finished readme except for more simulation details

amicciche · amicciche · commit 9270443d149a · 2025-08-22T16:32:04.000-04:00
diff --git a/README.md b/README.md
@@ -235,7 +235,50 @@ julia> CircuitCompilation2xn.calculate_shifts(shor_new_circuit)
  [sXCZ(6,18), sXCZ(7,19), sXCZ(3,15), sXCZ(5,17)]
 ```
 ## Nice to have functions for quick data collection
+If one is only interested in obtaining the number of shuttling operations required for different levels of compilation (and doesn't need the compiled circuit) for a given syndrome circuit, a function is provided for this for bot Shor and naive syndrome extraction. The last two numbers are related to the minimum number of shuttles, if allowing blank qubits in the array.  This number wasn't optimized, and is computed by just counting the number of gaps in the chains. Refer to the paper for more information on this. 
+
+Shor syndrome circuit:
+```
+julia> cat, scirc, _ = QuantumClifford.ECC.shor_syndrome_circuit(code);
+julia> code = Steane7();
+julia> cat, scirc, _ = QuantumClifford.ECC.shor_syndrome_circuit(code);
+julia> CircuitCompilation2xn.shorNumbers(scirc)
+Uncompiled: 14
+Gate Shuffled: 14
+Ancil Heuristic: 7
+SSSC: 6
+Or could do in 6 shifts, using  at most 2 blank qubits.
+6-element Vector{Any}:
+ 14
+ 14
+  7
+  6
+  6
+  2
+```
+
+Naive circuit: 
+```
+julia> code = Steane7();
+julia> scirc, _ = QuantumClifford.ECC.naive_syndrome_circuit(code);
+julia> num_qubits = code_n(code)+code_s(code)
+13
+julia> CircuitCompilation2xn.comp_numbers(scirc, num_qubits)
+4-element Vector{Any}:
+ 24
+ 11
+  9
+  7
+```
+24 is the uncompiled number of shuttles, 11 is gate shuffled, 9 is ancillary reindexing, and 7 is ancillary + data reindexing.
 
 ## How to do simulations with this software
+`src/plotting_CC2xn.jl` contains some lines at the bottom that can be commented or uncommented to generate various plots that appear in the paper. For example
+```
+f_Steane = my_plot_both_synd(Steane7(), TableDecoder(Steane7()))
+f_t3 = plot_for_paper_figure(Toric(3, 3), PyMatchingDecoder(Toric(3, 3)), name="Toric 3x3")
+```
+`f_Steane` will be the plot containing the 4 different physical vs logical error plots from the paper's appendix, `f_t3` generates a single plot. 
+More details coming soon...
 ## Further information
-README under construction....
+Please contact Anthony Micciche (email listed in the paper) if you have any issues running this software.
diff --git a/src/CircuitCompilation2xn.jl b/src/CircuitCompilation2xn.jl
@@ -711,7 +711,7 @@ function shorNumbers(circuit)
     println("Ancil Heuristic: ", shifts[3])
     println("SSSC: ", shifts[4])
 
-    println("Or could do in ",chain_info[1], " shifts, using  ", chain_info[2], " blank qubits.")
+    println("Or could do in ",chain_info[1], " shifts, using  at most ", chain_info[2], " blank qubits.")
     push!(shifts, chain_info[1]); push!(shifts, chain_info[2])
     return shifts
 end
diff --git a/src/plotting_CC2xn.jl b/src/plotting_CC2xn.jl
@@ -23,9 +23,9 @@ function my_plot_both_synd(code::AbstractECC, decoder::AbstractSyndromeDecoder,
     #p_wait = 1-exp(-14.5/m/28_000) # improvement in time to shuttle
     #p_shift = p_shift/m #improvement in shuttling fidelity
 
-    #gate_noise = 0
+    # gate_noise = 0
     # p_wait = 0
-    #p_shift = 0
+    # p_shift = 0
     error_rates = exp10.(range(-4,-0.5,length=30))
 
     f = Figure(size=(1400, 1400),px_per_unit = 5.0)
@@ -51,15 +51,15 @@ function my_plot_both_synd(code::AbstractECC, decoder::AbstractSyndromeDecoder,
     z_error_MB_CB = [post_ec_error_rates_MB_CB[i][2] for i in eachindex(post_ec_error_rates_MB_CB)]
 
     # Gate shuffled circuit 
-    gate_shuffle_circ = CircuitCompilation2xn.gate_Shuffle!(scirc)
+    gate_shuffled_circ = CircuitCompilation2xn.gate_shuffle_circ(scirc)
 
     # Gate shuffle - no gate noise
-    post_ec_error_rates_MS_CA = [evaluate_code_decoder_naive_syndrome(checks, decoder, ecirc, gate_shuffle_circ, p, p_shift*p*m, p_wait*p*m, gate_noise*p*m, nsamples=nsamples) for p in error_rates]
+    post_ec_error_rates_MS_CA = [evaluate_code_decoder_naive_syndrome(checks, decoder, ecirc, gate_shuffled_circ, p, p_shift*p*m, p_wait*p*m, gate_noise*p*m, nsamples=nsamples) for p in error_rates]
     x_error_MS_CA = [post_ec_error_rates_MS_CA[i][1] for i in eachindex(post_ec_error_rates_MS_CA)]
     z_error_MS_CA = [post_ec_error_rates_MS_CA[i][2] for i in eachindex(post_ec_error_rates_MS_CA)]
 
     # Gate shuffle- gate noise== init noise
-    post_ec_error_rates_MS_CB = [evaluate_code_decoder_naive_syndrome(checks, decoder, ecirc, gate_shuffle_circ, p, p_shift, p_wait, gate_noise, nsamples=nsamples) for p in error_rates]
+    post_ec_error_rates_MS_CB = [evaluate_code_decoder_naive_syndrome(checks, decoder, ecirc, gate_shuffled_circ, p, p_shift, p_wait, gate_noise, nsamples=nsamples) for p in error_rates]
     x_error_MS_CB = [post_ec_error_rates_MS_CB[i][1] for i in eachindex(post_ec_error_rates_MS_CB)]
     z_error_MS_CB = [post_ec_error_rates_MS_CB[i][2] for i in eachindex(post_ec_error_rates_MS_CB)]
 
@@ -147,15 +147,15 @@ function my_plot_both_synd(code::AbstractECC, decoder::AbstractSyndromeDecoder,
     z_error_MB_CB_shor = [post_ec_error_rates_MB_CB_shor[i][2] for i in eachindex(post_ec_error_rates_MB_CB_shor)]
 
     # Gate shuffled circuit 
-    gate_shuffle_circ = CircuitCompilation2xn.gate_Shuffle!(scirc)
+    gate_shuffled_circ = CircuitCompilation2xn.gate_shuffle_circ(scirc)
 
     # Gate shuffle - no gate noise
-    post_ec_error_rates_MS_CA_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, gate_shuffle_circ, p, p_shift*p*m, p_wait*p*m, gate_noise*p*m,  nsamples=nsamples) for p in error_rates]
+    post_ec_error_rates_MS_CA_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, gate_shuffled_circ, p, p_shift*p*m, p_wait*p*m, gate_noise*p*m,  nsamples=nsamples) for p in error_rates]
     x_error_MS_CA_shor = [post_ec_error_rates_MS_CA_shor[i][1] for i in eachindex(post_ec_error_rates_MS_CA_shor)]
     z_error_MS_CA_shor = [post_ec_error_rates_MS_CA_shor[i][2] for i in eachindex(post_ec_error_rates_MS_CA_shor)]
 
     # Gate shuffle- gate noise== init noise
-    post_ec_error_rates_MS_CB_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, gate_shuffle_circ, p, p_shift, p_wait, gate_noise, nsamples=nsamples) for p in error_rates]
+    post_ec_error_rates_MS_CB_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, gate_shuffled_circ, p, p_shift, p_wait, gate_noise, nsamples=nsamples) for p in error_rates]
     x_error_MS_CB_shor = [post_ec_error_rates_MS_CB_shor[i][1] for i in eachindex(post_ec_error_rates_MS_CB_shor)]
     z_error_MS_CB_shor = [post_ec_error_rates_MS_CB_shor[i][2] for i in eachindex(post_ec_error_rates_MS_CB_shor)]
 
@@ -279,158 +279,6 @@ function my_plot_both_synd(code::AbstractECC, decoder::AbstractSyndromeDecoder,
     return f 
 end
 
-######## Legacy code for plotting the LDPC codes given to me
-function LDPC_plot(code::AbstractECC, decoder::AbstractSyndromeDecoder, p_shift=0.0001, p_wait=1-exp(-14.5/28_000); name=string(typeof(code)))
-    title = name*" Code - Naive Syndrome Circuit"
-    checks = parity_checks(code)
-    scirc, _ = naive_syndrome_circuit(checks)
-
-    #ecirc = naive_encoding_circuit(code)
-    ecirc = nothing
-
-    nsamples = 10
-    gate_fidelity = 0.9995
-    m = 10 # improvment factor
-    gate_noise = 1- gate_fidelity
-
-    error_rates = exp10.(range(-4,-0.5,length=30))
-
-    # All to all connectivty - no gate noise 
-    post_ec_error_rates_MA_CA = [evaluate_code_decoder_naive_syndrome(checks, decoder, ecirc, scirc, p, 0, 0, gate_noise*p*m, nsamples=nsamples) for p in error_rates]
-    x_error_MA_CA = [post_ec_error_rates_MA_CA[i][1] for i in eachindex(post_ec_error_rates_MA_CA)]
-    z_error_MA_CA = [post_ec_error_rates_MA_CA[i][2] for i in eachindex(post_ec_error_rates_MA_CA)]
-
-    # All to all connectivty - gate noise == init noise 
-    post_ec_error_rates_MA_CB= [evaluate_code_decoder_naive_syndrome(checks, decoder, ecirc, scirc, p, 0, 0, gate_noise, nsamples=nsamples) for p in error_rates]
-    x_error_MA_CB = [post_ec_error_rates_MA_CB[i][1] for i in eachindex(post_ec_error_rates_MA_CB)]
-    z_error_MA_CB = [post_ec_error_rates_MA_CB[i][2] for i in eachindex(post_ec_error_rates_MA_CB)]
-
-    # Circuit compilation
-    new_circuit, order = CircuitCompilation2xn.ancil_reindex_pipeline(scirc)
-
-    # Circuit comp - no gate noise
-    post_ec_error_rates_MC_CA = [evaluate_code_decoder_naive_syndrome(checks, decoder, ecirc, new_circuit, p, p_shift*p*m, p_wait*p*m, gate_noise*p*m, nsamples=nsamples) for p in error_rates]
-    x_error_MC_CA = [post_ec_error_rates_MC_CA[i][1] for i in eachindex(post_ec_error_rates_MC_CA)]
-    z_error_MC_CA = [post_ec_error_rates_MC_CA[i][2] for i in eachindex(post_ec_error_rates_MC_CA)]
-
-    # Circuit Comp gate noise == init noise
-    post_ec_error_rates_MC_CB = [evaluate_code_decoder_naive_syndrome(checks, decoder, ecirc, new_circuit, p, p_shift, p_wait, gate_noise, nsamples=nsamples) for p in error_rates]
-    x_error_MC_CB = [post_ec_error_rates_MC_CB[i][1] for i in eachindex(post_ec_error_rates_MC_CB)]
-    z_error_MC_CB = [post_ec_error_rates_MC_CB[i][2] for i in eachindex(post_ec_error_rates_MC_CB)]
-
-    f = Figure(size=(1500, 1500))
-    # X plot
-    f_x =  f[1,1]
-    ax = f[1,1] = Axis(f_x, xlabel="p_mem = physical qubit error rate after encoding",ylabel="Logical error rate",title=title*" Logical X")
-    lines!(f_x, [-5, -0.5], [-5, -0.5], label="single bit", color=:gray)
-
-    # All to all connectivty
-    scatter!(f_x, log10.(error_rates), log10.(x_error_MA_CA), color=:black, marker=:circle)
-    scatter!(f_x, log10.(error_rates), log10.(x_error_MA_CB), color=:black, marker=:utriangle)
-
-    # Ancil reindex Compilation
-    scatter!(f_x, log10.(error_rates), log10.(x_error_MC_CA), color=:green, marker=:circle)
-    scatter!(f_x, log10.(error_rates), log10.(x_error_MC_CB), color=:green, marker=:utriangle)
-
-    xlims!(ax, high=-0.5, low=-4.0)
-    ylims!(ax, high=-0.5, low=-4.0)
-    # Z plot
-    f_z = f[2,1]
-    ax = f[2,1] = Axis(f_z, xlabel="p_mem",ylabel="Logical error rate",title=title*" Logical Z")
-    lines!(f_z, [-5, -0.5], [-5, -0.5], label="single bit", color=:gray)
-
-    # All to all connectivty
-    scatter!(f_z, log10.(error_rates), log10.(z_error_MA_CA), color=:black, marker=:circle)
-    scatter!(f_z, log10.(error_rates), log10.(z_error_MA_CB), color=:black, marker=:utriangle)
- 
-    # Ancil reindex Compilation
-    scatter!(f_z, log10.(error_rates), log10.(z_error_MC_CA), color=:green, marker=:circle)
-    scatter!(f_z, log10.(error_rates), log10.(z_error_MC_CB), color=:green, marker=:utriangle)
-
-    xlims!(ax, high=-0.5, low=-4.0)
-    ylims!(ax, high=-0.5, low=-4.0)
-
-    ################ Shor syndrome simulation ################
-    cat, scirc, anc_qubits, bit_indices = shor_syndrome_circuit(checks)
-    title = name*" Code - Shor Syndrome Circuit"
-
-    # All to all connectivty - no gate noise 
-    post_ec_error_rates_MA_CA_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, scirc, p, 0, 0, gate_noise*p*m, nsamples=nsamples) for p in error_rates]
-    x_error_MA_CA_shor = [post_ec_error_rates_MA_CA_shor[i][1] for i in eachindex(post_ec_error_rates_MA_CA_shor)]
-    z_error_MA_CA_shor = [post_ec_error_rates_MA_CA_shor[i][2] for i in eachindex(post_ec_error_rates_MA_CA_shor)]
-
-    # All to all connectivty - gate noise == init noise 
-    post_ec_error_rates_MA_CB_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, scirc, p, 0, 0, gate_noise, nsamples=nsamples) for p in error_rates]
-    x_error_MA_CB_shor = [post_ec_error_rates_MA_CB_shor[i][1] for i in eachindex(post_ec_error_rates_MA_CB_shor)]
-    z_error_MA_CB_shor = [post_ec_error_rates_MA_CB_shor[i][2] for i in eachindex(post_ec_error_rates_MA_CB_shor)]
-
-    # Special shor syndrome Compiled circuit
-    shor_new_circuit, shor_order = CircuitCompilation2xn.ancil_reindex_pipeline_shor_syndrome(scirc)
-    shor_cat = CircuitCompilation2xn.reindex_by_dict(cat, shor_order)
-
-    # TODO hack for working around gate commuting problem with Steane code
-    if isa(code, QuantumClifford.ECC.Steane7)
-        non_mz, mz = CircuitCompilation2xn.two_qubit_sieve(shor_new_circuit)
-        batches = CircuitCompilation2xn.calculate_shifts(non_mz)
-        reordered_batches = batches[[1,2,4,3,5,6]]
-        new_non_mz = reduce(vcat, reordered_batches)
-        shor_new_circuit = vcat(new_non_mz,mz)
-    end
-
-    # Special Shor circuit Compilation - no gate noise
-    post_ec_error_rates_MD_CA_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, shor_cat, shor_new_circuit, p, p_shift*p*m, p_wait*p*m, gate_noise*p*m, nsamples=nsamples) for p in error_rates]
-    x_error_MD_CA_shor = [post_ec_error_rates_MD_CA_shor[i][1] for i in eachindex(post_ec_error_rates_MD_CA_shor)]
-    z_error_MD_CA_shor = [post_ec_error_rates_MD_CA_shor[i][2] for i in eachindex(post_ec_error_rates_MD_CA_shor)]
-
-    # Special Shor circuit Compilation - gate noise == init noise 
-    post_ec_error_rates_MD_CB_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, shor_cat, shor_new_circuit, p, p_shift, p_wait, gate_noise, nsamples=nsamples) for p in error_rates]
-    x_error_MD_CB_shor = [post_ec_error_rates_MD_CB_shor[i][1] for i in eachindex(post_ec_error_rates_MD_CB_shor)]
-    z_error_MD_CB_shor = [post_ec_error_rates_MD_CB_shor[i][2] for i in eachindex(post_ec_error_rates_MD_CB_shor)]
-
-    # Shor syndrome plots
-    f_shor_x = f[1, 2]
-    ax = f[1,2] = Axis(f_shor_x, xlabel="p_mem",title=title*" Logical X")
-    lines!(f_shor_x, [-5, -0.5], [-5, -0.5], label="single bit", color=:gray)
-
-    # All to all connectivty
-    scatter!(f_shor_x, log10.(error_rates), log10.(x_error_MA_CA_shor), label="All to all (A2A) - no gate noise", color=:black, marker=:circle)
-    scatter!(f_shor_x, log10.(error_rates), log10.(x_error_MA_CB_shor), label="A2A - gate noise == after encoding error", color=:black, marker=:utriangle)
-
-    # Fancy Shor- specialized comilation
-    scatter!(f_shor_x, log10.(error_rates), log10.(x_error_MD_CA_shor), label="Shor-syndrome Specialized comp (SSSC) - no gate noise", color=:orange, marker=:circle)
-    scatter!(f_shor_x, log10.(error_rates), log10.(x_error_MD_CB_shor), label="SSSC - gate noise == after encoding error", color=:orange, marker=:utriangle)
-
-    xlims!(ax, high=-0.5, low=-4.0)
-    ylims!(ax, high=-0.5, low=-4.0)
-
-    f_shor_z = f[2,2]
-    ax = f[2,2] = Axis(f_shor_z, xlabel="p_mem",title=title*" Logical Z")
-    lines!(f_shor_z, [-5, -0.5], [-5, -0.5], color=:gray)
-
-    # All to all connectivty
-    scatter!(f_shor_z, log10.(error_rates), log10.(z_error_MA_CA_shor), color=:black, marker=:circle)
-    scatter!(f_shor_z, log10.(error_rates), log10.(z_error_MA_CB_shor), color=:black, marker=:utriangle)
-
-    # Fancy Shor- specialized comilation
-    scatter!(f_shor_z, log10.(error_rates), log10.(z_error_MD_CA_shor), color=:orange, marker=:circle)
-    scatter!(f_shor_z, log10.(error_rates), log10.(z_error_MD_CB_shor), color=:orange, marker=:utriangle)
-
-    lines!(f_shor_z, [0,0], [0,0], label="All to all connectivty", color=:black)
-    lines!(f_shor_z, [0,0], [0,0], label="Naive compilation", color=:red)
-    lines!(f_shor_z, [0,0], [0,0], label="Ancil heuristic", color=:green)
-    lines!(f_shor_z, [0,0], [0,0], label="Shor-syndrome specialized comp", color=:orange)
-
-    scatter!(f_shor_z, [0,0], [0,0], label="Constant near-term noise parameters \n(shift error, decoherence, gate noise)", color=:gray, marker=:utriangle)
-    scatter!(f_shor_z, [0,0], [0,0], label="Near-term noise parameters are \nmultiplied by 10*p_mem", color=:gray, marker=:circle)
-
-    xlims!(ax, high=-0.5, low=-4.0)
-    ylims!(ax, high=-0.5, low=-4.0)
-    f[1,3] = Legend(f, ax, "Compilation Style/Gate Noise")
-    f[2,3] = Legend(f, ax, "Compilation Style/Gate Noise")
-
-    return f 
-end
-
 function plot_for_paper_figure(code::AbstractECC, decoder::AbstractSyndromeDecoder, p_shift=0.0001, p_wait=1-exp(-14.5/28_000); name=string(typeof(code)))
     title = name*" Code - Naive Syndrome Circuit"
     checks = parity_checks(code)
@@ -477,15 +325,15 @@ function plot_for_paper_figure(code::AbstractECC, decoder::AbstractSyndromeDecod
     z_error_MB_CB_shor = [post_ec_error_rates_MB_CB_shor[i][2] for i in eachindex(post_ec_error_rates_MB_CB_shor)]
 
     # Gate shuffled circuit 
-    gate_shuffle_circ = CircuitCompilation2xn.gate_Shuffle!(scirc)
+    gate_shuffled_circ = CircuitCompilation2xn.gate_shuffle_circ(scirc)
 
     # Gate shuffle - no gate noise
-    post_ec_error_rates_MS_CA_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, gate_shuffle_circ, p, p_shift*p*m, p_wait*p*m, gate_noise*p*m,  nsamples=nsamples) for p in error_rates]
+    post_ec_error_rates_MS_CA_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, gate_shuffled_circ, p, p_shift*p*m, p_wait*p*m, gate_noise*p*m,  nsamples=nsamples) for p in error_rates]
     x_error_MS_CA_shor = [post_ec_error_rates_MS_CA_shor[i][1] for i in eachindex(post_ec_error_rates_MS_CA_shor)]
     z_error_MS_CA_shor = [post_ec_error_rates_MS_CA_shor[i][2] for i in eachindex(post_ec_error_rates_MS_CA_shor)]
 
     # Gate shuffle- gate noise== init noise
-    post_ec_error_rates_MS_CB_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, gate_shuffle_circ, p, p_shift, p_wait, gate_noise, nsamples=nsamples) for p in error_rates]
+    post_ec_error_rates_MS_CB_shor = [evaluate_code_decoder_shor_syndrome(checks, decoder, ecirc, cat, gate_shuffled_circ, p, p_shift, p_wait, gate_noise, nsamples=nsamples) for p in error_rates]
     x_error_MS_CB_shor = [post_ec_error_rates_MS_CB_shor[i][1] for i in eachindex(post_ec_error_rates_MS_CB_shor)]
     z_error_MS_CB_shor = [post_ec_error_rates_MS_CB_shor[i][2] for i in eachindex(post_ec_error_rates_MS_CB_shor)]
 
@@ -582,7 +430,7 @@ function plot_for_paper_figure(code::AbstractECC, decoder::AbstractSyndromeDecod
     return f 
 end
 
-#f_Steane = my_plot_both_synd(Steane7(), TableDecoder(Steane7()))
+f_Steane = my_plot_both_synd(Steane7(), TableDecoder(Steane7()))
 #f_Shor = my_plot_both_synd(Shor9(), TableDecoder(Shor9()))
 # f_Cleve = my_plot_both_synd(Cleve8(), TableDecoder(Cleve8()))
 # f_P5 = my_plot_both_synd(Perfect5(), TableDecoder(Perfect5()))
@@ -594,12 +442,4 @@ f_t3 = plot_for_paper_figure(Toric(3, 3), PyMatchingDecoder(Toric(3, 3)), name="
 
 #f_t4 = my_plot_both_synd(Toric(4, 4), PyMatchingDecoder(Toric(4, 4)), name="Toric 4x4")
 #f_t6 = my_plot_both_synd(Toric(6, 6), PyMatchingDecoder(Toric(6, 6)), name="Toric 6x6")
-# f_t10 = the_plot_both_synd(Toric(10, 10), PyMatchingDecoder(Toric(10, 10)), name="Toric10")
-
-# H = LDPCDecoders.parity_check_matrix(n, wr, wc)
-# code = CSS(zeros(Bool,size(H)),H)
-# f_ldpc = LDPC_plot(code, PyBeliefPropDecoder(code))
-
-# stab, Cx, Cz = CircuitCompilation2xn.getGoodLDPC(1)
-# code = CSS(Cx, Cz)
-# f_ldpc = LDPC_plot(code, PyBeliefPropDecoder(code))
+# f_t10 = the_plot_both_synd(Toric(10, 10), PyMatchingDecoder(Toric(10, 10)), name="Toric10")
