_Vs = active_Vs[bds[2:end - 1]] - Threads.@threads for i in 2:length(bds) - 1 + active_Vs = active_Vs[bds[2:(end-1)]] + Threads.@threads for i = 2:(length(bds)-1) Vi_size = profiles[1][i] - len_act = length(active_Vs[i - 1]) + len_act = length(active_Vs[i-1]) # TODO: can I get away with not reversing throughout # TODO: do I gain anything from making the V.label correct? - for num in 0:Vi_size - 1 + for num = 0:(Vi_size-1) # int to small active digits array - bin = reverse(digits(num, base=p, pad=len_act)) + bin = reverse(digits(num, base = p, pad = len_act)) # to full syn length size temp_label = zeros(Int64, syn_len) loc = 1 - for j in active_Vs[i - 1] + for j in active_Vs[i-1] temp_label[j] = bin[loc] loc += 1 end # i == 3 && println("i = 3: $temp_label") # i == 2 && println("i = 2: $temp_label") # back to int - V[i][num + 1].label = digitstoint(reverse(temp_label, dims=1), p) + V[i][num+1].label = digitstoint(reverse(temp_label, dims = 1), p) end end verbose && println("Vertex construction completed.") @@ -2086,8 +2265,8 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: else active_temp = Vector{Vector{Int64}}() parallel = Vector{Vector{Int64}}() - for i in 1:length(bds) - 1 - temp = sort!(unique!(vcat([active[j] for j in bds[i] + 1:bds[i + 1]]...))) + for i = 1:(length(bds)-1) + temp = sort!(unique!(vcat([active[j] for j = (bds[i]+1):bds[i+1]]...))) # println("temp: $temp") act = Vector{Int64}() par = Vector{Int64}() @@ -2095,7 +2274,8 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: # i == 1 && println(a) # i == 1 && println(bds[i] + 1, ", ", left[a], ", ", right[a], ", ", bds[i + 1]) # i == 1 && println(bds[i] + 1 <= left[a] && right[a] <= bds[i + 1]) - (bds[i] + 1 <= left[a] && right[a] <= bds[i + 1]) ? append!(par, a) : append!(act, a) + (bds[i] + 1 <= left[a] && right[a] <= bds[i+1]) ? append!(par, a) : + append!(act, a) end push!(active_temp, act) push!(parallel, par) @@ -2107,16 +2287,18 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: H = _Flint_matrix_to_Julia_int_matrix(wrt_V) else sym_wrt_V = quadratic_to_symplectic(wrt_V) - H = _Flint_matrix_to_Julia_int_matrix(hcat(sym_wrt_V[:, n + 1:end], -sym_wrt_V[:, 1:n])) + H = _Flint_matrix_to_Julia_int_matrix( + hcat(sym_wrt_V[:, (n+1):end], -sym_wrt_V[:, 1:n]), + ) end - + # Threads.@threads - for i in length(bds) - 1:-1:1 + for i = (length(bds)-1):-1:1 verbose && println("Starting E[$i]") - + valid_edges = Vector{FqMatrix}() - edge_contrib = Dict{FqMatrix, Vector{Int64}}() - contrib_edge = Dict{Vector{Int64}, FqMatrix}() + edge_contrib = Dict{FqMatrix,Vector{Int64}}() + contrib_edge = Dict{Vector{Int64},FqMatrix}() par_flag = false if !ismissing(parallel) && !isempty(parallel[i]) @@ -2125,24 +2307,34 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: for a in parallel[i] # should never be zero because the entire row is between this # same argument says it's always unique - push!(p_edges, wrt_E[a, bds[i] + 1:bds[i + 1]]) + push!(p_edges, wrt_E[a, (bds[i]+1):bds[i+1]]) end parallel_edges = Vector{FqMatrix}() - for iter in Nemo.AbstractAlgebra.ProductIterator(collect(0:p - 1), length(p_edges)) + for iter in + Nemo.AbstractAlgebra.ProductIterator(collect(0:(p-1)), length(p_edges)) e = K(iter[1]) * p_edges[1] - for r in 2:length(p_edges) + for r = 2:length(p_edges) if !iszero(iter[r]) e += K(iter[r]) * p_edges[r] end end !iszero(e) && push!(parallel_edges, e) end - + if length(parallel_edges) > 1 p_e_mat_sym = quadratic_to_symplectic(reduce(vcat, parallel_edges)) - temp = symplectic_to_quadratic(_remove_empty(_rref_no_col_swap(p_e_mat_sym, 1:nrows(p_e_mat_sym), 1:ncols(p_e_mat_sym)), :rows)) - parallel_edges = [temp[i, :] for i in 1:nrows(temp)] + temp = symplectic_to_quadratic( + _remove_empty( + _rref_no_col_swap( + p_e_mat_sym, + 1:nrows(p_e_mat_sym), + 1:ncols(p_e_mat_sym), + ), + :rows, + ), + ) + parallel_edges = [temp[i, :] for i = 1:nrows(temp)] else p_e_mat_sym = quadratic_to_symplectic(reduce(vcat, parallel_edges)) end @@ -2152,7 +2344,7 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: # i == 2 && return for a in active_temp[i] - temp = wrt_E[a, bds[i] + 1:bds[i + 1]] + temp = wrt_E[a, (bds[i]+1):bds[i+1]] if !iszero(temp) push!(valid_edges, temp) end @@ -2162,34 +2354,61 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: v_e_mat_sym = quadratic_to_symplectic(reduce(vcat, valid_edges)) F = base_ring(v_e_mat_sym) VS = vector_space(F, ncols(v_e_mat_sym)) - U, U_to_VS = sub(VS, [VS(p_e_mat_sym[i, :]) for i in 1:nrows(p_e_mat_sym)]) - W, W_to_VS = sub(VS, [VS(v_e_mat_sym[i, :]) for i in 1:nrows(v_e_mat_sym)]) + U, U_to_VS = sub(VS, [VS(p_e_mat_sym[i, :]) for i = 1:nrows(p_e_mat_sym)]) + W, W_to_VS = sub(VS, [VS(v_e_mat_sym[i, :]) for i = 1:nrows(v_e_mat_sym)]) I, _ = intersect(U, W) if !iszero(AbstractAlgebra.dim(I)) println("i = $i, here quo") gens_of_U_in_W = [preimage(W_to_VS, U_to_VS(g)) for g in gens(U)] U_in_W, _ = sub(W, gens_of_U_in_W) Q, W_to_Q = quo(W, U_in_W) - C2_mod_C1_basis = [W_to_VS(x) for x in [preimage(W_to_Q, g) for g in gens(Q)]] - F_basis = [[F(C2_mod_C1_basis[j][i]) for i in 1:AbstractAlgebra.dim(parent(C2_mod_C1_basis[1]))] for j in 1:length(C2_mod_C1_basis)] - temp = symplectic_to_quadratic(matrix(F, length(F_basis), length(F_basis[1]), vcat(F_basis...))) - valid_edges = [temp[i, :] for i in 1:nrows(temp)] + C2_mod_C1_basis = + [W_to_VS(x) for x in [preimage(W_to_Q, g) for g in gens(Q)]] + F_basis = [ + [ + F(C2_mod_C1_basis[j][i]) for + i = 1:AbstractAlgebra.dim(parent(C2_mod_C1_basis[1])) + ] for j = 1:length(C2_mod_C1_basis) + ] + temp = symplectic_to_quadratic( + matrix(F, length(F_basis), length(F_basis[1]), vcat(F_basis...)), + ) + valid_edges = [temp[i, :] for i = 1:nrows(temp)] else - temp = symplectic_to_quadratic(_remove_empty(_rref_no_col_swap(v_e_mat_sym, 1:nrows(v_e_mat_sym), 1:ncols(v_e_mat_sym)), :rows)) - valid_edges = [temp[i, :] for i in 1:nrows(temp)] + temp = symplectic_to_quadratic( + _remove_empty( + _rref_no_col_swap( + v_e_mat_sym, + 1:nrows(v_e_mat_sym), + 1:ncols(v_e_mat_sym), + ), + :rows, + ), + ) + valid_edges = [temp[i, :] for i = 1:nrows(temp)] end else - temp = symplectic_to_quadratic(_remove_empty(_rref_no_col_swap(v_e_mat_sym, 1:nrows(v_e_mat_sym), 1:ncols(v_e_mat_sym)), :rows)) - valid_edges = [temp[i, :] for i in 1:nrows(temp)] + temp = symplectic_to_quadratic( + _remove_empty( + _rref_no_col_swap( + v_e_mat_sym, + 1:nrows(v_e_mat_sym), + 1:ncols(v_e_mat_sym), + ), + :rows, + ), + ) + valid_edges = [temp[i, :] for i = 1:nrows(temp)] end println("i = $i") display(valid_edges) # return # i == 2 && return - for iter in Nemo.AbstractAlgebra.ProductIterator(collect(0:p - 1), length(valid_edges)) + for iter in + Nemo.AbstractAlgebra.ProductIterator(collect(0:(p-1)), length(valid_edges)) e = K(iter[1]) * valid_edges[1] - for r in 2:length(valid_edges) + for r = 2:length(valid_edges) if !iszero(iter[r]) e += K(iter[r]) * valid_edges[r] end @@ -2198,19 +2417,19 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: if typeof(C) <: AbstractLinearCode P = zeros(Int64, n) for (j, k) in enumerate(e) - P[bds[i] + j] = coeff(k, 0) + P[bds[i]+j] = coeff(k, 0) end else P = zeros(Int64, 2 * n) for (j, k) in enumerate(e) - P[bds[i] + j] = coeff(k, 0) - P[bds[i] + j + n] = coeff(k, 1) + P[bds[i]+j] = coeff(k, 0) + P[bds[i]+j+n] = coeff(k, 1) end end syn = H * P .% p # if !iszero(syn) - edge_contrib[e] = syn - contrib_edge[syn] = e + edge_contrib[e] = syn + contrib_edge[syn] = e # end end # i == 2 && display(edge_contrib) @@ -2218,16 +2437,17 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: verbose && println("Edges dictionaries completed for E[$i].") Vl_len = profiles[1][i] - Vr_len = profiles[1][i + 1] - left_vertices = Vector{Tuple{BigInt, Vector{Int}}}() - right_vertices = Vector{Tuple{BigInt, Vector{Int}}}() + Vr_len = profiles[1][i+1] + left_vertices = Vector{Tuple{BigInt,Vector{Int}}}() + right_vertices = Vector{Tuple{BigInt,Vector{Int}}}() sizehint!(left_vertices, profiles[4][i]) sizehint!(right_vertices, profiles[3][i]) # find fundamental edge configuration # find all v-e-0 left_syn = right_syn = zeros(Int64, syn_len) - fundamental = Vector{Tuple{BigInt, Vector{Int}, Vector{FqMatrix}, Vector{Int}, BigInt}}() + fundamental = + Vector{Tuple{BigInt,Vector{Int},Vector{FqMatrix},Vector{Int},BigInt}}() for lab in keys(edge_contrib) left_syn = (right_syn .- edge_contrib[lab] .+ p) .% p if i == 1 && iszero(left_syn) @@ -2239,8 +2459,9 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: end push!(fundamental, (bio, left_syn, edgs, right_syn, bio)) push!(left_vertices, (bio, left_syn)) - elseif i != 1 && iszero(left_syn[setdiff(1:syn_len, active_Vs[i - 1])]) - left_loc = BigInt(digitstoint(reverse(left_syn[active_Vs[i - 1]], dims=1), p)) + 1 + elseif i != 1 && iszero(left_syn[setdiff(1:syn_len, active_Vs[i-1])]) + left_loc = + BigInt(digitstoint(reverse(left_syn[active_Vs[i-1]], dims = 1), p)) + 1 if left_loc <= Vl_len edgs = [lab] if par_flag @@ -2259,7 +2480,8 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: for lab in keys(edge_contrib) right_syn = edge_contrib[lab] if i != length(bds) - 1 && iszero(right_syn[setdiff(1:syn_len, active_Vs[i])]) - right_loc = BigInt(digitstoint(reverse(right_syn[active_Vs[i]], dims=1), p)) + 1 + right_loc = + BigInt(digitstoint(reverse(right_syn[active_Vs[i]], dims = 1), p)) + 1 if !isone(right_loc) edgs = [lab] if par_flag @@ -2278,23 +2500,23 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: for (rl, rv) in right_vertices temp = (rv .- lv .+ p) .% p # if !iszero(temp) - lab = contrib_edge[temp] - edgs = [lab] - if par_flag - for a in parallel_edges - push!(edgs, a + lab) - end - end - tup = (ll, lv, edgs, rv, rl) - if tup ∉ fundamental - push!(fundamental, tup) + lab = contrib_edge[temp] + edgs = [lab] + if par_flag + for a in parallel_edges + push!(edgs, a + lab) end + end + tup = (ll, lv, edgs, rv, rl) + if tup ∉ fundamental + push!(fundamental, tup) + end # end end end # record fundamental in E[i1] - sort!(fundamental, by=last) + sort!(fundamental, by = last) # i == 2 && println("i = $i") display(fundamental) @@ -2313,12 +2535,12 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: sign = R(0) for (j, k) in enumerate(e) if !iszero(coeff(k, 0)) - sign += character_vector(C)[bds[i] + j] + sign += character_vector(C)[bds[i]+j] end if !iszero(coeff(k, 1)) - sign += character_vector(C)[bds[i] + j + n] + sign += character_vector(C)[bds[i]+j+n] end - end + end E[i][rl][count].sign = sign end count += 1 @@ -2337,7 +2559,7 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: for edg in keys(edge_contrib) error_syn = edge_contrib[edg] # int to small active digits array - bin = reverse(digits(r_loc - 1, base=p, pad=len_act)) + bin = reverse(digits(r_loc - 1, base = p, pad = len_act)) # to full syn length size right_syn = zeros(Int64, syn_len) loc = 1 @@ -2349,7 +2571,7 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: left_syn = (right_syn .- error_syn .+ p) .% p # i == 2 && println("left: $left_syn") # check if this exists and only shift if it does - if iszero(left_syn[setdiff(1:syn_len, active_Vs[i - 1])]) + if iszero(left_syn[setdiff(1:syn_len, active_Vs[i-1])]) # now have v-e-v' not in the fundamental edge configuration # use it to shift # i == 2 && println("in") @@ -2359,9 +2581,21 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: rl == cur || (count = 1; cur = rl;) right_v = (rv .+ right_syn .+ p) .% p # okay to reuse variable here - rl = BigInt(digitstoint(reverse(right_v[active_Vs[i]], dims=1), p)) + 1 + rl = + BigInt( + digitstoint( + reverse(right_v[active_Vs[i]], dims = 1), + p, + ), + ) + 1 left_v = (lv .+ left_syn .+ p) .% p - E[i][rl][count].out_vertex = BigInt(digitstoint(reverse(left_v[active_Vs[i - 1]], dims=1), p)) + 1 + E[i][rl][count].out_vertex = + BigInt( + digitstoint( + reverse(left_v[active_Vs[i-1]], dims = 1), + p, + ), + ) + 1 for e in edgs newe = e + edg E[i][rl][count].label = newe @@ -2369,10 +2603,10 @@ function sect(C::AbstractCode, type::String="primal", sect::Bool=true, verbose:: sign = R(0) for (j, k) in enumerate(newe) if !iszero(coeff(k, 0)) - sign += character_vector(C)[bds[i] + j] + sign += character_vector(C)[bds[i]+j] end if !iszero(coeff(k, 1)) - sign += character_vector(C)[bds[i] + j + n] + sign += character_vector(C)[bds[i]+j+n] end end E[i][rl][count].sign = sign diff --git a/src/utils.jl b/src/utils.jl index 2b58ff1e..1a824b9f 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -5,7 +5,7 @@ # LICENSE file in the root directory of this source tree. ############################# - # Generic Helper Functions +# Generic Helper Functions ############################# """ @@ -13,7 +13,7 @@ Returns a copy of the code `C`. """ -function copy(C::T) where T <: AbstractCode +function copy(C::T) where {T<:AbstractCode} C2 = deepcopy(C) hasfield(T, :F) && (C2.F = C.F;) hasfield(T, :E) && (C2.E = C.E;) @@ -28,7 +28,8 @@ function copy(C::T) where T <: AbstractCode end _has_equivalent_row_spaces(A::CTMatrixTypes, B::CTMatrixTypes) = - return _remove_empty(rref(deepcopy(A))[2], :rows) == _remove_empty(rref(deepcopy(B))[2], :rows) + return _remove_empty(rref(deepcopy(A))[2], :rows) == + _remove_empty(rref(deepcopy(B))[2], :rows) # """ # reverse(v::CTMatrixTypes) @@ -92,13 +93,16 @@ _has_equivalent_row_spaces(A::CTMatrixTypes, B::CTMatrixTypes) = Return the direct sum of the two matrices `A` and `B`. """ -function ⊕(A::T, B::T) where T <: CTMatrixTypes - base_ring(A) == base_ring(B) || throw(ArgumentError("Matrices must be over the same base ring in direct_sum.")) +function ⊕(A::T, B::T) where {T<:CTMatrixTypes} + base_ring(A) == base_ring(B) || + throw(ArgumentError("Matrices must be over the same base ring in direct_sum.")) - return vcat(hcat(A, zero_matrix(base_ring(B), nrows(A), ncols(B))), - hcat(zero_matrix(base_ring(A), nrows(B), ncols(A)), B)) + return vcat( + hcat(A, zero_matrix(base_ring(B), nrows(A), ncols(B))), + hcat(zero_matrix(base_ring(A), nrows(B), ncols(A)), B), + ) end -direct_sum(A::T, B::T) where T <: CTMatrixTypes = A ⊕ B +direct_sum(A::T, B::T) where {T<:CTMatrixTypes} = A ⊕ B """ ⊗(A::CTMatrixTypes, B::CTMatrixTypes) @@ -108,9 +112,18 @@ direct_sum(A::T, B::T) where T <: CTMatrixTypes = A ⊕ B Return the Kronecker product of the two matrices `A` and `B`. """ -⊗(A::Union{CTMatrixTypes, MatElem{<: ResElem}, MatElem{<: CTGroupAlgebra}}, B::Union{CTMatrixTypes, MatElem{<: ResElem}, MatElem{<: CTGroupAlgebra}}) = kronecker_product(A, B) -kron(A::Union{CTMatrixTypes, MatElem{<: ResElem}, MatElem{<: CTGroupAlgebra}}, B::Union{CTMatrixTypes, MatElem{<: ResElem}, MatElem{<: CTGroupAlgebra}}) = kronecker_product(A, B) -tensor_product(A::Union{CTMatrixTypes, MatElem{<: ResElem}, MatElem{<: CTGroupAlgebra}}, B::Union{CTMatrixTypes, MatElem{<: ResElem}, MatElem{<: CTGroupAlgebra}}) = kronecker_product(A, B) +⊗( + A::Union{CTMatrixTypes,MatElem{<: ResElem},MatElem{<: CTGroupAlgebra}}, + B::Union{CTMatrixTypes,MatElem{<: ResElem},MatElem{<: CTGroupAlgebra}}, +) = kronecker_product(A, B) +kron( + A::Union{CTMatrixTypes,MatElem{<: ResElem},MatElem{<: CTGroupAlgebra}}, + B::Union{CTMatrixTypes,MatElem{<: ResElem},MatElem{<: CTGroupAlgebra}}, +) = kronecker_product(A, B) +tensor_product( + A::Union{CTMatrixTypes,MatElem{<: ResElem},MatElem{<: CTGroupAlgebra}}, + B::Union{CTMatrixTypes,MatElem{<: ResElem},MatElem{<: CTGroupAlgebra}}, +) = kronecker_product(A, B) # I think we should avoid length checking here and return it for entire matrix if given # Hamming_weight(v::T) where T <: Union{CTMatrixTypes, gfp_mat, Vector{S}} where S <: Integer = count(i->(i != 0), v) @@ -121,18 +134,48 @@ tensor_product(A::Union{CTMatrixTypes, MatElem{<: ResElem}, MatElem{<: CTGroupAl Return the Hamming weight of `v`. """ -function Hamming_weight(v::T) where T <: Union{CTMatrixTypes, Vector{<:CTFieldElem}, Vector{S}, Adjoint{S, Vector{S}}, AbstractMatrix{S}} where S <: Integer +function Hamming_weight( + v::T, +) where { + T<:Union{ + CTMatrixTypes, + Vector{<:CTFieldElem}, + Vector{S}, + Adjoint{S,Vector{S}}, + AbstractMatrix{S}, + }, +} where {S<:Integer} count(x -> !iszero(x), v) end -weight(v::T) where T <: Union{CTMatrixTypes, Vector{<:CTFieldElem}, Vector{S}, Adjoint{S, Vector{S}}, AbstractMatrix{S}} where S <: Integer = Hamming_weight(v) -wt(v::T) where T <: Union{CTMatrixTypes, Vector{<:CTFieldElem}, Vector{S}, Adjoint{S, Vector{S}}, AbstractMatrix{S}} where S <: Integer = Hamming_weight(v) +weight( + v::T, +) where { + T<:Union{ + CTMatrixTypes, + Vector{<:CTFieldElem}, + Vector{S}, + Adjoint{S,Vector{S}}, + AbstractMatrix{S}, + }, +} where {S<:Integer} = Hamming_weight(v) +wt( + v::T, +) where { + T<:Union{ + CTMatrixTypes, + Vector{<:CTFieldElem}, + Vector{S}, + Adjoint{S,Vector{S}}, + AbstractMatrix{S}, + }, +} where {S<:Integer} = Hamming_weight(v) # TODO polish and export? -function row_wts_symplectic(A::Union{CTMatrixTypes, Matrix{<: Integer}, Matrix{Bool}}) +function row_wts_symplectic(A::Union{CTMatrixTypes,Matrix{<: Integer},Matrix{Bool}}) nc = size(A, 2) iseven(nc) || throw(ArgumentError("Input does not have even length")) n = div(nc, 2) - return [count(!iszero(A[i, j]) || !iszero(A[i, j + n]) for j in 1:n) for i in axes(A, 1)] + return [count(!iszero(A[i, j]) || !iszero(A[i, j+n]) for j = 1:n) for i in axes(A, 1)] end # Hamming_weight(v::Matrix{Int}) = return sum(v) @@ -151,26 +194,35 @@ wt(f::CTPolyRingElem) = Hamming_weight(collect(coefficients(f))) # # Return the minimum weight and corresponding index of the rows of `A`. # """ -function _min_wt_row(A::Union{CTMatrixTypes, Matrix{S}, LinearAlgebra.Adjoint{S, Matrix{S}}}) where S <: Integer +function _min_wt_row( + A::Union{CTMatrixTypes,Matrix{S},LinearAlgebra.Adjoint{S,Matrix{S}}}, +) where {S<:Integer} w = size(A, 2) + 1 i = 0 for r in axes(A, 1) w_loc = 0 for c in axes(A, 2) - iszero(A[r,c]) || (w_loc += 1) + iszero(A[r, c]) || (w_loc += 1) end w_loc < w && (w = w_loc; i = r;) end return w, i end -function _min_wt_col(A::Union{CTMatrixTypes, Matrix{S}, LinearAlgebra.Adjoint{S, Matrix{S}}, LinearAlgebra.Adjoint{Bool, BitMatrix}}) where S <: Integer +function _min_wt_col( + A::Union{ + CTMatrixTypes, + Matrix{S}, + LinearAlgebra.Adjoint{S,Matrix{S}}, + LinearAlgebra.Adjoint{Bool,BitMatrix}, + }, +) where {S<:Integer} w = size(A, 1) + 1 i = 0 for c in axes(A, 2) w_loc = 0 for r in axes(A, 1) - iszero(A[r,c]) || (w_loc += 1) + iszero(A[r, c]) || (w_loc += 1) end w_loc < w && (w = w_loc; i = c;) end @@ -184,9 +236,12 @@ end Return the Hamming distance between `u` and `v`. """ -Hamming_distance(u::T, v::T) where T <: Union{CTMatrixTypes, Vector{S}} where S <: Integer = Hamming_weight(u - v) -distance(u::T, v::T) where T <: Union{CTMatrixTypes, Vector{S}} where S <: Integer = Hamming_weight(u - v) -dist(u::T, v::T) where T <: Union{CTMatrixTypes, Vector{S}} where S <: Integer = Hamming_weight(u - v) +Hamming_distance(u::T, v::T) where {T<:Union{CTMatrixTypes,Vector{S}}} where {S<:Integer} = + Hamming_weight(u - v) +distance(u::T, v::T) where {T<:Union{CTMatrixTypes,Vector{S}}} where {S<:Integer} = + Hamming_weight(u - v) +dist(u::T, v::T) where {T<:Union{CTMatrixTypes,Vector{S}}} where {S<:Integer} = + Hamming_weight(u - v) """ symplectic_inner_product(u::CTMatrixTypes, v::CTMatrixTypes) @@ -194,14 +249,26 @@ dist(u::T, v::T) where T <: Union{CTMatrixTypes, Vector{S}} where S <: Integer = Return the symplectic inner product of `u` and `v`. """ function symplectic_inner_product(u::CTMatrixTypes, v::CTMatrixTypes) - (nrows(u) == 1 || ncols(u) == 1) || throw(ArgumentError("First argument of symplectic inner product is not a vector: dims = $(size(u, 1)).")) - (nrows(v) == 1 || ncols(v) == 1) || throw(ArgumentError("Second argument of symplectic inner product is not a vector: dims = $(size(v, 1)).")) - length(u) == length(v) || throw(ArgumentError("Vectors must be the same length in symplectic inner product.")) - iseven(length(u)) || throw(ArgumentError("Vectors must have even length in symplectic inner product.")) - base_ring(u) == base_ring(v) || throw(ArgumentError("Vectors must be over the same field in symplectic inner product.")) - + (nrows(u) == 1 || ncols(u) == 1) || throw( + ArgumentError( + "First argument of symplectic inner product is not a vector: dims = $(size(u, 1)).", + ), + ) + (nrows(v) == 1 || ncols(v) == 1) || throw( + ArgumentError( + "Second argument of symplectic inner product is not a vector: dims = $(size(v, 1)).", + ), + ) + length(u) == length(v) || + throw(ArgumentError("Vectors must be the same length in symplectic inner product.")) + iseven(length(u)) || + throw(ArgumentError("Vectors must have even length in symplectic inner product.")) + base_ring(u) == base_ring(v) || throw( + ArgumentError("Vectors must be over the same field in symplectic inner product."), + ) + ncols = div(length(u), 2) - return sum(u[i + ncols] * v[i] - v[i + ncols] * u[i] for i in 1:ncols) + return sum(u[i+ncols] * v[i] - v[i+ncols] * u[i] for i = 1:ncols) end """ @@ -210,9 +277,12 @@ end Return `true` if the rows of the matrices `A` and `B` are symplectic orthogonal. """ function are_symplectic_orthogonal(A::CTMatrixTypes, B::CTMatrixTypes) - base_ring(A) == base_ring(B) || throw(ArgumentError("Matrices in product must both be over the same base ring.")) - - return iszero(hcat(A[:, div(ncols(A), 2) + 1:end], -A[:, 1:div(ncols(A), 2)]) * transpose(B)) + base_ring(A) == base_ring(B) || + throw(ArgumentError("Matrices in product must both be over the same base ring.")) + + return iszero( + hcat(A[:, (div(ncols(A), 2)+1):end], -A[:, 1:div(ncols(A), 2)]) * transpose(B), + ) end # function traceinnerproduct(u::CTMatrixTypes, v::CTMatrixTypes) @@ -225,15 +295,30 @@ end Return the Hermitian inner product of `u` and `v`. """ function Hermitian_inner_product(u::CTMatrixTypes, v::CTMatrixTypes) - (nrows(u) == 1 || ncols(u) == 1) || throw(ArgumentError("First argument of Hermitian inner product is not a vector: dims = $(size(u, 1)).")) - (nrows(v) == 1 || ncols(v) == 1) || throw(ArgumentError("Second argument of Hermitian inner product is not a vector: dims = $(size(v, 1)).")) - length(u) == length(v) || throw(ArgumentError("Vectors must be the same length in Hermitian inner product.")) - base_ring(u) == base_ring(v) || throw(ArgumentError("Vectors must be over the same field in Hermitian inner product.")) + (nrows(u) == 1 || ncols(u) == 1) || throw( + ArgumentError( + "First argument of Hermitian inner product is not a vector: dims = $(size(u, 1)).", + ), + ) + (nrows(v) == 1 || ncols(v) == 1) || throw( + ArgumentError( + "Second argument of Hermitian inner product is not a vector: dims = $(size(v, 1)).", + ), + ) + length(u) == length(v) || + throw(ArgumentError("Vectors must be the same length in Hermitian inner product.")) + base_ring(u) == base_ring(v) || throw( + ArgumentError("Vectors must be over the same field in Hermitian inner product."), + ) q2 = order(base_ring(u)) - is_square(q2) || throw(ArgumentError("The Hermitian inner product is only defined over quadratic field extensions.")) - + is_square(q2) || throw( + ArgumentError( + "The Hermitian inner product is only defined over quadratic field extensions.", + ), + ) + q = Int(sqrt(q2, check = false)) - return sum(u[i] * v[i]^q for i in 1:length(u)) + return sum(u[i] * v[i]^q for i = 1:length(u)) end """ @@ -244,7 +329,11 @@ Return the Hermitian conjugate of the matrix `A`. function Hermitian_conjugate_matrix(A::CTMatrixTypes) R = base_ring(A) q2 = order(R) - is_square(q2) || throw(ArgumentError("The Hermitian conjugate is only defined over quadratic field extensions.")) + is_square(q2) || throw( + ArgumentError( + "The Hermitian conjugate is only defined over quadratic field extensions.", + ), + ) q = Int(sqrt(q2, check = false)) # return matrix(R, A .^ q) @@ -265,11 +354,17 @@ end # return x * (log(q, q - 1) - log(q, x)) - (1 - x) * log(q, 1 - x) # end -_Flint_matrix_element_to_Julia_int(x::fpMatrix, i::Int, j::Int) = ccall((:nmod_mat_get_entry, - Oscar.Nemo.libflint), Int, (Ref{fpMatrix}, Int, Int), x, i - 1 , j - 1) +_Flint_matrix_element_to_Julia_int(x::fpMatrix, i::Int, j::Int) = ccall( + (:nmod_mat_get_entry, Oscar.Nemo.libflint), + Int, + (Ref{fpMatrix}, Int, Int), + x, + i - 1, + j - 1, +) -_Flint_matrix_to_Julia_int_matrix(A) = [ _Flint_matrix_element_to_Julia_int(A, i, j) for i in - 1:nrows(A), j in 1:ncols(A)] +_Flint_matrix_to_Julia_int_matrix(A) = + [_Flint_matrix_element_to_Julia_int(A, i, j) for i = 1:nrows(A), j = 1:ncols(A)] _Flint_matrix_to_Julia_int_vector(A) = vec(_Flint_matrix_to_Julia_int_matrix(A)) @@ -283,7 +378,7 @@ function _Flint_matrix_to_Julia_bool_matrix(A::CTMatrixTypes) Matrix{Bool}(_Flint_matrix_to_Julia_int_matrix(A)) end -function _Flint_matrix_to_Julia_T_matrix(A::CTMatrixTypes, ::Type{T}) where T <: Number +function _Flint_matrix_to_Julia_T_matrix(A::CTMatrixTypes, ::Type{T}) where {T<:Number} Matrix{T}(_Flint_matrix_to_Julia_int_matrix(A)) end @@ -292,7 +387,9 @@ Assumes the input is in rref form and returns the indexs of the columns that do Note that rref form here requires pivot entries have been normalized to 1. """ function _rref_non_pivot_cols(A::CTMatrixTypes, type::Symbol = :nsp) - type ∈ (:sp, :nsp) || throw(DomainError(type, "Parameter should be `:sp` (sparse) or `:nsp` (not sparse).")) + type ∈ (:sp, :nsp) || throw( + DomainError(type, "Parameter should be `:sp` (sparse) or `:nsp` (not sparse)."), + ) if type == :sp return setdiff(collect(1:ncols(A)), [x.pos[1] for x in A]) @@ -315,24 +412,29 @@ function _rref_non_pivot_cols(A::CTMatrixTypes, type::Symbol = :nsp) end end -function _quotient_space(big::T, small::T, alg::Symbol=:sys_eqs) where T <: CTMatrixTypes +function _quotient_space(big::T, small::T, alg::Symbol = :sys_eqs) where {T<:CTMatrixTypes} alg ∈ [:VS, :sys_eqs] || throw(ArgumentError("Unknown algorithm type")) if alg == :VS F = base_ring(big) V = vector_space(F, ncols(big)) - U, U_to_V = sub(V, [V(small[i, :]) for i in 1:nrows(small)]) - W, W_to_V = sub(V, [V(big[i, :]) for i in 1:nrows(big)]) + U, U_to_V = sub(V, [V(small[i, :]) for i = 1:nrows(small)]) + W, W_to_V = sub(V, [V(big[i, :]) for i = 1:nrows(big)]) gens_of_U_in_W = Vector{typeof(gens(U)[1])}(undef, length(gens(U))) # gens_of_U_in_W = [preimage(W_to_V, U_to_V(g)) for g in gens(U)] - Threads.@threads for i in 1:length(gens(U)) + Threads.@threads for i = 1:length(gens(U)) gens_of_U_in_W[i] = preimage(W_to_V, U_to_V(gens(U)[i])) end U_in_W, _ = sub(W, gens_of_U_in_W) Q, W_to_Q = quo(W, U_in_W) iszero(dim(Q)) && (return zero_matrix(F, 1, ncols(big));) C2_mod_C1_basis = [W_to_V(x) for x in [preimage(W_to_Q, g) for g in gens(Q)]] - F_basis = [[F(C2_mod_C1_basis[j][i]) for i in 1:AbstractAlgebra.dim(parent(C2_mod_C1_basis[1]))] for j in 1:length(C2_mod_C1_basis)] + F_basis = [ + [ + F(C2_mod_C1_basis[j][i]) for + i = 1:AbstractAlgebra.dim(parent(C2_mod_C1_basis[1])) + ] for j = 1:length(C2_mod_C1_basis) + ] return matrix(F, length(F_basis), length(F_basis[1]), reduce(vcat, F_basis)) else # solve the system x big = small @@ -341,10 +443,10 @@ function _quotient_space(big::T, small::T, alg::Symbol=:sys_eqs) where T <: CTMa # corresponding to the basis of the quotient # in the general case, anything without a pivot in the row reduction is not required to make # the elements of small and therefore lie in the quotient space - flag, sol = can_solve_with_solution(big, small, side=:left) + flag, sol = can_solve_with_solution(big, small, side = :left) !flag && error("Cannot solve system for quotient") _, rref_sol = rref(sol) - if typeof(rref_sol) <: SMat{W, Vector{W}} where W <: CTFieldElem + if typeof(rref_sol) <: SMat{W,Vector{W}} where {W<:CTFieldElem} nonpivots = _rref_non_pivot_cols(rref_sol, :sp) return reduce(vcat, [big[r, :] for r in nonpivots]) else @@ -372,11 +474,13 @@ end # return maxlen # end -function _has_empty_vec(A::Union{CTMatrixTypes, Matrix{<: Number}, BitMatrix, Matrix{Bool}}, - type::Symbol) - +function _has_empty_vec( + A::Union{CTMatrixTypes,Matrix{<: Number},BitMatrix,Matrix{Bool}}, + type::Symbol, +) + type ∈ (:rows, :cols) || throw(ArgumentError("Unknown type in _remove_empty")) - + del = Vector{Int}() if type == :rows for r in axes(A, 1) @@ -401,14 +505,16 @@ function _has_empty_vec(A::Union{CTMatrixTypes, Matrix{<: Number}, BitMatrix, Ma flag && append!(del, c) end end - return !isempty(del) + return !isempty(del) end -function _remove_empty(A::Union{CTMatrixTypes, Matrix{<: Number}, BitMatrix, Matrix{Bool}}, - type::Symbol) - +function _remove_empty( + A::Union{CTMatrixTypes,Matrix{<: Number},BitMatrix,Matrix{Bool}}, + type::Symbol, +) + type ∈ (:rows, :cols) || throw(ArgumentError("Unknown type in _remove_empty")) - + del = Vector{Int}() if type == :rows for r in axes(A, 1) @@ -437,24 +543,33 @@ function _remove_empty(A::Union{CTMatrixTypes, Matrix{<: Number}, BitMatrix, Mat end end -function _rref_no_col_swap(M::CTMatrixTypes, row_range::AbstractUnitRange{Int} = axes(M, 1), - col_range::AbstractUnitRange{Int} = axes(M, 2)) +function _rref_no_col_swap( + M::CTMatrixTypes, + row_range::AbstractUnitRange{Int} = axes(M, 1), + col_range::AbstractUnitRange{Int} = axes(M, 2), +) A = deepcopy(M) _rref_no_col_swap!(A, row_range, col_range) return A end -function _rref_no_col_swap_binary(A::Union{BitMatrix, Matrix{Bool}, Matrix{<: Integer}}, - row_range::AbstractUnitRange{Int} = axes(A, 1), col_range::AbstractUnitRange{Int} = axes(A, 2)) +function _rref_no_col_swap_binary( + A::Union{BitMatrix,Matrix{Bool},Matrix{<: Integer}}, + row_range::AbstractUnitRange{Int} = axes(A, 1), + col_range::AbstractUnitRange{Int} = axes(A, 2), +) B = deepcopy(A) _rref_no_col_swap_binary!(B, row_range, col_range) return B end -function _rref_no_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = axes(A, 1), - col_range::AbstractUnitRange{Int} = axes(A, 2)) +function _rref_no_col_swap!( + A::CTMatrixTypes, + row_range::AbstractUnitRange{Int} = axes(A, 1), + col_range::AbstractUnitRange{Int} = axes(A, 2), +) # don't do anything to A if the range is empty isempty(row_range) && return nothing @@ -468,7 +583,7 @@ function _rref_no_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break @@ -504,19 +619,19 @@ function _rref_no_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break end end - + if !iszero(ind) # swap to put the pivot in the next row if ind != i A[i, :], A[ind, :] = A[ind, :], A[i, :] end - + # eliminate for k in row_range if k != i @@ -536,8 +651,11 @@ function _rref_no_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} return nothing end -function _rref_no_col_swap_binary!(A::Union{BitMatrix, Matrix{Bool}, Matrix{<: Integer}}, - row_range::AbstractUnitRange{Int} = axes(A, 1), col_range::AbstractUnitRange{Int} = axes(A, 2)) +function _rref_no_col_swap_binary!( + A::Union{BitMatrix,Matrix{Bool},Matrix{<: Integer}}, + row_range::AbstractUnitRange{Int} = axes(A, 1), + col_range::AbstractUnitRange{Int} = axes(A, 2), +) isempty(row_range) && return nothing isempty(col_range) && return nothing @@ -548,7 +666,7 @@ function _rref_no_col_swap_binary!(A::Union{BitMatrix, Matrix{Bool}, Matrix{<: I while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break @@ -579,16 +697,22 @@ function _rref_no_col_swap_binary!(A::Union{BitMatrix, Matrix{Bool}, Matrix{<: I return nothing end -function _rref_col_swap(M::CTMatrixTypes, row_range::AbstractUnitRange{Int} = axes(M, 1), - col_range::AbstractUnitRange{Int} = axes(M, 2)) +function _rref_col_swap( + M::CTMatrixTypes, + row_range::AbstractUnitRange{Int} = axes(M, 1), + col_range::AbstractUnitRange{Int} = axes(M, 2), +) A = deepcopy(M) rnk, P = _rref_col_swap!(A, row_range, col_range) return rnk, A, P end -function _rref_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = axes(A, 1), - col_range::AbstractUnitRange{Int} = axes(A, 2)) +function _rref_col_swap!( + A::CTMatrixTypes, + row_range::AbstractUnitRange{Int} = axes(A, 1), + col_range::AbstractUnitRange{Int} = axes(A, 2), +) # don't do anything to A if the range is empty, return rank 0 and missing permutation matrix isempty(row_range) && return 0, missing @@ -607,7 +731,7 @@ function _rref_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = a while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break @@ -616,8 +740,8 @@ function _rref_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = a # need to column swap if iszero(ind) - for k in j + 1:nc - for l in i:nr + for k = (j+1):nc + for l = i:nr if !iszero(A[l, k]) ismissing(P) && (P = identity_matrix(base_ring(A), nc_A);) swap_cols!(A, k, j) @@ -660,17 +784,17 @@ function _rref_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = a while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break end end - + # need to column swap if iszero(ind) - for k in j + 1:nc - for l in i:nr + for k = (j+1):nc + for l = i:nr if !iszero(A[l, k]) ismissing(P) && (P = identity_matrix(base_ring(A), nc_A);) swap_cols!(A, k, j) @@ -681,14 +805,14 @@ function _rref_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = a end end end - + # if true, the rest of the submatrix is zero if iszero(ind) return rnk, P - else + else # swap to put the pivot in the next row ind != i && swap_rows!(A, ind, i) - + # eliminate for k = first(row_range):nr if k != i @@ -709,15 +833,22 @@ function _rref_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = a return rnk, P end -function _rref_col_swap_perm(M::CTMatrixTypes, row_range::AbstractUnitRange{Int} = axes(M, 1), col_range::AbstractUnitRange{Int} = axes(M, 2)) +function _rref_col_swap_perm( + M::CTMatrixTypes, + row_range::AbstractUnitRange{Int} = axes(M, 1), + col_range::AbstractUnitRange{Int} = axes(M, 2), +) A = deepcopy(M) rnk, P = _rref_col_swap_perm!(A, row_range, col_range) return rnk, A, P end -function _rref_col_swap_perm!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = axes(A, 1), - col_range::AbstractUnitRange{Int} = axes(A, 2)) +function _rref_col_swap_perm!( + A::CTMatrixTypes, + row_range::AbstractUnitRange{Int} = axes(A, 1), + col_range::AbstractUnitRange{Int} = axes(A, 2), +) # don't do anything to A if the range is empty, return rank 0 and missing permutation matrix isempty(row_range) && return 0, missing @@ -732,12 +863,12 @@ function _rref_col_swap_perm!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int nc = last(col_range) sym_group = symmetric_group(nc) # permutation to return to rowspace if column swap done - P = cperm(sym_group) + P = cperm(sym_group) if Int(order(base_ring(A))) != 2 while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break @@ -746,11 +877,11 @@ function _rref_col_swap_perm!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int # need to column swap if iszero(ind) - for k in j + 1:nc - for l in i:nr + for k = (j+1):nc + for l = i:nr if !iszero(A[l, k]) swap_cols!(A, k, j) - P = P * cperm(sym_group, [k,j]) + P = P * cperm(sym_group, [k, j]) ind = l break end @@ -789,34 +920,34 @@ function _rref_col_swap_perm!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break end end - + # need to column swap if iszero(ind) - for k in j + 1:nc - for l in i:nr + for k = (j+1):nc + for l = i:nr if !iszero(A[l, k]) swap_cols!(A, k, j) - P = P * cperm(sym_group, [k,j]) + P = P * cperm(sym_group, [k, j]) ind = l break end end end end - + # if true, the rest of the submatrix is zero if iszero(ind) return rnk, P - else + else # swap to put the pivot in the next row ind != i && swap_rows!(A, ind, i) - + # eliminate for k = first(row_range):nr if k != i @@ -837,15 +968,21 @@ function _rref_col_swap_perm!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int return rnk, inv(P) end -function _rref_symp_col_swap(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = axes(A, 1), - col_range::AbstractUnitRange{Int} = axes(A, 2)) +function _rref_symp_col_swap( + A::CTMatrixTypes, + row_range::AbstractUnitRange{Int} = axes(A, 1), + col_range::AbstractUnitRange{Int} = axes(A, 2), +) B = deepcopy(A) _rref_symp_col_swap!(B, row_range, col_range) return B end -function _rref_symp_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int} = axes(A, 1), - col_range::AbstractUnitRange{Int} = axes(A, 2)) +function _rref_symp_col_swap!( + A::CTMatrixTypes, + row_range::AbstractUnitRange{Int} = axes(A, 1), + col_range::AbstractUnitRange{Int} = axes(A, 2), +) # don't do anything to A if the range is empty, return rank 0 and missing permutation matrix isempty(row_range) && return 0, missing @@ -864,7 +1001,7 @@ function _rref_symp_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break @@ -873,8 +1010,8 @@ function _rref_symp_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int # need to column swap if iszero(ind) - for k in j + 1:nc - for l in i:nr + for k = (j+1):nc + for l = i:nr if !iszero(A[l, k]) ismissing(P) && (P = identity_matrix(base_ring(A), nc_A);) k_symp = mod1(k + div(nc_A, 2), nc_A) @@ -921,7 +1058,7 @@ function _rref_symp_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int while i <= nr && j <= nc # find first pivot ind = 0 - for k in i:nr + for k = i:nr if !iszero(A[k, j]) ind = k break @@ -930,8 +1067,8 @@ function _rref_symp_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int # need to column swap if iszero(ind) - for k in j + 1:nc - for l in i:nr + for k = (j+1):nc + for l = i:nr if !iszero(A[l, k]) ismissing(P) && (P = identity_matrix(base_ring(A), nc_A);) k_symp = mod1(k + div(nc_A, 2), nc_A) @@ -974,7 +1111,7 @@ function _rref_symp_col_swap!(A::CTMatrixTypes, row_range::AbstractUnitRange{Int return rnk, P end -function _col_permutation!(X::Matrix{T}, A::Matrix{T}, p::AbstractVector{Int}) where T +function _col_permutation!(X::Matrix{T}, A::Matrix{T}, p::AbstractVector{Int}) where {T} length(p) == size(A, 2) || throw(ArgumentError("`p` should have length `size(A, 2)`.")) size(X) == size(A) || throw(ArgumentError("`X` and `A` should have the same shape.")) for j in axes(X, 2) @@ -985,24 +1122,28 @@ function _col_permutation!(X::Matrix{T}, A::Matrix{T}, p::AbstractVector{Int}) w return nothing end -function _col_permutation_symp!(X::Matrix{T}, A::Matrix{T}, p::AbstractVector{Int}) where T +function _col_permutation_symp!( + X::Matrix{T}, + A::Matrix{T}, + p::AbstractVector{Int}, +) where {T} n = length(p) # 2n == size(A, 2) || throw(ArgumentError("`p` should have length `size(A, 2)/2`.")) # size(X) == size(A) || throw(ArgumentError("`X` and `A` should have the same shape.")) - for j in 1:n + for j = 1:n for i in axes(X, 1) X[i, j] = A[i, p[j]] end end - for j in 1:n + for j = 1:n for i in axes(X, 1) - X[i, j + n] = A[i, p[j] + n] + X[i, j+n] = A[i, p[j]+n] end end return nothing end -function digits_to_int(x::Vector{Int}, base::Int=2) +function digits_to_int(x::Vector{Int}, base::Int = 2) res = 0 for digit in x res = digit + base * res @@ -1010,7 +1151,7 @@ function digits_to_int(x::Vector{Int}, base::Int=2) return res end -function _CT_adjoint(A::MatElem{T}) where T <: ResElem +function _CT_adjoint(A::MatElem{T}) where {T<:ResElem} R = parent(A[1, 1]) S = base_ring(A[1, 1]) f = modulus(R) @@ -1019,10 +1160,10 @@ function _CT_adjoint(A::MatElem{T}) where T <: ResElem A_tr = transpose(A) nr, nc = size(A_tr) - for c in 1:nc - for r in 1:nr + for c = 1:nc + for r = 1:nr h_coeffs = collect(coefficients(Nemo.lift(A_tr[r, c]))) - for _ in 1:l - length(h_coeffs) + for _ = 1:(l-length(h_coeffs)) push!(h_coeffs, Fz) end h_coeffs[2:end] = reverse(h_coeffs[2:end]) @@ -1032,7 +1173,7 @@ function _CT_adjoint(A::MatElem{T}) where T <: ResElem return A_tr end -function _CT_adjoint(A::MatElem{T}) where T <: CTGroupAlgebra +function _CT_adjoint(A::MatElem{T}) where {T<:CTGroupAlgebra} FG = parent(A[1, 1]) f = hom(FG, FG, basis_matrix([inv(g) for g in basis(FG)])) # for each element of A, map the sum \sum_i c_i g_i to \sum_i c_i (g_i)^-1 @@ -1044,7 +1185,7 @@ end Return the circulant matrix whose first row or column is the coefficients of `f` if `type` is `:row` or `:col`, respectively. """ -function residue_polynomial_to_circulant_matrix(f::ResElem, type::Symbol=:col) +function residue_polynomial_to_circulant_matrix(f::ResElem, type::Symbol = :col) type ∈ (:col, :row) || throw(ArgumentError("Unknown type")) R = parent(f) @@ -1061,19 +1202,19 @@ function residue_polynomial_to_circulant_matrix(f::ResElem, type::Symbol=:col) temp = collect(coefficients(Nemo.lift(f))) F_coeffs[1:length(temp), 1] = temp A[:, 1] = F_coeffs - for c in 2:l + for c = 2:l # A[:, c] = circshift(F_coeffs, c - 1) - A[1:c - 1, c] = F_coeffs[l - (c - 1) + 1:l, 1] - A[c:end, c] = F_coeffs[1:l - (c - 1), 1] + A[1:(c-1), c] = F_coeffs[(l-(c-1)+1):l, 1] + A[c:end, c] = F_coeffs[1:(l-(c-1)), 1] end elseif type == :row F_coeffs = zero_matrix(F, 1, l) temp = collect(coefficients(Nemo.lift(f))) F_coeffs[1, 1:length(temp)] = temp A[1, :] = F_coeffs - for c in 2:l - A[c, 1:c - 1] = F_coeffs[1, l - (c - 1) + 1:l] - A[c, c:end] = F_coeffs[1, 1:l - (c - 1)] + for c = 2:l + A[c, 1:(c-1)] = F_coeffs[1, (l-(c-1)+1):l] + A[c, c:end] = F_coeffs[1, 1:(l-(c-1))] end end return A @@ -1084,9 +1225,9 @@ end Return the circulant matrix whose first row or column is the coefficients of `x` if `type` is `:row` or `:col`, respectively. """ -function group_algebra_element_to_circulant_matrix(x::CTGroupAlgebra, type::Symbol=:col) +function group_algebra_element_to_circulant_matrix(x::CTGroupAlgebra, type::Symbol = :col) type ∈ (:col, :row) || throw(ArgumentError("Unknown type")) - + F = base_ring(parent(x)) F_coeffs = coefficients(x) l = length(F_coeffs) @@ -1094,16 +1235,16 @@ function group_algebra_element_to_circulant_matrix(x::CTGroupAlgebra, type::Symb if type == :col F_coeffs = matrix(F, l, 1, F_coeffs) A[:, 1] = F_coeffs - for c in 2:l - A[1:c - 1, c] = F_coeffs[l - (c - 1) + 1:l, 1] - A[c:end, c] = F_coeffs[1:l - (c - 1), 1] + for c = 2:l + A[1:(c-1), c] = F_coeffs[(l-(c-1)+1):l, 1] + A[c:end, c] = F_coeffs[1:(l-(c-1)), 1] end elseif type == :row F_coeffs = matrix(F, 1, l, F_coeffs) A[1, :] = F_coeffs - for c in 2:l - A[c, 1:c - 1] = F_coeffs[1, l - (c - 1) + 1:l] - A[c, c:end] = F_coeffs[1, 1:l - (c - 1)] + for c = 2:l + A[c, 1:(c-1)] = F_coeffs[1, (l-(c-1)+1):l] + A[c, c:end] = F_coeffs[1, 1:(l-(c-1))] end end return A @@ -1115,7 +1256,7 @@ end Return the matrix whose residue polynomial elements are converted to circulant matrices over the base field. """ -function lift(A::MatElem{T}, type::Symbol=:col) where T <: ResElem +function lift(A::MatElem{T}, type::Symbol = :col) where {T<:ResElem} type ∈ (:col, :row) || throw(ArgumentError("Unknown type")) R = parent(A[1, 1]) @@ -1131,7 +1272,7 @@ function lift(A::MatElem{T}, type::Symbol=:col) where T <: ResElem for c in axes(A, 2) for r in axes(A, 1) if !iszero(A[r, c]) - A_lift[(r - 1) * l + 1:r * l, (c - 1) * l + 1:c * l] = + A_lift[((r-1)*l+1):(r*l), ((c-1)*l+1):(c*l)] = residue_polynomial_to_circulant_matrix(A[r, c], type) end end @@ -1145,7 +1286,7 @@ end Return the matrix whose group algebra elements are converted to circulant matrices over the base field. """ -function lift(A::MatElem{T}, type::Symbol=:col) where T <: CTGroupAlgebra +function lift(A::MatElem{T}, type::Symbol = :col) where {T<:CTGroupAlgebra} type ∈ (:col, :row) || throw(ArgumentError("Unknown type")) F = base_ring(parent(A[1, 1])) @@ -1155,7 +1296,7 @@ function lift(A::MatElem{T}, type::Symbol=:col) where T <: CTGroupAlgebra for c in axes(A, 2) for r in axes(A, 1) if !iszero(A[r, c]) - A_lift[(r - 1) * l + 1:r * l, (c - 1) * l + 1:c * l] = + A_lift[((r-1)*l+1):(r*l), ((c-1)*l+1):(c*l)] = group_algebra_element_to_circulant_matrix(A[r, c], type) end end @@ -1164,15 +1305,15 @@ function lift(A::MatElem{T}, type::Symbol=:col) where T <: CTGroupAlgebra end # Creates a matrix with copies of `M` at every nonzero entry of `locations`. -function _concat(locations::Union{CTMatrixTypes, Matrix}, M::CTMatrixTypes) +function _concat(locations::Union{CTMatrixTypes,Matrix}, M::CTMatrixTypes) nr_M, nc_M = size(M) nr_L, ncL = size(locations) output = zero_matrix(base_ring(M), nr_M * nr_L, nc_M * ncL) - for j_outer in 1:ncL - for i_outer in 1:nr_L + for j_outer = 1:ncL + for i_outer = 1:nr_L if !iszero(locations[i_outer, j_outer]) - for j in 1:nc_M - for i in 1:nr_M + for j = 1:nc_M + for i = 1:nr_M row = i + nr_M * (i_outer - 1) col = j + nc_M * (j_outer - 1) output[row, col] = M[i, j] @@ -1190,8 +1331,9 @@ end Returns a vector where the ith entry lists the indices of the nonzero entries of `M[i, :]` """ -function row_supports(M::Union{CTMatrixTypes, - MatElem{EuclideanRingResidueRingElem{fpPolyRingElem}}}) +function row_supports( + M::Union{CTMatrixTypes,MatElem{EuclideanRingResidueRingElem{fpPolyRingElem}}}, +) output = [Int[] for _ in axes(M, 1)] for j in axes(M, 2) @@ -1212,15 +1354,15 @@ function row_supports_symplectic(M::CTMatrixTypes) iseven(ncols(M)) || throw(ArgumentError("Matrix should have an even number of cols")) n = div(ncols(M), 2) X = row_supports(view(M, :, 1:n)) - Z = row_supports(view(M, :, 1 + n:2n)) + Z = row_supports(view(M, :, (1+n):2n)) collect(zip(X, Z)) end function _node_adjacencies(H::CTMatrixTypes) - check_adj_list = [Int[] for _ in 1:nrows(H)] - var_adj_list = [Int[] for _ in 1:ncols(H)] - for r in 1:nrows(H) - for c in 1:ncols(H) + check_adj_list = [Int[] for _ = 1:nrows(H)] + var_adj_list = [Int[] for _ = 1:ncols(H)] + for r = 1:nrows(H) + for c = 1:ncols(H) if !iszero(H[r, c]) push!(check_adj_list[r], c) push!(var_adj_list[c], r) @@ -1246,7 +1388,7 @@ function strongly_lower_triangular_reduction(A::CTMatrixTypes) id_mat = identity_matrix(F, nc) κ = deepcopy(id_mat) π = collect(1:nc) - for j in 1:nc + for j = 1:nc i = 1 while i < nr && !isone(B[i, j]) i += 1 @@ -1255,7 +1397,7 @@ function strongly_lower_triangular_reduction(A::CTMatrixTypes) if isone(B[i, j]) # more natural and probably faster to push pivots to a list π = setdiff(π, [j]) - for l in j+1:nc + for l = (j+1):nc if isone(B[i, l]) B[:, l] += B[:, j] κ[:, l] += κ[:, j] @@ -1282,33 +1424,47 @@ Return a `Matrix{Int}` object from the matrix stored in the alist file format in """ function load_alist(file::String) contents = split.(readlines(file)) - length(contents[1]) == 2 || throw(ArgumentError("Not a valid alist file. First line wrong.")) - length(contents[2]) == 2 || throw(ArgumentError("Not a valid alist file. Second line wrong.")) + length(contents[1]) == 2 || + throw(ArgumentError("Not a valid alist file. First line wrong.")) + length(contents[2]) == 2 || + throw(ArgumentError("Not a valid alist file. Second line wrong.")) M = parse(Int, contents[1][1]) N = parse(Int, contents[1][2]) - length(contents) == M + N + 4 || throw(ArgumentError("Not a valid alist file. Wrong number of lines.")) + length(contents) == M + N + 4 || + throw(ArgumentError("Not a valid alist file. Wrong number of lines.")) row_wts = parse.(Int, contents[3]) col_wts = parse.(Int, contents[4]) - length(row_wts) == M || throw(ArgumentError("Not a valid alist file. Wrong number of row weights.")) - length(col_wts) == N || throw(ArgumentError("Not a valid alist file. Wrong number of column weights.")) - maximum(row_wts) == parse(Int, contents[2][1]) || throw(ArgumentError("Not a valid alist file. Row weight mismatch.")) - maximum(col_wts) == parse(Int, contents[2][2]) || throw(ArgumentError("Not a valid alist file. Col weight mismatch.")) - all(allunique, contents[5:end]) || throw(ArgumentError("Not a valid alist file. Indices are repeated.")) - all(length(contents[j]) == row_wts[i] for (i, j) in enumerate(5:M + 4)) || throw(ArgumentError("Not a valid alist file. Row weights don't match.")) - all(length(contents[j]) == col_wts[i] for (i, j) in enumerate(M + 5:M + N + 4)) || throw(ArgumentError("Not a valid alist file. Column weights don't match.")) + length(row_wts) == M || + throw(ArgumentError("Not a valid alist file. Wrong number of row weights.")) + length(col_wts) == N || + throw(ArgumentError("Not a valid alist file. Wrong number of column weights.")) + maximum(row_wts) == parse(Int, contents[2][1]) || + throw(ArgumentError("Not a valid alist file. Row weight mismatch.")) + maximum(col_wts) == parse(Int, contents[2][2]) || + throw(ArgumentError("Not a valid alist file. Col weight mismatch.")) + all(allunique, contents[5:end]) || + throw(ArgumentError("Not a valid alist file. Indices are repeated.")) + all(length(contents[j]) == row_wts[i] for (i, j) in enumerate(5:(M+4))) || + throw(ArgumentError("Not a valid alist file. Row weights don't match.")) + all(length(contents[j]) == col_wts[i] for (i, j) in enumerate((M+5):(M+N+4))) || + throw(ArgumentError("Not a valid alist file. Column weights don't match.")) mat = zeros(Int, M, N) - for (col, i) in enumerate(M + 5:M + N + 4) + for (col, i) in enumerate((M+5):(M+N+4)) rows = parse.(Int, contents[i]) for row in rows mat[row, col] = 1 end end - for (row, i) in enumerate(5:M + 4) + for (row, i) in enumerate(5:(M+4)) cols = parse.(Int, contents[i]) - for col in 1:N - mat[row, col] == (col in cols) || throw(ArgumentError("Not a valid alist file. The two matrix representations don't match.")) + for col = 1:N + mat[row, col] == (col in cols) || throw( + ArgumentError( + "Not a valid alist file. The two matrix representations don't match.", + ), + ) end end return mat @@ -1333,7 +1489,7 @@ end # end ############################# - # Quantum Helper Functions +# Quantum Helper Functions ############################# """ @@ -1346,17 +1502,18 @@ Return `true` if the binary matrix `G` is triorthogonal. * If the optional parameter `verbos` is set to `true`, the first pair or triple of non-orthogonal rows will be identified on the console. """ -function is_triorthogonal(G::CTMatrixTypes, verbose::Bool=false) - Int(order(base_ring(G))) == 2 || throw(ArgumentError("Triothogonality is only defined over 𝔽₂.")) +function is_triorthogonal(G::CTMatrixTypes, verbose::Bool = false) + Int(order(base_ring(G))) == 2 || + throw(ArgumentError("Triothogonality is only defined over 𝔽₂.")) nr, nc = size(G) - for r1 in 1:nr - for r2 in (r1 + 1):nr - if !iszero(sum(G[r1, i] * G[r2, i] for i in 1:nc)) + for r1 = 1:nr + for r2 = (r1+1):nr + if !iszero(sum(G[r1, i] * G[r2, i] for i = 1:nc)) verbose && println("Rows $r1 and $r2 are not orthogonal.") return false end - for r3 in (r2 + 1):nr - if !iszero(sum(G[r1, i] * G[r2, i] * G[r3, i] for i in 1:nc)) + for r3 = (r2+1):nr + if !iszero(sum(G[r1, i] * G[r2, i] * G[r3, i] for i = 1:nc)) verbose && println("Rows $r1, $r2, and $r3 are not orthogonal.") return false end @@ -1366,16 +1523,16 @@ function is_triorthogonal(G::CTMatrixTypes, verbose::Bool=false) return true end -function is_triorthogonal(G::Matrix{Int}, verbose::Bool=false) +function is_triorthogonal(G::Matrix{Int}, verbose::Bool = false) nr, nc = size(G) - for r1 in 1:nr - for r2 in (r1 + 1):nr - if !iszero(sum(G[r1, i] * G[r2, i] for i in 1:nc) % 2) + for r1 = 1:nr + for r2 = (r1+1):nr + if !iszero(sum(G[r1, i] * G[r2, i] for i = 1:nc) % 2) verbose && println("Rows $r1 and $r2 are not orthogonal.") return false end - for r3 in (r2 + 1):nr - if !iszero(sum(G[r1, i] * G[r2, i] * G[r3, i] for i in 1:nc) % 2) + for r3 = (r2+1):nr + if !iszero(sum(G[r1, i] * G[r2, i] * G[r3, i] for i = 1:nc) % 2) verbose && println("Rows $r1, $r2, and $r3 are not orthogonal.") return false end @@ -1385,7 +1542,7 @@ function is_triorthogonal(G::Matrix{Int}, verbose::Bool=false) return true end -function print_string_array(A::Vector{String}, without_Is=false) +function print_string_array(A::Vector{String}, without_Is = false) for a in A if !withoutIs println(a) @@ -1402,8 +1559,10 @@ function print_string_array(A::Vector{String}, without_Is=false) end end # BUG: do these set functions exist anymore? -print_char_array(A::Vector{Vector{Char}}, without_Is=false) = print_string_array(set_char_to_string_array(A), without_Is) -printsymplecticarray(A::Vector{Vector{T}}, without_Is=false) where T <: Int = print_string_array(set_symplectic_to_string_array(A), without_Is) +print_char_array(A::Vector{Vector{Char}}, without_Is = false) = + print_string_array(set_char_to_string_array(A), without_Is) +printsymplecticarray(A::Vector{Vector{T}}, without_Is = false) where {T<:Int} = + print_string_array(set_symplectic_to_string_array(A), without_Is) """ pseudoinverse(M::CTMatrixTypes) @@ -1424,18 +1583,23 @@ function pseudoinverse(M::CTMatrixTypes) nr, nc = size(M) _, E = rref(hcat(M, identity_matrix(base_ring(M), nr))) - E = E[:, (nc + 1):end] + E = E[:, (nc+1):end] p_inv = E[1:nc, :] - dual = E[nc + 1:nr, :] + dual = E[(nc+1):nr, :] # verify _, M_rref = rref(M) E * M == M_rref || error("Pseudoinverse calculation failed (transformation incorrect).") - M_rref[1:nc, 1:nc] == identity_matrix(base_ring(M), nc) || error("Pseudoinverse calculation failed (failed to get I).") - iszero(M_rref[nc + 1:nr, :]) || error("Pseudoinverse calculation failed (failed to get zero).") - p_inv * M == identity_matrix(base_ring(M), nc) || error("Pseudoinverse calculation failed (eq 1).") - transpose(M) * transpose(p_inv) == identity_matrix(base_ring(M), nc) || error("Pseudoinverse calculation failed (eq 2).") - iszero(transpose(M) * transpose(dual)) || error("Failed to correctly compute dual (rhs).") + M_rref[1:nc, 1:nc] == identity_matrix(base_ring(M), nc) || + error("Pseudoinverse calculation failed (failed to get I).") + iszero(M_rref[(nc+1):nr, :]) || + error("Pseudoinverse calculation failed (failed to get zero).") + p_inv * M == identity_matrix(base_ring(M), nc) || + error("Pseudoinverse calculation failed (eq 1).") + transpose(M) * transpose(p_inv) == identity_matrix(base_ring(M), nc) || + error("Pseudoinverse calculation failed (eq 2).") + iszero(transpose(M) * transpose(dual)) || + error("Failed to correctly compute dual (rhs).") iszero(dual * M) || error("Failed to correctly compute dual (lhs).") return p_inv end @@ -1486,7 +1650,7 @@ end # return Mquad # end -function _Pauli_string_to_symplectic(str::T) where T <: Union{String, Vector{Char}} +function _Pauli_string_to_symplectic(str::T) where {T<:Union{String,Vector{Char}}} n = length(str) # F = GF(2, 1, :ω) F = Oscar.Nemo.Native.GF(2) @@ -1495,21 +1659,24 @@ function _Pauli_string_to_symplectic(str::T) where T <: Union{String, Vector{Cha if c == 'X' sym[1, i] = F(1) elseif c == 'Z' - sym[1, i + n] = F(1) + sym[1, i+n] = F(1) elseif c == 'Y' sym[1, i] = 1 - sym[1, i + n] = F(1) + sym[1, i+n] = F(1) elseif c != 'I' - error("Encountered non-{I, X, Y, Z} character in Pauli string. This function is only defined for binary strings.") + error( + "Encountered non-{I, X, Y, Z} character in Pauli string. This function is only defined for binary strings.", + ) end end return sym end -_Pauli_string_to_symplectic(A::Vector{T}) where T <: Union{String, Vector{Char}} = reduce(vcat, [_Pauli_string_to_symplectic(s) for s in A]) +_Pauli_string_to_symplectic(A::Vector{T}) where {T<:Union{String,Vector{Char}}} = + reduce(vcat, [_Pauli_string_to_symplectic(s) for s in A]) # need symplectictoPaulistring # charvec::Union{Vector{zzModRingElem}, Missing}=missing) -function _process_strings(SPauli::Vector{T}) where T <: Union{String, Vector{Char}} +function _process_strings(SPauli::Vector{T}) where {T<:Union{String,Vector{Char}}} # Paulisigns = Vector{Int}() S_tr_Pauli_stripped = Vector{String}() for (i, s) in enumerate(SPauli) @@ -1523,14 +1690,17 @@ function _process_strings(SPauli::Vector{T}) where T <: Union{String, Vector{Cha # append!(Paulisigns, -1) push!(S_tr_Pauli_stripped, s[2:end]) else - error("The first element of Pauli string $i is neither a Pauli character or +/-: $s.") + error( + "The first element of Pauli string $i is neither a Pauli character or +/-: $s.", + ) end end n = length(S_tr_Pauli_stripped[1]) for s in S_tr_Pauli_stripped for i in s - i ∈ ['I', 'X', 'Y', 'Z'] || error("Element of provided Pauli string is not a Pauli character: $s.") + i ∈ ['I', 'X', 'Y', 'Z'] || + error("Element of provided Pauli string is not a Pauli character: $s.") end length(s) == n || error("Not all Pauli strings are the same length.") end @@ -1549,7 +1719,7 @@ function _process_strings(SPauli::Vector{T}) where T <: Union{String, Vector{Cha end ############################# - # Finite Fields +# Finite Fields ############################# """ @@ -1569,10 +1739,14 @@ function tr(x::CTFieldElem, K::CTFieldTypes; verify::Bool = false) # Int(characteristic(L)) == Int(characteristic(K)) || error("The given field is not a subfield of the base ring of the element.") # degree(L) % degree(K) == 0 || error("The given field is not a subfield of the base ring of the element.") flag, m = is_extension(L, K) - flag || throw(ArgumentError("The given field is not a subfield of the base ring of the matrix.")) + flag || throw( + ArgumentError( + "The given field is not a subfield of the base ring of the matrix.", + ), + ) end n = div(degree(L), degree(K)) - return sum([x^(q^i) for i in 0:(n - 1)]) + return sum([x^(q^i) for i = 0:(n-1)]) end # function _expandelement(x::CTFieldElem, K::CTFieldTypes, basis::Vector{<:CTFieldElem}, verify::Bool=false) @@ -1592,7 +1766,7 @@ end function _expansion_dict(L::CTFieldTypes, K::CTFieldTypes, λ::Vector{<:CTFieldElem}) m = div(degree(L), degree(K)) L_elms = collect(L) - D = Dict{FqFieldElem, FqMatrix}() + D = Dict{FqFieldElem,FqMatrix}() for x in L_elms D[x] = matrix(L, 1, m, [CodingTheory.tr(x * λi, K) for λi in λ]) end @@ -1600,13 +1774,13 @@ function _expansion_dict(L::CTFieldTypes, K::CTFieldTypes, λ::Vector{<:CTFieldE end # BUG this is building the expanded matrix in the wrong ring, added change_base_ring below -function _expand_matrix(M::CTMatrixTypes, D::Dict{FqFieldElem, FqMatrix}, m::Int) +function _expand_matrix(M::CTMatrixTypes, D::Dict{FqFieldElem,FqMatrix}, m::Int) m > 0 || throw(DomainError("Expansion factor must be positive")) M_exp = zero_matrix(base_ring(M), nrows(M), ncols(M) * m) - for r in 1:nrows(M) - for c in 1:ncols(M) - M_exp[r, (c - 1) * m + 1:c * m] = D[M[r, c]] + for r = 1:nrows(M) + for c = 1:ncols(M) + M_exp[r, ((c-1)*m+1):(c*m)] = D[M[r, c]] end end return M_exp @@ -1622,8 +1796,11 @@ function expand_matrix(M::CTMatrixTypes, K::CTFieldTypes, β::Vector{<:CTFieldEl L = base_ring(M) L == K && return M flag, m = is_extension(L, K) - flag || throw(ArgumentError("The given field is not a subfield of the base ring of the matrix.")) - m == length(β) || throw(ArgumentError("Basis does not have length degree of the extension.")) + flag || throw( + ArgumentError("The given field is not a subfield of the base ring of the matrix."), + ) + m == length(β) || + throw(ArgumentError("Basis does not have length degree of the extension.")) flag, λ = _is_basis(L, β, Int(order(K))) flag || throw(ArgumentError("The provided vector is not a basis for the extension.")) @@ -1638,8 +1815,10 @@ end Return the sets of quadratic resides and quadratic non-residues of `q` and `n`. """ function quadratic_residues(q::Int, n::Int) - isodd(n) && is_prime(n) || throw(ArgumentError("n must be an odd prime in quadratic residues")) - q^div(n - 1, 2) % n == 1 || throw(ArgumentError("q^(n - 1)/2 ≅ 1 mod n in quadratic residues")) + isodd(n) && is_prime(n) || + throw(ArgumentError("n must be an odd prime in quadratic residues")) + q^div(n - 1, 2) % n == 1 || + throw(ArgumentError("q^(n - 1)/2 ≅ 1 mod n in quadratic residues")) # F = GF(n, 1, :α) # elms = collect(F) @@ -1649,24 +1828,24 @@ function quadratic_residues(q::Int, n::Int) # return q_res, not_q_res # don't want this returning in the field - q_res = sort!(unique!([i^2 % n for i in 1:n - 1])) - not_q_res = setdiff(1:(n - 1), q_res) + q_res = sort!(unique!([i^2 % n for i = 1:(n-1)])) + not_q_res = setdiff(1:(n-1), q_res) return q_res, not_q_res end function _is_basis(E::CTFieldTypes, basis::Vector{<:CTFieldElem}, q::Int) m = length(basis) B = zero_matrix(E, m, m) - for r in 1:m - for c in 1:m + for r = 1:m + for c = 1:m B[r, c] = basis[r]^(q^(c - 1)) end end iszero(det(B)) && return false, missing - + try B_inv = inv(B) - λ = [B_inv[1, i] for i in 1:m] + λ = [B_inv[1, i] for i = 1:m] return true, λ catch return false, missing @@ -1712,9 +1891,11 @@ otherwise return `false, missing`. function is_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CTFieldElem}) flag, m = is_extension(E, F) flag || throw(ArgumentError("Second field is not a subfield of the first.")) - length(basis) == m || throw(ArgumentError("Basis does not have length degree of the extension.")) - for i in 1:m - parent(basis[i]) == E || throw(ArgumentError("The basis must be elements of the extension field.")) + length(basis) == m || + throw(ArgumentError("Basis does not have length degree of the extension.")) + for i = 1:m + parent(basis[i]) == E || + throw(ArgumentError("The basis must be elements of the extension field.")) end return _is_basis(E, basis, Int(order(F))) @@ -1729,7 +1910,7 @@ function primitive_basis(E::CTFieldTypes, F::CTFieldTypes) flag, m = is_extension(E, F) flag || throw(ArgumentError("Second field is not a subfield of the first.")) α = gen(E) - basis = [α^i for i in 0:m - 1] + basis = [α^i for i = 0:(m-1)] flag, λ = _is_basis(E, basis, Int(order(F))) return basis, λ end @@ -1751,7 +1932,7 @@ function normal_basis(E::CTFieldTypes, F::CTFieldTypes) q = Int(order(F)) elms = collect(E) for e in elms - basis = [e^(q^i) for i in 0:m - 1] + basis = [e^(q^i) for i = 0:(m-1)] flag, dual_basis = _is_basis(E, basis, q) flag && return basis, dual_basis end @@ -1769,7 +1950,8 @@ function dual_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CTFieldEle flag || throw(ArgumentError("The provided vector is not a basis for the extension.")) return λ end -complementary_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CTFieldElem}) = dual_basis(E, F, basis) +complementary_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CTFieldElem}) = + dual_basis(E, F, basis) """ verify_dual_basis(E::fqPolyRepField, F::fqPolyRepField, basis::Vector{fqPolyRepFieldElem}, dual_basis::Vector{fqPolyRepFieldElem}) @@ -1777,34 +1959,47 @@ complementary_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CTFieldEle Return `true` if `basis` is the dual of `dual_basis` for `E/F`, otherwise return `false`. """ -function verify_dual_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CTFieldElem}, dual_basis::Vector{<:CTFieldElem}) +function verify_dual_basis( + E::CTFieldTypes, + F::CTFieldTypes, + basis::Vector{<:CTFieldElem}, + dual_basis::Vector{<:CTFieldElem}, +) flag, m = is_extension(E, F) flag || throw(ArgumentError("Second field is not a subfield of the first.")) m = length(basis) - length(dual_basis) == m || throw(ArgumentError("The basis and dual basis must have the same length.")) + length(dual_basis) == m || + throw(ArgumentError("The basis and dual basis must have the same length.")) E = parent(basis[1]) - for i in 1:m - parent(basis[i]) == E || throw(ArgumentError("Elements must be over the same field.")) - parent(dual_basis[i]) == E || throw(ArgumentError("Elements must be over the same field.")) + for i = 1:m + parent(basis[i]) == E || + throw(ArgumentError("Elements must be over the same field.")) + parent(dual_basis[i]) == E || + throw(ArgumentError("Elements must be over the same field.")) end q = Int(order(F)) B = zero_matrix(E, m, m) - for r in 1:m - for c in 1:m + for r = 1:m + for c = 1:m B[r, c] = basis[r]^(q^(c - 1)) end end B_inv = zero_matrix(E, m, m) - for r in 1:m - for c in 1:m + for r = 1:m + for c = 1:m B_inv[r, c] = dual_basis[c]^(q^(r - 1)) end end return B * B_inv == identity_matrix(E, m) end -verify_complementary_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CTFieldElem}, dual_basis::Vector{<:CTFieldElem}) = verify_dual_basis(E, F, basis, dual_basis) +verify_complementary_basis( + E::CTFieldTypes, + F::CTFieldTypes, + basis::Vector{<:CTFieldElem}, + dual_basis::Vector{<:CTFieldElem}, +) = verify_dual_basis(E, F, basis, dual_basis) """ are_equivalent_basis(basis::Vector{fqPolyRepFieldElem}, basis2::Vector{fqPolyRepFieldElem}) @@ -1813,12 +2008,15 @@ Return `true` if `basis` is a scalar multiple of `basis2`. """ function are_equivalent_basis(basis::Vector{<:CTFieldElem}, basis2::Vector{<:CTFieldElem}) m = length(basis) - length(basis2) == m || throw(ArgumentError("The two vectors must have the same length.")) + length(basis2) == m || + throw(ArgumentError("The two vectors must have the same length.")) c = basis[1] * basis2[1]^-1 E = parent(basis[1]) - for i in 1:m - parent(basis[i]) == E || throw(ArgumentError("Elements must be over the same field.")) - parent(basis2[i]) == E || throw(ArgumentError("Elements must be over the same field.")) + for i = 1:m + parent(basis[i]) == E || + throw(ArgumentError("Elements must be over the same field.")) + parent(basis2[i]) == E || + throw(ArgumentError("Elements must be over the same field.")) # for logical consistency should probably do this in a separate loop basis[i] == c * basis2[i] || return false end @@ -1846,7 +2044,7 @@ function is_primitive_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CT flag || throw(ArgumentError("The provided vector is not a basis for the extension.")) isone(basis[1]) ? (x = basis[2];) : (x = basis[1];) m = length(basis) - for i in 0:m - 1 + for i = 0:(m-1) x^i ∈ basis || return false end return true @@ -1863,7 +2061,7 @@ function is_normal_basis(E::CTFieldTypes, F::CTFieldTypes, basis::Vector{<:CTFie isone(basis[1]) ? (return false;) : (x = basis[1];) m = length(basis) q = Int(order(F)) - for i in 0:m - 1 + for i = 0:(m-1) x^(q^i) ∈ basis || return false end return true @@ -1875,7 +2073,7 @@ end # (Imamura 1983) The finite field F_q^n has no self-dual power bases. ############################# - # Graphs +# Graphs ############################# """ @@ -1899,7 +2097,7 @@ function edge_vertex_incidence_matrix(G::SimpleGraph{Int}) nr, nc = size(I) I_tr = transpose(I) B = vcat(hcat(zeros(Int, nc, nc), I_tr), hcat(I, zeros(Int, nr, nr))) - return B, collect(1:nc), collect(nc + 1:nr + nc) + return B, collect(1:nc), collect((nc+1):(nr+nc)) end """ @@ -1919,7 +2117,8 @@ end Return `true` if the vertices indexed by `left` and `right` form a valid bipartition for `G`. """ function is_valid_bipartition(G::SimpleGraph{Int}, left::Vector{Int}, right::Vector{Int}) - Grphs.nv(G) == length(left) + length(right) || throw(ArgumentError("Too few vertices in lists.")) + Grphs.nv(G) == length(left) + length(right) || + throw(ArgumentError("Too few vertices in lists.")) l = sort(left) r = sort(right) temp = l ∩ r # can manually do using sorted knowledge if this is slow @@ -1966,7 +2165,7 @@ function _rand_invertible_matrix(F::CTFieldTypes, n::Integer) A = matrix(F, 1, 1, [rand(collect(F)[2:end])]) # extend from (k-1)×(k-1) to k×k, repeat up to n×n - for k in 2:n + for k = 2:n # pick a random nonzero vector of length n v = zero_matrix(F, 1, k) @@ -1984,8 +2183,8 @@ function _rand_invertible_matrix(F::CTFieldTypes, n::Integer) # copy data from A into the right places B = zero_matrix(F, k, k) B[1, r] = one(F) - B[2:end, 1:r - 1] = A[:, 1:r - 1] - B[2:end, r + 1:end] = A[:, r:end] + B[2:end, 1:(r-1)] = A[:, 1:(r-1)] + B[2:end, (r+1):end] = A[:, r:end] A = B * I_v end @@ -1993,12 +2192,14 @@ function _rand_invertible_matrix(F::CTFieldTypes, n::Integer) return A end -function extended_binomial(x::Union{Int, UInt}, y::Union{Int, UInt}) +function extended_binomial(x::Union{Int,UInt}, y::Union{Int,UInt}) return y <= x ? UInt128.(binomial(x, y)) : UInt128(0) end function _value_distribution(vals) - return OrderedDict([(i, count(x -> (x == i), vals)) for i in collect(sort(unique(vals)))]) + return OrderedDict([ + (i, count(x -> (x == i), vals)) for i in collect(sort(unique(vals))) + ]) end # #= diff --git a/test/Classical/GRS_alternate_test.jl b/test/Classical/GRS_alternate_test.jl index 2c9df752..e7c90ead 100644 --- a/test/Classical/GRS_alternate_test.jl +++ b/test/Classical/GRS_alternate_test.jl @@ -9,8 +9,8 @@ # MacWilliams & Sloane, p. 335 E = GF(8) α = gen(E) - γ = [α^i for i in 0:6] - v = [E(1) for _ in 1:7] + γ = [α^i for i = 0:6] + v = [E(1) for _ = 1:7] A = AlternateCode(GF(2), 2, v, γ) @test length(A) == 7 @test dimension(A) == 3 @@ -51,13 +51,13 @@ n = 6 α = gen(E) # α is root of α^3 + α + 1 = 0 - v = [E(1) for _ in 1:n] + v = [E(1) for _ = 1:n] γ = [α, α^2, α^3, α^4, α^5, α^6] A = AlternateCode(GF(2), 3, v, γ) @test length(A) == 6 @test dimension(A) == 2 @test minimum_distance(A) == 4 - + # TODO write tests for GRS(Γ), GRS(A), etc end @@ -67,20 +67,20 @@ α = gen(E) a = [E(0), E(1), α^9, α^18, α^27, α^36, α^45, α^54] w = [α] - z = [E(1) for _ in 1:8] + z = [E(1) for _ = 1:8] F = GF(2) C = GeneralizedSrivastavaCode(F, a, w, z, 2) @test Int(order(field(C))) == 2 @test length(C) == 8 @test dimension(C) == 2 @test minimum_distance(C) == 5 - + # from Goppa_test.jl E2 = GF(8, :α) S, z = polynomial_ring(E2, :z) β = gen(E2) g = β^3 + z + z^2 - L = [E2(0); [β^i for i in 0:6]] + L = [E2(0); [β^i for i = 0:6]] C2 = GoppaCode(F, L, g) flag, _ = are_permutation_equivalent(C, C2) @test_broken flag @@ -91,7 +91,7 @@ α = gen(E) w = [E(0), E(1)] a = setdiff(collect(E), w) - z = [E(1) for _ in 1:length(a)] + z = [E(1) for _ = 1:length(a)] C = GeneralizedSrivastavaCode(F, a, w, z, 2) @test length(C) == 14 @test dimension(C) == 6 diff --git a/test/Classical/Goppa_test.jl b/test/Classical/Goppa_test.jl index 8aab6b06..b5cf3877 100644 --- a/test/Classical/Goppa_test.jl +++ b/test/Classical/Goppa_test.jl @@ -10,7 +10,7 @@ # julia> minimal_polynomial(α) # x^3 + x + 1 g = α^3 + z + z^2 - L = [E(0); [α^i for i in 0:6]] + L = [E(0); [α^i for i = 0:6]] F = GF(2) C = GoppaCode(F, L, g) @test length(C) == 8 @@ -20,7 +20,7 @@ # Ling & Xing, Corollary 9.3.4, p. 198 n = length(L) # v = [g(a)^(-1) for a in L] - v = [g(L[i]) * prod(L[i] - L[j] for j in 1:n if i ≠ j)^-1 for i in 1:n] + v = [g(L[i]) * prod(L[i] - L[j] for j = 1:n if i ≠ j)^-1 for i = 1:n] t = degree(g) C2 = AlternateCode(F, n - t, v, L) # TODO I highly suspect this result comes from using different bases and scalars throughout different books and the expansion is highly basis dependent @@ -66,7 +66,7 @@ E = GF(2^5, :α) S, z = polynomial_ring(E, :z) α = gen(E) - L = [E(0); [α^i for i in 0:Int(order(E)) - 2]] + L = [E(0); [α^i for i = 0:(Int(order(E))-2)]] g = z^3 + z + 1 C = GoppaCode(F, L, g) @test is_irreducible(C) @@ -79,7 +79,7 @@ S, z = polynomial_ring(E, :z) α = gen(E) g = z^2 + z + α^3 - L = [E(0); [α^i for i in 0:Int(order(E)) - 2]] + L = [E(0); [α^i for i = 0:(Int(order(E))-2)]] C = GoppaCode(GF(2), L, g) @test is_irreducible(C) @test length(C) == 16 @@ -91,7 +91,7 @@ S, z = polynomial_ring(E, :z) α = gen(E) g = z^3 + z + 1 - L = [α^i for i in 0:14] + L = [α^i for i = 0:14] C = GoppaCode(GF(2), L, g) @test length(C) == 15 @test dimension(C) == 3 diff --git a/test/Classical/ReedMuller_test.jl b/test/Classical/ReedMuller_test.jl index 690b7541..1009db1a 100644 --- a/test/Classical/ReedMuller_test.jl +++ b/test/Classical/ReedMuller_test.jl @@ -5,41 +5,69 @@ F = Oscar.Nemo.Native.GF(2) # Huffman, Pless, p. 34 # identity used for RM(1, 1) - @test CodingTheory._Reed_Muller_generator_matrix(1, 1, true) == matrix(F, - [1 0; - 0 1]); - @test generator_matrix(ReedMullerCode(1, 2, true)) == matrix(F, - [1 0 1 0; - 0 1 0 1; - 0 0 1 1]); - @test generator_matrix(ReedMullerCode(1, 3, true)) == matrix(F, - [1 0 1 0 1 0 1 0; - 0 1 0 1 0 1 0 1; - 0 0 1 1 0 0 1 1; - 0 0 0 0 1 1 1 1]) - @test generator_matrix(ReedMullerCode(2, 3, true)) == matrix(F, - [1 0 0 0 1 0 0 0; - 0 1 0 0 0 1 0 0; - 0 0 1 0 0 0 1 0; - 0 0 0 1 0 0 0 1; - 0 0 0 0 1 0 1 0; - 0 0 0 0 0 1 0 1; - 0 0 0 0 0 0 1 1]) + @test CodingTheory._Reed_Muller_generator_matrix(1, 1, true) == matrix( + F, + [ + 1 0; + 0 1 + ], + ); + @test generator_matrix(ReedMullerCode(1, 2, true)) == matrix( + F, + [ + 1 0 1 0; + 0 1 0 1; + 0 0 1 1 + ], + ); + @test generator_matrix(ReedMullerCode(1, 3, true)) == matrix( + F, + [ + 1 0 1 0 1 0 1 0; + 0 1 0 1 0 1 0 1; + 0 0 1 1 0 0 1 1; + 0 0 0 0 1 1 1 1 + ], + ) + @test generator_matrix(ReedMullerCode(2, 3, true)) == matrix( + F, + [ + 1 0 0 0 1 0 0 0; + 0 1 0 0 0 1 0 0; + 0 0 1 0 0 0 1 0; + 0 0 0 1 0 0 0 1; + 0 0 0 0 1 0 1 0; + 0 0 0 0 0 1 0 1; + 0 0 0 0 0 0 1 1 + ], + ) # Ling & Xing, p. 119 # other sources, using [1 1; 0 1] for RM(1, 1) - @test CodingTheory._Reed_Muller_generator_matrix(1, 1) == matrix(F, - [1 1; - 0 1]); - @test generator_matrix(ReedMullerCode(1, 2)) == matrix(F, - [1 1 1 1; - 0 1 0 1; - 0 0 1 1]); - @test generator_matrix(ReedMullerCode(1, 3)) == matrix(F, - [1 1 1 1 1 1 1 1; - 0 1 0 1 0 1 0 1; - 0 0 1 1 0 0 1 1; - 0 0 0 0 1 1 1 1]) + @test CodingTheory._Reed_Muller_generator_matrix(1, 1) == matrix( + F, + [ + 1 1; + 0 1 + ], + ); + @test generator_matrix(ReedMullerCode(1, 2)) == matrix( + F, + [ + 1 1 1 1; + 0 1 0 1; + 0 0 1 1 + ], + ); + @test generator_matrix(ReedMullerCode(1, 3)) == matrix( + F, + [ + 1 1 1 1 1 1 1 1; + 0 1 0 1 0 1 0 1; + 0 0 1 1 0 0 1 1; + 0 0 0 0 1 1 1 1 + ], + ) end @testset "self-dual property" begin @@ -75,7 +103,7 @@ @testset "Nested and Even-weight Property" begin # Reed-Muller codes are nested m = rand(3:6) - r = rand(1:m - 2) + r = rand(1:(m-2)) C = ReedMullerCode(r, m) C2 = ReedMullerCode(r + 1, m) @test C ⊆ C2 @@ -96,15 +124,15 @@ sup = support(C) flag = true for i in sup - if isodd(i) - flag = false - break - end + if isodd(i) + flag = false + break + end end @test flag == true C = ReedMullerCode(2, 5) - @test weight_distribution(C, alg = :auto, compact = true) == [(32, 1), (24, 620), - (20, 13888), (16, 36518), (12, 13888), (8, 620), (0, 1)] + @test weight_distribution(C, alg = :auto, compact = true) == + [(32, 1), (24, 620), (20, 13888), (16, 36518), (12, 13888), (8, 620), (0, 1)] end end diff --git a/test/Classical/TwistedReedSolomon_test.jl b/test/Classical/TwistedReedSolomon_test.jl index 5b01d1ec..1845e0f6 100644 --- a/test/Classical/TwistedReedSolomon_test.jl +++ b/test/Classical/TwistedReedSolomon_test.jl @@ -18,7 +18,7 @@ η = [setdiff(α, sqs)[1]]; C = TwistedReedSolomonCode(k, α, t, h, η); G = zero_matrix(F, k, length(α)); - for c in 1:length(α) + for c = 1:length(α) G[1, c] = α[c]^0 G[2, c] = α[c]^1 G[3, c] = α[c]^2 + η[1] * α[c]^6 @@ -38,7 +38,7 @@ η = [F(0), ω, ω^2]; C = TwistedReedSolomonCode(k, α, t, h, η); G = zero_matrix(F, k, length(α)); - for c in 1:length(α) + for c = 1:length(α) G[1, c] = α[c]^0 G[2, c] = α[c]^1 G[3, c] = α[c]^2 + η[3] * α[c]^7 diff --git a/test/Classical/concatenation_test.jl b/test/Classical/concatenation_test.jl index 68b860b5..554e4570 100644 --- a/test/Classical/concatenation_test.jl +++ b/test/Classical/concatenation_test.jl @@ -5,16 +5,28 @@ # same field examples come from https://benjamin-hackl.at/downloads/BA-Thesis_Hackl.pdf # "Concatenated Error Correcting Codes: Galois and Binary Concatenation" F = Oscar.Nemo.Native.GF(2) - Ham = matrix(F, 4, 8, [ + Ham = matrix( + F, + 4, + 8, + [ 1 0 0 0 0 1 1 1; 0 1 0 0 1 0 1 1; 0 0 1 0 1 1 0 1; - 0 0 0 1 1 1 1 0]) - G_in = matrix(F, 4, 8, [ + 0 0 0 1 1 1 1 0 + ], + ) + G_in = matrix( + F, + 4, + 8, + [ 1 0 0 0 0 1 0 0; 0 1 0 0 0 0 1 0; 0 0 1 0 1 0 0 1; - 0 0 0 1 1 1 1 0]) + 0 0 0 1 1 1 1 0 + ], + ) # G_out should be the [8, 4, 4] extended binary Hamming code C_Ham = LinearCode(Ham) @test dimension(C_Ham) == 4 @@ -24,59 +36,99 @@ @test dimension(C_in) == 4 @test minimum_distance(C_in) == 2 C = concatenate(C_Ham, C_in) - G_final = matrix(F, 4, 16, [ + G_final = matrix( + F, + 4, + 16, + [ 1 0 0 0 0 1 0 0 0 1 1 1 0 1 0 1; 0 1 0 0 0 0 1 0 1 0 1 1 0 0 1 1; 0 0 1 0 1 0 0 1 1 1 0 1 1 0 0 0; - 0 0 0 1 1 1 1 0 1 1 1 0 1 1 1 1]) + 0 0 0 1 1 1 1 0 1 1 1 0 1 1 1 1 + ], + ) @test generator_matrix(C) == G_final @test_broken minimum_distance(C) == 7 C = concatenate(C_Ham, C_Ham) - G_final = matrix(F, 4, 16, [ + G_final = matrix( + F, + 4, + 16, + [ 1 0 0 0 0 1 1 1 0 1 1 1 1 0 0 0; 0 1 0 0 1 0 1 1 1 0 1 1 0 1 0 0; 0 0 1 0 1 1 0 1 1 1 0 1 0 0 1 0; - 0 0 0 1 1 1 1 0 1 1 1 0 0 0 0 1]) + 0 0 0 1 1 1 1 0 1 1 1 0 0 0 0 1 + ], + ) @test generator_matrix(C) == G_final @test_broken minimum_distance(C) == 8 - G_out = matrix(F, 4, 12, [ + G_out = matrix( + F, + 4, + 12, + [ 1 0 0 0 0 0 1 1 0 1 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 1 1 0 0 1 0 0 0 - 0 0 0 1 0 0 1 1 0 0 1 1]) + 0 0 0 1 0 0 1 1 0 0 1 1 + ], + ) C_out = LinearCode(G_out) @test dimension(C_out) == 4 @test minimum_distance(C_out) == 4 C = concatenate(C_out, C_Ham) - G_final = matrix(F, 4, 24, [ + G_final = matrix( + F, + 4, + 24, + [ 1 0 0 0 0 1 1 1 0 0 1 1 0 0 1 1 0 1 1 0 0 1 1 0; 0 1 0 0 1 0 1 1 1 0 0 0 0 1 1 1 1 0 0 1 1 0 0 1; 0 0 1 0 1 1 0 1 1 1 0 0 1 1 0 0 1 0 0 0 0 1 1 1; - 0 0 0 1 1 1 1 0 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1]) + 0 0 0 1 1 1 1 0 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 + ], + ) @test generator_matrix(C) == G_final @test_broken minimum_distance(C) == 8 - G_out = matrix(F, 4, 12, [ + G_out = matrix( + F, + 4, + 12, + [ 1 0 0 0 1 0 1 1 0 0 1 0; 0 1 0 0 0 1 1 1 1 0 0 0; 0 0 1 0 1 1 1 1 0 1 1 1; - 0 0 0 1 1 1 1 0 1 1 1 0]) + 0 0 0 1 1 1 1 0 1 1 1 0 + ], + ) C_out = LinearCode(G_out) @test dimension(C_out) == 4 @test minimum_distance(C_out) == 5 C = concatenate(C_out, C_Ham) - G_final = matrix(F, 4, 24, [ + G_final = matrix( + F, + 4, + 24, + [ 1 0 0 0 0 1 1 1 1 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1; 0 1 0 0 1 0 1 1 0 1 1 1 1 0 0 0 1 0 0 0 0 1 1 1; 0 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 0 0; - 0 0 0 1 1 1 1 0 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1]) + 0 0 0 1 1 1 1 0 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 + ], + ) @test generator_matrix(C) == G_final @test_broken minimum_distance(C) == 12 # claims this is ExtendedGolayCode(2) but I can't find the equivalence - G_in = matrix(F, 12, 24, [ + G_in = matrix( + F, + 12, + 24, + [ 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 1 0 0 0 1 1; 0 1 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 1 0 0 1 0; 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 1 0 1 0 1 1; @@ -88,14 +140,22 @@ 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 1 1 0 0; 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 1 1 0; 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 1 0 0 0 1 1 0 1; - 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 1 0 0 0 1 1 1]) + 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 1 0 0 0 1 1 1 + ], + ) C_in = LinearCode(G_in) C = concatenate(C_out, C_in) - G_final = matrix(F, 4, 24, [ + G_final = matrix( + F, + 4, + 24, + [ 1 0 0 0 1 0 1 1 0 0 1 0 0 1 0 1 1 1 1 1 1 0 0 0 0 1 0 0 0 1 1 1 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 1 0 1 1 1 1 0 1 1 1 0 0 1 1 0 1 0 0 0 1 0 0 - 0 0 0 1 1 1 1 0 1 1 1 0 1 0 0 1 0 0 0 1 1 0 1 0]) + 0 0 0 1 1 1 1 0 1 1 1 0 1 0 0 1 0 0 0 1 1 0 1 0 + ], + ) @test generator_matrix(C) == G_final @test_broken minimum_distance(C) == 8 diff --git a/test/Classical/cyclic_code_test.jl b/test/Classical/cyclic_code_test.jl index 312b5678..1a59fecf 100644 --- a/test/Classical/cyclic_code_test.jl +++ b/test/Classical/cyclic_code_test.jl @@ -64,7 +64,8 @@ C = BCHCode(2, 31, 5, 1) @test dimension(C) == 21 @test_broken minimum_distance(C) == 5 - @test_broken polynomial(MacWilliams_identity(C, weight_enumerator(C, :Hamming))) == y^31 + 310x^12*y^19 + 527x^16*y^15 + 186x^20*y^11 + @test_broken polynomial(MacWilliams_identity(C, weight_enumerator(C, :Hamming))) == + y^31 + 310x^12*y^19 + 527x^16*y^15 + 186x^20*y^11 # example: Huffman & Pless C = ReedSolomonCode(13, 5, 1) @@ -81,13 +82,15 @@ @test minimum_distance(D) == 9 @test is_MDS(D) == true @test defining_set(D) == [0, 1, 2, 3, 4, 5, 6, 7] - @test generator_polynomial(D) == 3 + 12x + x^2 + 5x^3 + 11x^4 + 4x^5 + 10x^6 + 5x^7 + x^8 + @test generator_polynomial(D) == + 3 + 12x + x^2 + 5x^3 + 11x^4 + 4x^5 + 10x^6 + 5x^7 + x^8 Cc = complement(C) @test length(Cc) == 12 @test dimension(Cc) == 4 @test_broken minimum_distance(Cc) == 9 @test defining_set(Cc) == [0, 5, 6, 7, 8, 9, 10, 11] - @test generator_polynomial(Cc) == 9 + 6x + 12x^2 + 10x^3 + 8x^4 + 6x^5 + 9x^6 + 4x^7 + x^8 + @test generator_polynomial(Cc) == + 9 + 6x + 12x^2 + 10x^3 + 8x^4 + 6x^5 + 9x^6 + 4x^7 + x^8 # example: Huffman & Pless C = ReedSolomonCode(16, 7, 1) @@ -98,7 +101,8 @@ R = polynomial_ring(C) x = gen(R) α = primitive_root(C) - @test generator_polynomial(C) == α^6 + α^9*x + α^6*x^2 + α^4*x^3 + α^14*x^4 + α^10*x^5 + x^6 + @test generator_polynomial(C) == + α^6 + α^9*x + α^6*x^2 + α^4*x^3 + α^14*x^4 + α^10*x^5 + x^6 # example: MacWilliams & Sloane C = ReedSolomonCode(5, 3, 1) @@ -142,7 +146,7 @@ @test C2 ⊆ C @test C2 ⊂ C @test is_subcode(C2, C) - @test C == CyclicCode(16, 15, defining_set([i for i in 0:(0 + 5 - 2)], 16, 15, false)) + @test C == CyclicCode(16, 15, defining_set([i for i = 0:(0+5-2)], 16, 15, false)) @test C == BCHCode(16, 15, 5) @test design_distance(C) == 5 @test is_narrowsense(C) diff --git a/test/Classical/cyclotomic_test.jl b/test/Classical/cyclotomic_test.jl index 8e71c583..60476c38 100644 --- a/test/Classical/cyclotomic_test.jl +++ b/test/Classical/cyclotomic_test.jl @@ -1,7 +1,8 @@ @testitem "Classical/cyclotomic.jl" begin using CodingTheory - @test all_cyclotomic_cosets(2, 15, to_sort = false) == [[0], [1, 2, 4, 8], [3, 6, 12, 9], - [5, 10], [7, 14, 13, 11]] - @test all_cyclotomic_cosets(3, 13, to_sort = true) == [[0], [1, 3, 9], [2, 5, 6], [4, 10, 12] , [7, 8, 11]] + @test all_cyclotomic_cosets(2, 15, to_sort = false) == + [[0], [1, 2, 4, 8], [3, 6, 12, 9], [5, 10], [7, 14, 13, 11]] + @test all_cyclotomic_cosets(3, 13, to_sort = true) == + [[0], [1, 3, 9], [2, 5, 6], [4, 10, 12], [7, 8, 11]] end diff --git a/test/Classical/linear_code_test.jl b/test/Classical/linear_code_test.jl index a7f821ff..513de041 100644 --- a/test/Classical/linear_code_test.jl +++ b/test/Classical/linear_code_test.jl @@ -3,10 +3,15 @@ @testset "Linear Code" begin F = Oscar.Nemo.Native.GF(2) - G = matrix(F, [1 0 0 0 0 1 1; - 0 1 0 0 1 0 1; - 0 0 1 0 1 1 0; - 0 0 0 1 1 1 1]); + G = matrix( + F, + [ + 1 0 0 0 0 1 1; + 0 1 0 0 1 0 1; + 0 0 1 0 1 1 0; + 0 0 0 1 1 1 1 + ], + ); C = LinearCode(G); @test field(C) == F @test length(C) == 7 @@ -43,8 +48,8 @@ @test iszero(syndrome(C, v)) @test is_overcomplete(ZeroCode(5)) @test is_overcomplete(IdentityCode(5), :H) - @test !is_overcomplete(HammingCode(2,3)) - @test !is_overcomplete(HammingCode(2,3), :H) + @test !is_overcomplete(HammingCode(2, 3)) + @test !is_overcomplete(HammingCode(2, 3), :H) # lower rank test G_and_G = vcat(G, G); @@ -94,13 +99,16 @@ C = TetraCode() exC = extend(C) @test generator_matrix(exC) == matrix(field(C), [1 0 1 1 0; 0 1 1 -1 -1]) - @test parity_check_matrix(exC) == matrix(field(C), [1 1 1 1 1; -1 -1 1 0 0; -1 1 0 1 0]) + @test parity_check_matrix(exC) == + matrix(field(C), [1 1 1 1 1; -1 -1 1 0 0; -1 1 0 1 0]) G = matrix(F, [1 1 0 0 1; 0 0 1 1 0]) C = LinearCode(G) - @test generator_matrix(extend(puncture(C, [5]))) == matrix(F, [1 1 0 0 0; 0 0 1 1 0]) + @test generator_matrix(extend(puncture(C, [5]))) == + matrix(F, [1 1 0 0 0; 0 0 1 1 0]) G = matrix(F, [1 0 0 1 1 1; 0 1 0 1 1 1; 0 0 1 1 1 1]) C = LinearCode(G) - @test generator_matrix(puncture(C, [5, 6])) == matrix(F, [1 0 0 1; 0 1 0 1; 0 0 1 1]) + @test generator_matrix(puncture(C, [5, 6])) == + matrix(F, [1 0 0 1; 0 1 0 1; 0 0 1 1]) # shortening examples from Huffman/Pless shC = shorten(C, [5, 6]) shCtest = LinearCode(matrix(F, [1 0 1 0; 0 1 1 0])) @@ -110,7 +118,10 @@ D = Hermitian_dual(C) @test are_equivalent(C, D) # verify our definition of Hermitian_dual is equivalent: - @test are_equivalent(D, LinearCode(Hermitian_conjugate_matrix(generator_matrix(dual(C))))) + @test are_equivalent( + D, + LinearCode(Hermitian_conjugate_matrix(generator_matrix(dual(C)))), + ) C = HammingCode(2, 3) C2 = LinearCode(words(C)) @@ -139,8 +150,8 @@ C3 = permute_code(C, Perm(σ)) #C4 = permute_code(C, S7(σ)) #@test C1.G == C2.G == C3.G == C4.G == C.G[:, σ] - C1 = permute_code(C, [2,1,3,4,5,6,7]) - C2 = permute_code(C, [1,4,3,2,5,6,7]) + C1 = permute_code(C, [2, 1, 3, 4, 5, 6, 7]) + C2 = permute_code(C, [1, 4, 3, 2, 5, 6, 7]) flag, P = are_permutation_equivalent(C1, C2) @test flag @test are_equivalent(permute_code(C1, P), C2) @@ -162,11 +173,11 @@ bool2, permutation2 = CodingTheory._are_perm_equivalent_exhaustive_search(C1, C3) @test !bool2 @test permutation2 === missing - + end @testset "Random Linear Code Functions" begin - C_ham = HammingCode(2, 3) + C_ham = HammingCode(2, 3) @test ncols(C_ham.G) == 7 pivs = random_information_set(C_ham) mat = C_ham.G[:, pivs] @@ -174,12 +185,12 @@ @test ncols(mat) == 4 @test rank(mat) == 4 - C_ham = HammingCode(2, 4) + C_ham = HammingCode(2, 4) number_of_tests = 5 - for i in 1:number_of_tests + for i = 1:number_of_tests rng = CodingTheory.Random.seed!(i) - infoset = random_information_set(C_ham, rng = rng) - @test det(C_ham.G[:, infoset]) != 0 + infoset = random_information_set(C_ham, rng = rng) + @test det(C_ham.G[:, infoset]) != 0 end p = 2 @@ -189,13 +200,13 @@ C = random_linear_code(p, n, k, rng = rng) @test C.n == n @test C.k == k - + rng = CodingTheory.Random.seed!(0) prime_power = p^2 C = random_linear_code(prime_power, n, k, rng = rng) @test C.n == n @test C.k == k - + rng_from_field = CodingTheory.Random.seed!(0) C2 = random_linear_code(GF(p, 2, :x), n, k, rng = rng_from_field) @test C2.n == n @@ -203,10 +214,10 @@ @test C.G == C2.G end - # "On the Schur Product of Vector Spaces over Finite Fields" - # Christiaan Koster - # Lemma 14: If C is cyclic and dim(C) > (1/2)(n + 1), then C * C = F^n + # "On the Schur Product of Vector Spaces over Finite Fields" + # Christiaan Koster + # Lemma 14: If C is cyclic and dim(C) > (1/2)(n + 1), then C * C = F^n - # simplex code itself has dimension k(k + 1)/2 - # + # simplex code itself has dimension k(k + 1)/2 + # end diff --git a/test/Classical/misc_known_codes_test.jl b/test/Classical/misc_known_codes_test.jl index dc510605..b269ad53 100644 --- a/test/Classical/misc_known_codes_test.jl +++ b/test/Classical/misc_known_codes_test.jl @@ -21,8 +21,12 @@ C = HammingCode(2, 7) col = rand(1:length(C)) # columns are 1, 2, ... 2^r - 1 written as binary numerals - @test parity_check_matrix(C)[:, col:col] == matrix(F, length(C) - - dimension(C), 1, reverse(digits(col, base=2, pad=7))) + @test parity_check_matrix(C)[:, col:col] == matrix( + F, + length(C) - dimension(C), + 1, + reverse(digits(col, base = 2, pad = 7)), + ) # should be [2^r - 1, 2^r - 1 - r, 3] @test length(C) == 2^7 - 1 @test dimension(C) == 2^7 - 1 - 7 @@ -33,7 +37,8 @@ @test polynomial(ham_WE) == x^7 + 7*x^3*y^4 + 7*x^4*y^3 + y^7 n = length(C) C.weight_enum = missing - @test polynomial(ham_WE) == divexact((x + y)^n + n*(x + y)^div(n - 1, 2)*(y - x)^div(n + 1, 2), n + 1) + @test polynomial(ham_WE) == + divexact((x + y)^n + n*(x + y)^div(n - 1, 2)*(y - x)^div(n + 1, 2), n + 1) # simplex codes # random simplex code @@ -58,7 +63,10 @@ @test length(C) == 2^4 - 1 @test CodingTheory.dimension(C) == 4 C = SimplexCode(2, 3) - @test MacWilliams_identity(C, weight_enumerator(C, type = :Hamming, alg = :bruteforce)) == ham_WE + @test MacWilliams_identity( + C, + weight_enumerator(C, type = :Hamming, alg = :bruteforce), + ) == ham_WE end @testset "Golay code" begin @@ -68,18 +76,28 @@ C = ExtendedGolayCode(2) @test is_self_dual(C) C.weight_enum = missing - @test polynomial(weight_enumerator(C, type = :Hamming)) == y^24 + 759*x^8*y^16 + 2576*x^12*y^12 + 759*x^16*y^8 + x^24 + @test polynomial(weight_enumerator(C, type = :Hamming)) == + y^24 + 759*x^8*y^16 + 2576*x^12*y^12 + 759*x^16*y^8 + x^24 C = GolayCode(2) C.weight_enum = missing - @test polynomial(weight_enumerator(C, type = :Hamming)) == y^23 + 253*x^7*y^16 + - 506*x^8*y^15 + 1288*x^11*y^12 + 1288*x^12*y^11 + 506*x^15*y^8 + 253*x^16*y^7 + x^23 + @test polynomial(weight_enumerator(C, type = :Hamming)) == + y^23 + + 253*x^7*y^16 + + 506*x^8*y^15 + + 1288*x^11*y^12 + + 1288*x^12*y^11 + + 506*x^15*y^8 + + 253*x^16*y^7 + + x^23 C = ExtendedGolayCode(3) @test is_self_dual(C) # well-known weight enumerators C.weight_enum = missing - @test polynomial(weight_enumerator(C, type = :Hamming)) == y^12 + 264*x^6*y^6 + 440*x^9*y^3 + 24*x^12 + @test polynomial(weight_enumerator(C, type = :Hamming)) == + y^12 + 264*x^6*y^6 + 440*x^9*y^3 + 24*x^12 C = GolayCode(3) - @test polynomial(weight_enumerator(C, type = :Hamming)) == y^11 + 132*x^5*y^6 + 132*x^6*y^5 + 330*x^8*y^3 + 110*x^9*y^2 + 24*x^11 + @test polynomial(weight_enumerator(C, type = :Hamming)) == + y^11 + 132*x^5*y^6 + 132*x^6*y^5 + 330*x^8*y^3 + 110*x^9*y^2 + 24*x^11 # cyclic code with generator polynomial g(x) = -1 + x^2 - x^3 + x^4 + x^5 # and idempotent e(x) = -(x^2 + x^6 + x^7 + x^8 + x^10) # should be eqivalent to the [11, 6, 5] Golay code (maybe permutation?) @@ -88,7 +106,7 @@ C = ExtendedGolayCode(3) C2 = extend(puncture(C, 7), 7) T = identity_matrix(C.F, 12) - T[7,7] = C.F(-1) + T[7, 7] = C.F(-1) C3 = LinearCode(C2.G * T) @test are_equivalent(C, C3) end @@ -99,11 +117,15 @@ C.weight_enum = missing CWE = polynomial(weight_enumerator(C, type = :complete)) vars = gens(parent(CWE)) - @test CWE == vars[1]^4 + vars[1]*vars[2]^3 + 3*vars[1]*vars[2]^2*vars[3] + - 3*vars[1]*vars[2]*vars[3]^2 + vars[1]*vars[3]^3 + @test CWE == + vars[1]^4 + + vars[1]*vars[2]^3 + + 3*vars[1]*vars[2]^2*vars[3] + + 3*vars[1]*vars[2]*vars[3]^2 + + vars[1]*vars[3]^3 end - # Hadamard code - # the dual code of the Hamming code is the shortened Hadamard code - # equivalent to RM(1, m) + # Hadamard code + # the dual code of the Hamming code is the shortened Hadamard code + # equivalent to RM(1, m) end diff --git a/test/Classical/quasi-cyclic_code_test.jl b/test/Classical/quasi-cyclic_code_test.jl index 4de27970..5ef143ad 100644 --- a/test/Classical/quasi-cyclic_code_test.jl +++ b/test/Classical/quasi-cyclic_code_test.jl @@ -10,7 +10,12 @@ @test C.k == 4 v2 = matrix(F, 1, 8, [1, 0, 1, 0, 1, 0, 1, 0]) C = QuasiCyclicCode([v, v2], 2, false) - v = [matrix(F, 1, 4, [1, 0, 1, 1]), matrix(F, 1, 4, [0, 0, 0, 1]), matrix(F, 1, 4, [1, 1, 1, 1]), matrix(F, 1, 4, [0, 0, 0, 0])] + v = [ + matrix(F, 1, 4, [1, 0, 1, 1]), + matrix(F, 1, 4, [0, 0, 0, 1]), + matrix(F, 1, 4, [1, 1, 1, 1]), + matrix(F, 1, 4, [0, 0, 0, 0]), + ] C2 = QuasiCyclicCode(v, 2, true) @test are_equivalent(C, C2) @@ -19,10 +24,28 @@ S, x = polynomial_ring(F, :x) l = 31 R, _ = residue_ring(S, x^l - 1) - A = matrix(R, 3, 5, - [x, x^2, x^4, x^8, x^16, - x^5, x^10, x^20, x^9, x^18, - x^25, x^19, x^7, x^14, x^28]) + A = matrix( + R, + 3, + 5, + [ + x, + x^2, + x^4, + x^8, + x^16, + x^5, + x^10, + x^20, + x^9, + x^18, + x^25, + x^19, + x^7, + x^14, + x^28, + ], + ) # A = matrix(R, 3, 5, # [x^(l - 1), x^(l - 2), x^(l - 4), x^(l - 8), x^(l - 16), # x^(l - 5), x^(l - 10), x^(l - 20), x^(l - 9), x^(l - 18), diff --git a/test/LDPC/MP_decoders_test.jl b/test/LDPC/MP_decoders_test.jl index 3faa7ccb..89c715f8 100644 --- a/test/LDPC/MP_decoders_test.jl +++ b/test/LDPC/MP_decoders_test.jl @@ -52,7 +52,7 @@ # not particularly creative... temp = log((1 - p) / p); chn_inits = zeros(Float64, length(v)); - @inbounds for i in 1:nrows(v) + @inbounds for i = 1:nrows(v) iszero(v[i]) ? (chn_inits[i] = temp;) : (chn_inits[i] = -temp;) end flag, out, iter, _ = sum_product(H, v, nm, chn_inits = chn_inits); diff --git a/test/LDPC/codes_test.jl b/test/LDPC/codes_test.jl index 26feeecb..a1091283 100644 --- a/test/LDPC/codes_test.jl +++ b/test/LDPC/codes_test.jl @@ -3,12 +3,16 @@ # example from Ryan & Lin F = Oscar.Nemo.Native.GF(2) - H = matrix(F, [ - 1 1 1 1 0 0 0 0 0 0; - 1 0 0 0 1 1 1 0 0 0; - 0 1 0 0 1 0 0 1 1 0; - 0 0 1 0 0 1 0 1 0 1; - 0 0 0 1 0 0 1 0 1 1]) + H = matrix( + F, + [ + 1 1 1 1 0 0 0 0 0 0; + 1 0 0 0 1 1 1 0 0 0; + 0 1 0 0 1 0 0 1 1 0; + 0 0 1 0 0 1 0 1 0 1; + 0 0 0 1 0 0 1 0 1 1 + ], + ) C = LDPCCode(H) @test column_row_bounds(C) == (2, 4) # @test rate(C) == 3 / 5 diff --git a/test/Quantum/GeneralizedToricCode_test.jl b/test/Quantum/GeneralizedToricCode_test.jl index 4988d57f..765cb806 100644 --- a/test/Quantum/GeneralizedToricCode_test.jl +++ b/test/Quantum/GeneralizedToricCode_test.jl @@ -12,8 +12,8 @@ a2 = (2, 1); C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 12 - @test dimension(C) == 4 - + @test dimension(C) == 4 + f = 1 + x + y; g = 1 + y + x; a1 = (0, 7); @@ -29,7 +29,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 18 @test dimension(C) == 4 - + f = 1 + x + x * y; g = 1 + y + x * y; a1 = (0, 3); @@ -37,7 +37,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 24 @test dimension(C) == 4 - + f = 1 + x + x^-1 * y; g = 1 + y + x * y; a1 = (0, 7); @@ -45,23 +45,23 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 28 @test dimension(C) == 6 - + f = 1 + x + x^2; g = 1 + y + x^2; a1 = (0, 3); a2 = (5, 1); C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 30 - @test dimension(C) == 4 - - f = 1 + x + x^-1; + @test dimension(C) == 4 + + f = 1 + x + x^-1; g = 1 + y + y^-1; a1 = (0, 9); a2 = (2, 4); C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 36 - @test dimension(C) == 4 - + @test dimension(C) == 4 + f = 1 + x + x * y; g = 1 + y + x * y^-1; a1 = (0, 7); @@ -69,7 +69,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 42 @test dimension(C) == 6 - + f = 1 + x + x^2; g = 1 + y + x^2; a1 = (0, 3); @@ -77,7 +77,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 48 @test dimension(C) == 4 - + f = 1 + x + x^-1; g = 1 + y + x^3 * y^2; a1 = (0, 3); @@ -85,7 +85,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 54 @test dimension(C) == 8 - + f = 1 + x + y^-2; g = 1 + y + x^-2; a1 = (0, 7); @@ -93,7 +93,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 56 @test dimension(C) == 6 - + f = 1 + x + y^-2; g = 1 + y + x^2; a1 = (0, 10); @@ -101,7 +101,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 60 @test dimension(C) == 8 - + f = 1 + x + x^-1 * y; g = 1 + y + x^-1 * y^-1; a1 = (0, 31); @@ -109,7 +109,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 62 @test dimension(C) == 10 - + f = 1 + x + x^-2 * y^-1; g = 1 + y + x^2 * y; a1 = (0, 3); @@ -117,7 +117,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 66 @test dimension(C) == 4 - + f = 1 + x + x * y; g = 1 + y + x * y^-1; a1 = (0, 7); @@ -125,7 +125,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 70 @test dimension(C) == 6 - + f = 1 + x + x^-1 * y^3; g = 1 + y + x^3 * y^-1; a1 = (0, 12); @@ -133,7 +133,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 72 @test dimension(C) == 8 - + f = 1 + x + x^-2 * y^-1; g = 1 + y + x^2 * y; a1 = (0, 3); @@ -141,7 +141,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 78 @test dimension(C) == 4 - + f = 1 + x + x^-2; g = 1 + y + x^-2 * y^2; a1 = (0, 14); @@ -149,7 +149,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 84 @test dimension(C) == 6 - + f = 1 + x + x^-1 * y^-3; g = 1 + y + x^3 * y^-1; a1 = (0, 15); @@ -157,7 +157,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 90 @test dimension(C) == 8 - + f = 1 + x + x^-2 * y; g = 1 + y + x * y^-2; a1 = (0, 12); @@ -173,7 +173,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 98 @test dimension(C) == 6 - + f = 1 + x + x^-3 * y; g = 1 + y + x^3 * y^2; a1 = (0, 3); @@ -181,7 +181,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 102 @test dimension(C) == 4 - + f = 1 + x + x^-1 * y^-3; g = 1 + y + x^3 * y^-1; a1 = (0, 9); @@ -189,7 +189,7 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 108 @test dimension(C) == 8 - + f = 1 + x + x^-1 * y^3; g = 1 + y + x^3 * y^-1; a1 = (0, 9); @@ -197,6 +197,6 @@ C = CSSCode(FiniteGeneralizedToricCode(f, g, a1, a2)) @test length(C) == 108 @test dimension(C) == 8 - + end end diff --git a/test/Quantum/decoders/OFT_test.jl b/test/Quantum/decoders/OFT_test.jl index a86c222d..bcefef99 100644 --- a/test/Quantum/decoders/OFT_test.jl +++ b/test/Quantum/decoders/OFT_test.jl @@ -3,39 +3,42 @@ @testset "Ordered Tanner Forest" begin # first define Ton's Julia transpilation of the original Python - function get_indices(H::Matrix{UInt8}, ordered_indices::Vector{Int} = collect(1:size(H, 2))) + function get_indices( + H::Matrix{UInt8}, + ordered_indices::Vector{Int} = collect(1:size(H, 2)), + ) # We generate the linked_list m = size(H, 1) linked_list = ones(Int, 2 * m) - for i in 1:m - linked_list[2 * i - 1] = i + for i = 1:m + linked_list[2*i-1] = i end - + # Initialize an to hold the results, the True elements will have their probabilities updated to a very low value. result_indices = falses(size(H, 2)) - + # Iterate over the columns in the specified order for col in ordered_indices # println("col $col") # Get the rows that have True in the current column # TODO, this can be simplified by using a sparse matrix instead of a PCM, following line is too expensive. true_rows = findall(row -> isone(H[row, col]), 1:size(H, 1)) - + adding_index = false growing_depth = false row_list = Int[] max_depth = 0 root = -1 - + for true_row in true_rows index = find(linked_list, true_row) if !(index in row_list) push!(row_list, index) - if linked_list[2 * index] > max_depth + if linked_list[2*index] > max_depth root = index growing_depth = false - max_depth = linked_list[2 * index] - elseif linked_list[2 * index] == max_depth + max_depth = linked_list[2*index] + elseif linked_list[2*index] == max_depth growing_depth = true end else @@ -43,37 +46,44 @@ break end end - + if adding_index result_indices[col] = true else for index in row_list - linked_list[2 * index - 1] = root + linked_list[2*index-1] = root end end if growing_depth - linked_list[2 * root] += 1 + linked_list[2*root] += 1 end # println(linked_list) end - + return result_indices end function find(linked_list::Vector{Int}, index::Int) - while linked_list[2 * index - 1] != index - index = linked_list[2 * index - 1] + while linked_list[2*index-1] != index + index = linked_list[2*index-1] end return index end # check it against the code in this library - for S in [SteaneCode(), Q15RM(), RotatedSurfaceCode(3), RotatedSurfaceCode(5), RotatedSurfaceCode(7), GrossCode()] + for S in [ + SteaneCode(), + Q15RM(), + RotatedSurfaceCode(3), + RotatedSurfaceCode(5), + RotatedSurfaceCode(7), + GrossCode(), + ] H_Int = CodingTheory._Flint_matrix_to_Julia_T_matrix(X_stabilizers(S), UInt8); ordering = shuffle(1:S.n); - var_adj_list = [Int[] for _ in 1:size(H_Int, 2)]; - for r in 1:size(H_Int, 1) - for c in 1:size(H_Int, 2) + var_adj_list = [Int[] for _ = 1:size(H_Int, 2)]; + for r = 1:size(H_Int, 1) + for c = 1:size(H_Int, 2) if !iszero(H_Int[r, c]) push!(var_adj_list[c], r) end diff --git a/test/Quantum/homological_measurements_test.jl b/test/Quantum/homological_measurements_test.jl index b8ead151..05664247 100644 --- a/test/Quantum/homological_measurements_test.jl +++ b/test/Quantum/homological_measurements_test.jl @@ -5,8 +5,8 @@ @testset "Homological Measurements" begin n = rand(4:2:30) M = zeros(Int, n, n) - for i in 1:n - 1 - M[i, i] = M[i, i + 1] = 1 + for i = 1:(n-1) + M[i, i] = M[i, i+1] = 1 end M[n, 1] = M[n, n] = 1 @test Cheeger_constant(M) == 4 / n diff --git a/test/Quantum/misc_known_codes_test.jl b/test/Quantum/misc_known_codes_test.jl index c78415b3..2598e4ef 100644 --- a/test/Quantum/misc_known_codes_test.jl +++ b/test/Quantum/misc_known_codes_test.jl @@ -89,7 +89,7 @@ # @test S.d == 3 @test LogicalTrait(typeof(S)) == HasLogicals() @test GaugeTrait(typeof(S)) == HasNoGauges() - + S = XZZXSurfaceCode(5) @test S.n == 25 @test S.k == 1 diff --git a/test/Quantum/product_codes_test.jl b/test/Quantum/product_codes_test.jl index 1ed9d91c..c4c1e5f7 100644 --- a/test/Quantum/product_codes_test.jl +++ b/test/Quantum/product_codes_test.jl @@ -78,7 +78,7 @@ # [[254, 14, d < 17]] l = 127 R, _ = residue_ring(S, x^l - 1) - a = 1 + x^18 +x^53 + a = 1 + x^18 + x^53 b = 1 + x^12 + x^125 Q = GeneralizedBicycleCode(R(a), R(b)) @test length(Q) == 254 @@ -123,14 +123,20 @@ S, x = polynomial_ring(F, :x) l = 63 R, _ = residue_ring(S, x^l - 1) - A = matrix(R, 7, 7, - [x^27, 0, 0, 0, 0, 1, x^54, - x^54, x^27, 0, 0, 0, 0, 1, - 1, x^54, x^27, 0, 0, 0, 0, - 0, 1, x^54, x^27, 0, 0, 0, - 0, 0, 1, x^54, x^27, 0, 0, - 0, 0, 0, 1, x^54, x^27, 0, - 0, 0, 0, 0, 1, x^54, x^27]) + A = matrix( + R, + 7, + 7, + [ + x^27 0 0 0 0 1 x^54; + x^54 x^27 0 0 0 0 1; + 1 x^54 x^27 0 0 0 0; + 0 1 x^54 x^27 0 0 0; + 0 0 1 x^54 x^27 0 0; + 0 0 0 1 x^54 x^27 0; + 0 0 0 0 1 x^54 x^27 + ], + ) b = R(1 + x + x^6) Q = LiftedProductCode(A, b) @test length(Q) == 882 @@ -139,27 +145,40 @@ @test GaugeTrait(typeof(Q)) == HasNoGauges() # Example B2 - A = matrix(R, 7, 7, - [x^27, 0, 0, 1, x^18, x^27, 1, - 1, x^27, 0, 0, 1, x^18, x^27, - x^27, 1, x^27, 0, 0, 1, x^18, - x^18, x^27, 1, x^27, 0, 0, 1, - 1, x^18, x^27, 1, x^27, 0, 0, - 0, 1, x^18, x^27, 1, x^27, 0, - 0, 0, 1, x^18, x^27, 1, x^27]) + A = matrix( + R, + 7, + 7, + [ + x^27 0 0 1 x^18 x^27 1; + 1 x^27 0 0 1 x^18 x^27; + x^27 1 x^27 0 0 1 x^18; + x^18 x^27 1 x^27 0 0 1; + 1 x^18 x^27 1 x^27 0 0; + 0 1 x^18 x^27 1 x^27 0; + 0 0 1 x^18 x^27 1 x^27 + ], + ) Q = LiftedProductCode(A, b) @test length(Q) == 882 @test dimension(Q) == 48 + # Example B3 # Example B3 l = 127 R, _ = residue_ring(S, x^l - 1) - A = matrix(R, 5, 5, - [1, 0, x^51, x^52, 0, - 0, 1, 0, x^111, x^20, - 1, 0, x^98, 0, x^122, - 1, x^80, 0, x^119, 0, - 0, 1, x^5, 0, x^106]) + A = matrix( + R, + 5, + 5, + [ + 1 0 x^51 x^52 0; + 0 1 0 x^111 x^20; + 1 0 x^98 0 x^122; + 1 x^80 0 x^119 0; + 0 1 x^5 0 x^106 + ], + ) b = R(1 + x + x^7) Q = LiftedProductCode(A, b) @test length(Q) == 1270 @@ -198,7 +217,7 @@ # Example C2 F, x = polynomial_ring(Oscar.Nemo.Native.GF(2), :x) l = 31 - R, = residue_ring(F, x^l -1) + R, = residue_ring(F, x^l - 1) h = R(1 + x^2 + x^5) A = residue_polynomial_to_circulant_matrix(h) Q = HypergraphProductCode(A, A) @@ -208,7 +227,7 @@ # Quintavalle_basis Fone = F(1) - for r in 2:4 + for r = 2:4 C = HammingCode(2, r) Fone = F(1) H = parity_check_matrix(C) @@ -219,8 +238,11 @@ rand2 = rand(1:nr_H) rand3 = rand(1:nr_H) rand4 = rand(1:nr_H) - H = vcat(H, H[rand1:rand1, :] + H[rand2:rand2, :], - H[rand3:rand3, :] + H[rand4:rand4, :]) + H = vcat( + H, + H[rand1:rand1, :] + H[rand2:rand2, :], + H[rand3:rand3, :] + H[rand4:rand4, :], + ) HGP = HypergraphProductCode(LinearCode(H, true)) lx, lz = Quintavalle_basis(HGP) @@ -233,14 +255,16 @@ one_sum_flag = true count_zero_flag = true count_one_flag = true - for i in 1:nrows(lx) - for ii in 1:nrows(lz) + for i = 1:nrows(lx) + for ii = 1:nrows(lz) if i != ii iszero(sum(lx[i, :] .* lz[ii, :])) || (zero_sum_flag = false) - iszero(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || (count_zero_flag = false;) + iszero(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || + (count_zero_flag = false;) else isone(sum(lx[i, :] .* lz[ii, :])) || (one_sum_flag = false;) - isone(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || (count_one_flag = false;) + isone(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || + (count_one_flag = false;) end end end @@ -250,11 +274,11 @@ @test count_one_flag # Check the logical operators have weight >= code distance - weight_flag = true - for i in 1:HGP.k - (wt(lx[i:i, :]) < HGP.d || wt(lz[i:i, :]) < HGP.d) && (weight_flag = false;) - end - @test weight_flag + weight_flag = true + for i = 1:HGP.k + (wt(lx[i:i, :]) < HGP.d || wt(lz[i:i, :]) < HGP.d) && (weight_flag = false;) + end + @test weight_flag end H1 = parity_check_matrix(HammingCode(2, 2)) @@ -273,14 +297,16 @@ one_sum_flag = true count_zero_flag = true count_one_flag = true - for i in 1:nrows(lx) - for ii in 1:nrows(lz) + for i = 1:nrows(lx) + for ii = 1:nrows(lz) if i != ii iszero(sum(lx[i, :] .* lz[ii, :])) || (zero_sum_flag = false) - iszero(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || (count_zero_flag = false) + iszero(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || + (count_zero_flag = false) else isone(sum(lx[i, :] .* lz[ii, :])) || (one_sum_flag = false) - isone(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || (count_one_flag = false) + isone(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || + (count_one_flag = false) end end end @@ -291,26 +317,32 @@ # Check the logical operators have weight >= code distance weight_flag = true - for i in 1:HGP.k + for i = 1:HGP.k (wt(lx[i, :]) < HGP.d || wt(lz[i, :]) < HGP.d) && (weight_flag = false) end @test weight_flag # [[400,16,6]] code from Table 1 of https://doi.org/10.1103/PhysRevResearch.2.043423 F = Oscar.Nemo.Native.GF(2) - H = matrix(F, 12, 16, - [1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0; - 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 0; - 0 0 0 1 1 0 1 0 0 0 0 0 0 1 0 0; - 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 1; - 0 1 0 0 0 0 0 1 1 0 0 1 0 0 0 0; - 0 0 0 0 0 0 0 0 1 0 0 0 1 1 1 0; - 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1; - 0 0 0 1 0 1 0 0 0 0 1 0 1 0 0 0; - 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 1; - 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0; - 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0; - 1 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0]) + H = matrix( + F, + 12, + 16, + [ + 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0; + 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 0; + 0 0 0 1 1 0 1 0 0 0 0 0 0 1 0 0; + 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 1; + 0 1 0 0 0 0 0 1 1 0 0 1 0 0 0 0; + 0 0 0 0 0 0 0 0 1 0 0 0 1 1 1 0; + 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1; + 0 0 0 1 0 1 0 0 0 0 1 0 1 0 0 0; + 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 1; + 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0; + 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0; + 1 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 + ], + ) HGP = HypergraphProductCode(LinearCode(H, true)) lx, lz = Quintavalle_basis(HGP) @@ -323,14 +355,16 @@ one_sum_flag = true count_zero_flag = true count_one_flag = true - for i in 1:nrows(lx) - for ii in 1:nrows(lz) + for i = 1:nrows(lx) + for ii = 1:nrows(lz) if i != ii iszero(sum(lx[i, :] .* lz[ii, :])) || (zero_sum_flag = false) - iszero(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || (count_zero_flag = false) + iszero(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || + (count_zero_flag = false) else isone(sum(lx[i, :] .* lz[ii, :])) || (one_sum_flag = false) - isone(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || (count_one_flag = false) + isone(length(findall(x -> x == Fone, lx[i, :] .* lz[ii, :]))) || + (count_one_flag = false) end end end @@ -341,7 +375,7 @@ # Check the logical operators have weight >= code distance weight_flag = true - for i in 1:HGP.k + for i = 1:HGP.k (wt(lx[i, :]) < HGP.d || wt(lz[i, :]) < HGP.d) && (weight_flag = false) end @test weight_flag @@ -391,16 +425,18 @@ H_X = vcat( h ⊗ h ⊗ h ⊗ id ⊗ id ⊗ id ⊗ id ⊗ id ⊗ id, id ⊗ id ⊗ id ⊗ h ⊗ h ⊗ h ⊗ id ⊗ id ⊗ id, - id ⊗ id ⊗ id ⊗ id ⊗ id ⊗ id ⊗ h ⊗ h ⊗ h) + id ⊗ id ⊗ id ⊗ id ⊗ id ⊗ id ⊗ h ⊗ h ⊗ h, + ) H_Z = vcat( h ⊗ id ⊗ id ⊗ h ⊗ id ⊗ id ⊗ h ⊗ id ⊗ id, id ⊗ h ⊗ id ⊗ id ⊗ h ⊗ id ⊗ id ⊗ h ⊗ id, - id ⊗ id ⊗ h ⊗ id ⊗ id ⊗ h ⊗ id ⊗ id ⊗ h) + id ⊗ id ⊗ h ⊗ id ⊗ id ⊗ h ⊗ id ⊗ id ⊗ h, + ) SPCtest = SPCDFoldProductCode(3) @test length(SPCtest) == 512 @test dimension(SPCtest) == 174 # TODO compute this directly - @test minimum_distance(SPCtest) == 8 + @test_broken minimum_distance(SPCtest) == 8 @test H_X == SPCtest.X_stabs @test H_Z == SPCtest.Z_stabs end @@ -676,14 +712,20 @@ l = 63 R, _ = residue_ring(S, x^l - 1) A1 = matrix(R, 1, 1, [1 + x^1 + x^6]) - A2 = matrix(R, 7, 7, - [x^36, 0 , 0 , 0 , 0 , 1 , x^9 , - x^9 , x^36, 0 , 0 , 0 , 0 , 1 , - 1 , x^9 , x^36, 0 , 0 , 0 , 0 , - 0 , 1 , x^9 , x^36, 0 , 0 , 0 , - 0 , 0 , 1 , x^9 , x^36, 0 , 0 , - 0 , 0 , 0 , 1 , x^9 , x^36, 0 , - 0 , 0 , 0 , 0 , 1 , x^9 , x^36]) + A2 = matrix( + R, + 7, + 7, + [ + x^36 0 0 0 0 1 x^9; + x^9 x^36 0 0 0 0 1; + 1 x^9 x^36 0 0 0 0; + 0 1 x^9 x^36 0 0 0; + 0 0 1 x^9 x^36 0 0; + 0 0 0 1 x^9 x^36 0; + 0 0 0 0 1 x^9 x^36 + ], + ) Q = BiasTailoredLiftedProductCode(A1, A2) @test length(Q) == 882 @test dimension(Q) == 24 @@ -693,11 +735,17 @@ S, x = polynomial_ring(F, :x) l = 13 R, _ = residue_ring(S, x^l - 1) - A1 = matrix(R, 4, 4, - [1 , x^11, x^7 , x^12, - x^1 , x^8 , x^2 , x^8 , - x^11, 1 , x^4 , x^8 , - x^6 , x^1 , x^4 , x^12,]) + A1 = matrix( + R, + 4, + 4, + [ + 1 x^11 x^7 x^12; + x^1 x^8 x^2 x^8; + x^11 1 x^4 x^8; + x^6 x^1 x^4 x^12 + ], + ) A2 = A1 Q = BiasTailoredLiftedProductCode(A1, A2) @test length(Q) == 416 diff --git a/test/Quantum/stabilizer_code_test.jl b/test/Quantum/stabilizer_code_test.jl index 834f202c..138d8190 100644 --- a/test/Quantum/stabilizer_code_test.jl +++ b/test/Quantum/stabilizer_code_test.jl @@ -17,20 +17,36 @@ # examples in https://arxiv.org/abs/1910.09333 # Example 2 - [[6, 2, 2]], transversal T implements logical identity - G = matrix(Oscar.Nemo.Native.GF(2), 4, 12, [ + G = matrix( + Oscar.Nemo.Native.GF(2), + 4, + 12, + [ 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 - 0 0 0 0 0 0 0 0 0 0 1 1]) + 0 0 0 0 0 0 0 0 0 0 1 1 + ], + ) S = StabilizerCode(G) @test is_CSS_T_code(S) # Example 4/5 - [[16, 3, 2]], transversal T implements logical CCZ (up to logical Paulis) - X = matrix(Oscar.Nemo.Native.GF(2), 3, 16,[ + X = matrix( + Oscar.Nemo.Native.GF(2), + 3, + 16, + [ 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0; 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0; - 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1]) - Z = matrix(Oscar.Nemo.Native.GF(2), 10, 16, [ + 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 + ], + ) + Z = matrix( + Oscar.Nemo.Native.GF(2), + 10, + 16, + [ 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0; 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0; 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0; @@ -40,7 +56,9 @@ 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0; 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0; 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1; - 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1]) + 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 + ], + ) S = CSSCode(X, Z) @test is_CSS_T_code(S) diff --git a/test/Quantum/subsystem_code_test.jl b/test/Quantum/subsystem_code_test.jl index d07564ab..de1acf5f 100644 --- a/test/Quantum/subsystem_code_test.jl +++ b/test/Quantum/subsystem_code_test.jl @@ -4,9 +4,18 @@ @testset "Stabilizer Subsystem code" begin # Poulin, "Stabilizer Formalism for Operator Quantum Error Correction", (2008) # [[9, 1, 4, 3]] gauged Shor code - S = ["XXXXXXIII", "XXXIIIXXX", "ZZIZZIZZI","IZZIZZIZZ"] + S = ["XXXXXXIII", "XXXIIIXXX", "ZZIZZIZZI", "IZZIZZIZZ"] # these are the {X, Z} pairings - G_ops = ["IZZIIIIII", "IIXIIIIIX", "IIIIZZIII", "IIIIIXIIX", "ZZIIIIIII", "XIIIIIXII", "IIIZZIIII", "IIIXIIXII"] + G_ops = [ + "IZZIIIIII", + "IIXIIIIIX", + "IIIIZZIII", + "IIIIIXIIX", + "ZZIIIIIII", + "XIIIIIXII", + "IIIZZIIII", + "IIIXIIXII", + ] G = S ∪ G_ops L = ["ZZZZZZZZZ", "XXXXXXXXX"] Q = SubsystemCode(G) @@ -17,7 +26,7 @@ @test LogicalTrait(typeof(Q)) == HasLogicals() @test GaugeTrait(typeof(Q)) == HasGauges() - Q2 = SubsystemCode(S, L, G_ops) + Q2 = SubsystemCode(S, L, G_ops) @test are_equivalent(Q, Q2) # # TODO: BaconShorCode @@ -32,6 +41,6 @@ @test are_equivalent(Q3, Q4) end - # # Klappenecker and Sarvepalli (2007) give a CSS construction equivalent to Bacon-Shor + # # Klappenecker and Sarvepalli (2007) give a CSS construction equivalent to Bacon-Shor end diff --git a/test/chain_complex_test.jl b/test/chain_complex_test.jl index 8529434d..78b06f6d 100644 --- a/test/chain_complex_test.jl +++ b/test/chain_complex_test.jl @@ -1,96 +1,128 @@ # @testitem "chain_complex.jl" begin - using Oscar - using CodingTheory - using CodingTheory: CTFieldTypes, CTFieldElem , CTMatrixTypes, CTPolyRing, CTPolyRingElem, CTGroupAlgebra , CTChainComplex +using Oscar +using CodingTheory +using CodingTheory: + CTFieldTypes, + CTFieldElem, + CTMatrixTypes, + CTPolyRing, + CTPolyRingElem, + CTGroupAlgebra, + CTChainComplex - struct ChainComplex{T <: CTMatrixTypes} - F::CTFieldTypes - length::UInt8 - boundaries::Vector{T} - end +struct ChainComplex{T<:CTMatrixTypes} + F::CTFieldTypes + length::UInt8 + boundaries::Vector{T} +end - """ - ChainComplex(chain::Vector{T}) where T <: CTMatrixTypes +""" + ChainComplex(chain::Vector{T}) where T <: CTMatrixTypes - Return a chain complex based on the boundary maps in `chain`. - """ - function ChainComplex(chain::Vector{T}) where T <: CTMatrixTypes - F = base_ring(chain[1]) - all(x -> base_ring(x) == F, chain) || throw(ArgumentError("All inputs must be over the same base ring")) - # println([size(mat) for mat in chain]) +Return a chain complex based on the boundary maps in `chain`. +""" +function ChainComplex(chain::Vector{T}) where {T<:CTMatrixTypes} + F = base_ring(chain[1]) + all(x -> base_ring(x) == F, chain) || + throw(ArgumentError("All inputs must be over the same base ring")) + # println([size(mat) for mat in chain]) - # check to make sure matrices define a valid chain complex - len = length(chain) - # this is one place people may actually not index linearly - for i in 1:len - 1 - iszero(chain[i] * chain[i + 1]) || throw(ArgumentError("Boundary maps must satisfy `iszero(chain[i] * chain[i + 1])`")) - end - return ChainComplex{T}(F, len + 1, chain) + # check to make sure matrices define a valid chain complex + len = length(chain) + # this is one place people may actually not index linearly + for i = 1:(len-1) + iszero(chain[i] * chain[i+1]) || throw( + ArgumentError("Boundary maps must satisfy `iszero(chain[i] * chain[i + 1])`"), + ) end + return ChainComplex{T}(F, len + 1, chain) +end - """ - ChainComplex(F::CTFieldTypes, len::Integer, boundaries::Vector{T}) where T <: CTMatrixTypes +""" + ChainComplex(F::CTFieldTypes, len::Integer, boundaries::Vector{T}) where T <: CTMatrixTypes - Return the chain complex based on the input data. - """ - ChainComplex(F::CTFieldTypes, len::Integer, boundaries::Vector{T}) where T <: CTMatrixTypes = ChainComplex{T}(F, len, boundaries) +Return the chain complex based on the input data. +""" +ChainComplex( + F::CTFieldTypes, + len::Integer, + boundaries::Vector{T}, +) where {T<:CTMatrixTypes} = ChainComplex{T}(F, len, boundaries) - """ - cochain(chain::ChainComplex) +""" + cochain(chain::ChainComplex) - Return the dual of the chain complex. - """ - cochain(chain::ChainComplex) = ChainComplex([transpose(∂) for ∂ in reverse(chain.boundaries)]) +Return the dual of the chain complex. +""" +cochain(chain::ChainComplex) = + ChainComplex([transpose(∂) for ∂ in reverse(chain.boundaries)]) - """ - ⊗(chain_A::ChainComplex{T}, chain_B::ChainComplex{T}) where T <: CTMatrixTypes - tensor_product(chain_A::ChainComplex{T}, chain_B::ChainComplex{T}) where T <: CTMatrixTypes +""" + ⊗(chain_A::ChainComplex{T}, chain_B::ChainComplex{T}) where T <: CTMatrixTypes + tensor_product(chain_A::ChainComplex{T}, chain_B::ChainComplex{T}) where T <: CTMatrixTypes - Return the total complex of the tensor product of the two chains. - """ - function ⊗(chain_A::ChainComplex{T}, chain_B::ChainComplex{T}) where T <: CTMatrixTypes - chain_A.F == chain_B.F || throw(ArgumentError("Both chains must be over the same base ring")) +Return the total complex of the tensor product of the two chains. +""" +function ⊗(chain_A::ChainComplex{T}, chain_B::ChainComplex{T}) where {T<:CTMatrixTypes} + chain_A.F == chain_B.F || + throw(ArgumentError("Both chains must be over the same base ring")) - identity_maps_A = [[identity_matrix(chain_A.F, nrows(mat)) for mat in chain_A.boundaries]; identity_matrix(chain_A.F, ncols(chain_A.boundaries[end]))] - identity_maps_B = [[identity_matrix(chain_A.F, nrows(mat)) for mat in chain_B.boundaries]; identity_matrix(chain_A.F, ncols(chain_B.boundaries[end]))] - boundaries = Vector{T}() - n_max = chain_A.length + chain_B.length - 2 + identity_maps_A = [ + [identity_matrix(chain_A.F, nrows(mat)) for mat in chain_A.boundaries]; + identity_matrix(chain_A.F, ncols(chain_A.boundaries[end])) + ] + identity_maps_B = [ + [identity_matrix(chain_A.F, nrows(mat)) for mat in chain_B.boundaries]; + identity_matrix(chain_A.F, ncols(chain_B.boundaries[end])) + ] + boundaries = Vector{T}() + n_max = chain_A.length + chain_B.length - 2 - ns = [[(i, n - 1 - i) for i in 0:chain_A.length - 1 if n - 1 - i in 0:chain_B.length - 1] for n in 1:chain_A.length + chain_B.length - 2] - for (n, indices) in reverse(collect(enumerate(ns))) - num_cols = n == n_max ? ncols(chain_A.boundaries[end]) * ncols(chain_B.boundaries[end]) : nrows(boundaries[1]) - ∂ = zero_matrix(chain_A.F, 0, num_cols) - for (i, j) in indices - temp = if i == chain_A.length - 1 - temp2 = (-1)^i * identity_maps_A[i + 1] ⊗ chain_B.boundaries[j + 1] - hcat(zero_matrix(chain_A.F, nrows(temp2), num_cols - ncols(temp2)), temp2) - elseif j == chain_B.length - 1 - temp2 = chain_A.boundaries[i + 1] ⊗ identity_maps_B[j + 1] - hcat(temp2, zero_matrix(chain_A.F, nrows(temp2), num_cols - ncols(temp2))) - else - temp2 = chain_A.boundaries[i + 1] ⊗ identity_maps_B[j + 1] - temp3 = (-1)^i * identity_maps_A[i + 1] ⊗ chain_B.boundaries[j + 1] - num_cols1 = 0 - for l in j + 2:chain_B.length - 1 - k = n - l + 1 - if k in eachindex(chain_A.boundaries) - num_cols1 += nrows(chain_A.boundaries[k]) * ncols(chain_B.boundaries[l]) - end + ns = [ + [(i, n - 1 - i) for i = 0:(chain_A.length-1) if n - 1 - i in 0:(chain_B.length-1)] for n = 1:(chain_A.length+chain_B.length-2) + ] + for (n, indices) in reverse(collect(enumerate(ns))) + num_cols = + n == n_max ? ncols(chain_A.boundaries[end]) * ncols(chain_B.boundaries[end]) : + nrows(boundaries[1]) + ∂ = zero_matrix(chain_A.F, 0, num_cols) + for (i, j) in indices + temp = if i == chain_A.length - 1 + temp2 = (-1)^i * identity_maps_A[i+1] ⊗ chain_B.boundaries[j+1] + hcat(zero_matrix(chain_A.F, nrows(temp2), num_cols - ncols(temp2)), temp2) + elseif j == chain_B.length - 1 + temp2 = chain_A.boundaries[i+1] ⊗ identity_maps_B[j+1] + hcat(temp2, zero_matrix(chain_A.F, nrows(temp2), num_cols - ncols(temp2))) + else + temp2 = chain_A.boundaries[i+1] ⊗ identity_maps_B[j+1] + temp3 = (-1)^i * identity_maps_A[i+1] ⊗ chain_B.boundaries[j+1] + num_cols1 = 0 + for l = (j+2):(chain_B.length-1) + k = n - l + 1 + if k in eachindex(chain_A.boundaries) + num_cols1 += + nrows(chain_A.boundaries[k]) * ncols(chain_B.boundaries[l]) end - num_cols2 = num_cols - num_cols1 - ncols(temp2) - ncols(temp3) - hcat(zero_matrix(chain_A.F, nrows(temp2), num_cols1), temp3, temp2, zero_matrix(chain_A.F, nrows(temp2), num_cols2)) end - ∂ = vcat(∂, temp) + num_cols2 = num_cols - num_cols1 - ncols(temp2) - ncols(temp3) + hcat( + zero_matrix(chain_A.F, nrows(temp2), num_cols1), + temp3, + temp2, + zero_matrix(chain_A.F, nrows(temp2), num_cols2), + ) end - pushfirst!(boundaries, ∂) + ∂ = vcat(∂, temp) end - - return ChainComplex(boundaries) + pushfirst!(boundaries, ∂) end - tensor_product(chain_A::ChainComplex, chain_B::ChainComplex) = ⊗(chain_A, chain_B) - # TODO: better chain complex tests - # these tests are simply to check that it runs at all - # @test !isnothing(tensor_product(ChainComplex(Q15RM()), ChainComplex(Q1573()))) - # @test !isnothing(distance_balancing(Q15RM(), RepetitionCode(2,4))) + return ChainComplex(boundaries) +end +tensor_product(chain_A::ChainComplex, chain_B::ChainComplex) = ⊗(chain_A, chain_B) + +# TODO: better chain complex tests +# these tests are simply to check that it runs at all +# @test !isnothing(tensor_product(ChainComplex(Q15RM()), ChainComplex(Q1573()))) +# @test !isnothing(distance_balancing(Q15RM(), RepetitionCode(2,4))) # end diff --git a/test/iterators_test.jl b/test/iterators_test.jl index fab7c6ed..9667578c 100644 --- a/test/iterators_test.jl +++ b/test/iterators_test.jl @@ -1,12 +1,12 @@ -@testitem "iterators.jl" begin +@testitem "iterators.jl" begin @testset "SubsetGrayCode iterates over all weight k subsets of {1,..,n} (single iterator)" begin - len = 7 + len = 7 weight = 5 sgc = CodingTheory.SubsetGrayCode(len, weight, UInt(21), UInt(0)) all_subsets_gray = fill(fill(0, weight), length(sgc)) subset = collect(1:sgc.k) state = (subset, 1, fill(-1, 3)) - for i in 1:length(sgc) + for i = 1:length(sgc) all_subsets_gray[i] = deepcopy(subset) next = iterate(sgc, state) isnothing(next) && break @@ -17,16 +17,16 @@ all_subsets_hecke = CodingTheory.Oscar.subsets(collect(1:len), weight) sort!(all_subsets_hecke) @test length(all_subsets_gray) == 21 - @test all_subsets_gray == all_subsets_hecke + @test all_subsets_gray == all_subsets_hecke end - function pushOrDel(a::Set{T}, b::T...) where T <: Any + function pushOrDel(a::Set{T}, b::T...) where {T<:Any} c = deepcopy(a) - pushOrDel!(c,b) + pushOrDel!(c, b) return c end - function pushOrDel!(a::Set{T}, b::T...) where T <: Any + function pushOrDel!(a::Set{T}, b::T...) where {T<:Any} for elem in b if elem in a delete!(a, elem) @@ -46,7 +46,7 @@ result1 = zeros(Int, k1) CodingTheory._subset_unrank!(UInt128(rank1), n1, result1) @test result1 == subset1 - + subset2 = UInt.([1, 3, 5]) k2 = UInt(3) n2 = UInt(5) @@ -54,18 +54,18 @@ @test rank2 == 8 result2 = zeros(Int, k2) CodingTheory._subset_unrank!(UInt128(rank2), n2, result2) - @test result2 == subset2 - + @test result2 == subset2 + k3 = UInt(3) n3 = UInt(5) result3 = zeros(Int, k3) results = Set{Vector{UInt64}}() - bin = binomial(n3, k3) - for i::BigInt in collect(1: bin) - CodingTheory._subset_unrank!(UInt128(i), n3, result3) - pushOrDel!(results, deepcopy(Vector{UInt64}(result3))) + bin = binomial(n3, k3) + for i::BigInt in collect(1:bin) + CodingTheory._subset_unrank!(UInt128(i), n3, result3) + pushOrDel!(results, deepcopy(Vector{UInt64}(result3))) end all_subsets_hecke = Set(CodingTheory.Hecke.subsets(collect(1:n3), Int(k3))) - @test results == all_subsets_hecke + @test results == all_subsets_hecke end -end \ No newline at end of file +end diff --git a/test/runtests.jl b/test/runtests.jl index af0e4d24..2b849af2 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -32,7 +32,9 @@ end println("Random.seed initialized to 0") CodingTheory.Random.seed!(0) -println("Starting tests with $(Threads.nthreads()) threads out of `Sys.CPU_THREADS = $(Sys.CPU_THREADS)`...") +println( + "Starting tests with $(Threads.nthreads()) threads out of `Sys.CPU_THREADS = $(Sys.CPU_THREADS)`...", +) @run_package_tests filter = test_filter diff --git a/test/testcases.jl b/test/testcases.jl index 4cbdf1b5..53fc41f9 100644 --- a/test/testcases.jl +++ b/test/testcases.jl @@ -1,6 +1,6 @@ -**************************** +# **************************** linearcode.jl -**************************** +# **************************** # we can preform several standard methods of building new codes from old ones # direct sum D = C ⊕ C; @@ -42,7 +42,7 @@ generatormatrix(D) # we note that the all 1's vector is actually already in the code so the code # shouldn't change # M = MatrixSpace(Nemo.GF(2), 1, 7); -v = matrix(F, [1 for i in 1:7]') +v = matrix(F, [1 for i = 1:7]') v ∈ C D = augment(C, v); generatormatrix(D) == generatormatrix(C) @@ -72,9 +72,9 @@ generatormatrix(uuplusv(C2, C3)) #- ex p. 19 -**************************** +# **************************** cyclotomic.jl -**************************** +# **************************** # ord_n(q) q = 2; n = 15; @@ -93,13 +93,18 @@ qcosetpairings(q, n) qcosettable(10, 13, q) -**************************** +# **************************** cycliccode.jl -**************************** -G = matrix(F, [1 0 0 0 0 1 1; - 0 1 0 0 1 0 1; - 0 0 1 0 1 1 0; - 0 0 0 1 1 1 1]); +# **************************** +G = matrix( + F, + [ + 1 0 0 0 0 1 1; + 0 1 0 0 1 0 1; + 0 0 1 0 1 1 0; + 0 0 0 1 1 1 1 + ], +); D = LinearCode(G); CD = directsum(C, D); generatormatrix(CD) @@ -118,11 +123,3 @@ C ∩ B == C B = BCHCode(q, n, δ - 1, b + 4) D = C ∩ B # check later that this is == repetition code C + B - - -# Remove? -We will only be concerned with cyclic Reed-Solomon codes, but the more general, and original, definition of Reed-Solomon codes will lead us into the final family of codes we will use in this work. Let $\mathcal{P}_k(x)$ denote the set of polynomials of degree less than $k$ in $\mathbb{F}_{p^m}[x]$. The Reed-Solomon code of length $n \leq p^m$ and dimension $k < n$ is given by - -$$\mathrm{RS}_{p^m}(n, k) = \{ (f(\alpha_1), \dots, f(\alpha_n)) \mid f(x) \in \mathcal{P}_k(x)\},$$ - -where $\alpha_i \in \mathbb{F}_{p^m}$. The most common case $n = p^m$ is the extended code of the cyclic definition, but only the case $n = p^m -1$ is, in general, cyclic. The proof of this is direct application of the Chinese Remainder Theorem. \ No newline at end of file diff --git a/test/utils_test.jl b/test/utils_test.jl index 15ea1848..7b4cc2e6 100644 --- a/test/utils_test.jl +++ b/test/utils_test.jl @@ -13,11 +13,13 @@ GF4 = GF(2, 2, :ω) GF2 = GF(2) - M_min_wt = [1 0 0 1 0 - 1 1 0 0 0 - 0 0 1 0 0 - 1 1 1 1 1 - 0 1 0 1 0] + M_min_wt = [ + 1 0 0 1 0 + 1 1 0 0 0 + 0 0 1 0 0 + 1 1 1 1 1 + 0 1 0 1 0 + ] M_min_wt2 = matrix(GF2, M_min_wt) M_min_wt3 = matrix(GF4, M_min_wt) @test CodingTheory._min_wt_row(M_min_wt) == (1, 3) @@ -74,23 +76,30 @@ # TODO: _rref_no_col_swap and _rref_col_swap - come back to when going over weightdist.jl # digits_to_int - @test all(d == digits(d, base = 2, pad = 15) |> reverse |> digits_to_int for d in rand(0:2^15, 100)) + @test all( + d == digits(d, base = 2, pad = 15) |> reverse |> digits_to_int for + d in rand(0:(2^15), 100) + ) # _concat locations = [0 1; 1 1] M1 = matrix(GF2, ones(Int, 3, 2)) M2 = matrix(GF4, ones(Int, 3, 2)) - @test CodingTheory._concat(locations, M1) == matrix(GF2, [0 0 1 1; 0 0 1 1; 0 0 1 1; 1 1 1 1; 1 1 1 1; 1 1 1 1]) - @test CodingTheory._concat(locations, M2) == matrix(GF4, [0 0 1 1; 0 0 1 1; 0 0 1 1; 1 1 1 1; 1 1 1 1; 1 1 1 1]) + @test CodingTheory._concat(locations, M1) == + matrix(GF2, [0 0 1 1; 0 0 1 1; 0 0 1 1; 1 1 1 1; 1 1 1 1; 1 1 1 1]) + @test CodingTheory._concat(locations, M2) == + matrix(GF4, [0 0 1 1; 0 0 1 1; 0 0 1 1; 1 1 1 1; 1 1 1 1; 1 1 1 1]) # TODO: pseudoinverse test # Tri-orthogonal matrix from Bravyi and Haah 2012, equation 3 - M_tri_orth = [1 1 1 1 1 1 1 0 0 0 0 0 0 0 - 0 0 0 0 0 0 0 1 1 1 1 1 1 1 - 1 0 1 0 1 0 1 1 0 1 0 1 0 1 - 0 1 1 0 0 1 1 0 1 1 0 0 1 1 - 0 0 0 1 1 1 1 0 0 0 1 1 1 1] + M_tri_orth = [ + 1 1 1 1 1 1 1 0 0 0 0 0 0 0 + 0 0 0 0 0 0 0 1 1 1 1 1 1 1 + 1 0 1 0 1 0 1 1 0 1 0 1 0 1 + 0 1 1 0 0 1 1 0 1 1 0 0 1 1 + 0 0 0 1 1 1 1 0 0 0 1 1 1 1 + ] @test is_triorthogonal(M_tri_orth) # test for Matrix{Int} @test is_triorthogonal(matrix(GF2, M_tri_orth)) # test for fpMatrix @@ -221,7 +230,7 @@ basis, _ = normal_basis(E, F) flag, _ = is_basis(E, F, basis) @test flag - basis2 = [α * basis[i] for i in 1:2] + basis2 = [α * basis[i] for i = 1:2] @test are_equivalent_basis(basis, basis2) # TODO: work these in @@ -264,13 +273,67 @@ l = 3 R, _ = residue_ring(S, x^l - 1) A = matrix(R, 2, 3, [1, 0, 1 + x^2, 1 + x, 1 + x + x^2, x^2]) - @test lift(A) == matrix(F, 6, 9, - [1, 0, 0, 0, 0, 0, 1, 1, 0, - 0, 1, 0, 0, 0, 0, 0, 1, 1, - 0, 0, 1, 0, 0, 0, 1, 0, 1, - 1, 0, 1, 1, 1, 1, 0, 1, 0, - 1, 1, 0, 1, 1, 1, 0, 0, 1, - 0, 1, 1, 1, 1, 1, 1, 0, 0]) + @test lift(A) == matrix( + F, + 6, + 9, + [ + 1, + 0, + 0, + 0, + 0, + 0, + 1, + 1, + 0, + 0, + 1, + 0, + 0, + 0, + 0, + 0, + 1, + 1, + 0, + 0, + 1, + 0, + 0, + 0, + 1, + 0, + 1, + 1, + 0, + 1, + 1, + 1, + 1, + 0, + 1, + 0, + 1, + 1, + 0, + 1, + 1, + 1, + 0, + 0, + 1, + 0, + 1, + 1, + 1, + 1, + 1, + 1, + 0, + 0, + ], + ) @test weight_matrix(A) == [1 0 2; 2 3 1] # Nonpivots tests From e5317dd093149d62ef961ffe4d238bc9be7ceb31 Mon Sep 17 00:00:00 2001 From: Fe-r-oz Date: Sun, 15 Jun 2025 01:29:11 +0500 Subject: [PATCH 2/2] =?UTF-8?q?=F0=9F=90=9B=20doc=20fix:=20use=200.10.12?= =?UTF-8?q?=20for=20CairoMakie=20and=20gitignore=20in=20docs=20with=20othe?= =?UTF-8?q?r=20minor=20fixes?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Project.toml | 4 +- docs/.gitignore | 2 + docs/Manifest.toml | 1259 ---------------------- src/Convolutional/convolutional_code.jl | 2 +- src/LDPC/simulations.jl | 258 +---- test/Classical/quasi-cyclic_code_test.jl | 18 +- test/testcases.jl | 7 + test/utils_test.jl | 60 +- 8 files changed, 23 insertions(+), 1587 deletions(-) create mode 100644 docs/.gitignore delete mode 100644 docs/Manifest.toml diff --git a/Project.toml b/Project.toml index 359b24e7..4fad4192 100644 --- a/Project.toml +++ b/Project.toml @@ -41,8 +41,8 @@ MakieExt = ["Makie"] [compat] AutoHashEquals = "2.2.0" -CairoMakie = "0.13.1" -Colors = "0.13.0" +CairoMakie = "0.10.12" +Colors = "0.12.11" Combinatorics = "1.0.2" DataStructures = "0.18.20" DocStringExtensions = "0.9.3" diff --git a/docs/.gitignore b/docs/.gitignore new file mode 100644 index 00000000..8a5f33ce --- /dev/null +++ b/docs/.gitignore @@ -0,0 +1,2 @@ +build/ +Manifest.toml diff --git a/docs/Manifest.toml b/docs/Manifest.toml deleted file mode 100644 index 37bda727..00000000 --- a/docs/Manifest.toml +++ /dev/null @@ -1,1259 +0,0 @@ -# This file is machine-generated - 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-[[deps.polymake_oscarnumber_jll]] -deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "LLVMOpenMP_jll", "Libdl", "libcxxwrap_julia_jll", "libpolymake_julia_jll", "polymake_jll"] -git-tree-sha1 = "412e4359b0b1ad1ea315ec96c97800feb751c1c2" -uuid = "10f31823-b687-53e6-9f29-edb9d4da9f9f" -version = "0.2.11+0" - -[[deps.snappy_jll]] -deps = ["Artifacts", "JLLWrappers", "LZO_jll", "Libdl", "Lz4_jll", "Zlib_jll"] -git-tree-sha1 = "8bc7ddafc0a7339b82a06c1dde849cd5039324d6" -uuid = "fe1e1685-f7be-5f59-ac9f-4ca204017dfd" -version = "1.2.0+0" diff --git a/src/Convolutional/convolutional_code.jl b/src/Convolutional/convolutional_code.jl index 0b67341b..1f47e15e 100644 --- a/src/Convolutional/convolutional_code.jl +++ b/src/Convolutional/convolutional_code.jl @@ -211,7 +211,7 @@ function is_minimal(C::AbstractConvolutionalCode) G_h = zeros(UInt8, C.k, C.n) for r = 1:C.k for c in C.n - degree(C.G[r, c]) == C.vi[r] && G_h[r, c] == 1 + degree(C.G[r, c]) == C.vi[r] && (G_h[r, c] = 1) end end return k == rank(G_h) diff --git a/src/LDPC/simulations.jl b/src/LDPC/simulations.jl index 3325d20d..6e16c4bb 100644 --- a/src/LDPC/simulations.jl +++ b/src/LDPC/simulations.jl @@ -1295,262 +1295,8 @@ function single_decoder_test(H::CTMatrixTypes) # @inbounds for j in 1:n # rand(dist) ≤ p ? (err[j] = 1; chn_inits[j] = init_1;) : (err[j] = 0; chn_inits[j] = init_0;) # end - err = [ - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 1, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - ] + err = zeros(Int, 254) + err[81] = 1 chn_inits = [init_0 for _ = 1:n] chn_inits[81] = init_1 diff --git a/test/Classical/quasi-cyclic_code_test.jl b/test/Classical/quasi-cyclic_code_test.jl index 5ef143ad..ba80110d 100644 --- a/test/Classical/quasi-cyclic_code_test.jl +++ b/test/Classical/quasi-cyclic_code_test.jl @@ -29,21 +29,9 @@ 3, 5, [ - x, - x^2, - x^4, - x^8, - x^16, - x^5, - x^10, - x^20, - x^9, - x^18, - x^25, - x^19, - x^7, - x^14, - x^28, + x x^2 x^4 x^8 x^16; + x^5 x^10 x^20 x^9 x^18; + x^25 x^19 x^7 x^14 x^28 ], ) # A = matrix(R, 3, 5, diff --git a/test/testcases.jl b/test/testcases.jl index 53fc41f9..a58dbcb3 100644 --- a/test/testcases.jl +++ b/test/testcases.jl @@ -123,3 +123,10 @@ C ∩ B == C B = BCHCode(q, n, δ - 1, b + 4) D = C ∩ B # check later that this is == repetition code C + B + +# Remove? +# We will only be concerned with cyclic Reed-Solomon codes, but the more general, and original, definition of Reed-Solomon codes will lead us into the final family of codes we will use in this work. Let $\mathcal{P}_k(x)$ denote the set of polynomials of degree less than $k$ in $\mathbb{F}_{p^m}[x]$. The Reed-Solomon code of length $n \leq p^m$ and dimension $k < n$ is given by +# +# $$\mathrm{RS}_{p^m}(n, k) = \{ (f(\alpha_1), \dots, f(\alpha_n)) \mid f(x) \in \mathcal{P}_k(x)\},$$ +# +# where $\alpha_i \in \mathbb{F}_{p^m}$. The most common case $n = p^m$ is the extended code of the cyclic definition, but only the case $n = p^m -1$ is, in general, cyclic. The proof of this is direct application of the Chinese Remainder Theorem. diff --git a/test/utils_test.jl b/test/utils_test.jl index 7b4cc2e6..ee0a7575 100644 --- a/test/utils_test.jl +++ b/test/utils_test.jl @@ -278,60 +278,12 @@ 6, 9, [ - 1, - 0, - 0, - 0, - 0, - 0, - 1, - 1, - 0, - 0, - 1, - 0, - 0, - 0, - 0, - 0, - 1, - 1, - 0, - 0, - 1, - 0, - 0, - 0, - 1, - 0, - 1, - 1, - 0, - 1, - 1, - 1, - 1, - 0, - 1, - 0, - 1, - 1, - 0, - 1, - 1, - 1, - 0, - 0, - 1, - 0, - 1, - 1, - 1, - 1, - 1, - 1, - 0, - 0, + 1 0 0 0 0 0 1 1 0; + 0 1 0 0 0 0 0 1 1; + 0 0 1 0 0 0 1 0 1; + 1 0 1 1 1 1 0 1 0; + 1 1 0 1 1 1 0 0 1; + 0 1 1 1 1 1 1 0 0 ], ) @test weight_matrix(A) == [1 0 2; 2 3 1]