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Peeling union find with boundaries #29

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merged 10 commits into from
Jan 31, 2024
Merged

Peeling union find with boundaries #29

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a155b09
testing peeling union find with boundaries
quantumgizmos Jan 30, 2024
7154969
union find with boundaries
quantumgizmos Jan 30, 2024
3f0d2ce
peeling uf bug
quantumgizmos Jan 30, 2024
0b7f19b
looking for bug in planar decoder with boundaries
quantumgizmos Jan 30, 2024
a654e2b
bug found (I think)
quantumgizmos Jan 30, 2024
cc39e81
another bug found
quantumgizmos Jan 30, 2024
02465ab
peeling with boudaries tests passing
quantumgizmos Jan 30, 2024
ef78a06
fix max bit degree requirement
quantumgizmos Jan 31, 2024
b17284e
Removed comments, added max degree check to the cython
quantumgizmos Jan 31, 2024
57083b2
minor code issues
lucasberent Jan 31, 2024
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90 changes: 89 additions & 1 deletion cpp_test/TestUnionFind.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
#include "union_find.hpp"
#include "util.hpp"
#include "bp.hpp"
#include "robin_set.h"

using namespace std;
using namespace ldpc::uf;
Expand Down Expand Up @@ -111,15 +112,102 @@ TEST(UfDecoder, ring_code3){

auto syndrome = vector<uint8_t>{1, 0, 1};

auto decoding = bpd.peel_decode(syndrome, ldpc::uf::NULL_DOUBLE_VECTOR,3);
auto decoding = bpd.peel_decode(syndrome, ldpc::uf::EMPTY_DOUBLE_VECTOR, 3);

ASSERT_TRUE(bpd.pcm_max_bit_degree_2);
tsl::robin_set<int> boundary_bits = {};
ASSERT_EQ(bpd.planar_code_boundary_bits,boundary_bits);

}


TEST(UfDecoder, rep_code){

for(int n = 5; n < 20; n++){

auto pcm = ldpc::gf2codes::rep_code<ldpc::bp::BpEntry>(n);
auto bpd = UfDecoder(pcm);
ASSERT_TRUE(bpd.pcm_max_bit_degree_2);
tsl::robin_set<int> boundary_bits = {0,n-1};
ASSERT_EQ(bpd.planar_code_boundary_bits,boundary_bits);
auto syndrome = vector<uint8_t>(n,0);
syndrome[0] = 1;
syndrome[n-2] = 1;
auto decoding = bpd.peel_decode(syndrome, ldpc::uf::EMPTY_DOUBLE_VECTOR, 1);
auto expected_decoding = vector<uint8_t>(n,0);
expected_decoding[0] = 1;
expected_decoding[n-1] = 1;
ASSERT_EQ(decoding,expected_decoding);

}

}

TEST(UfDecoder, peeling_with_boundaries){


auto pcm = ldpc::gf2sparse::GF2Sparse<ldpc::bp::BpEntry>(2,7);
pcm.insert_entry(0,0);
pcm.insert_entry(0,1);
pcm.insert_entry(0,2);
pcm.insert_entry(0,3);
pcm.insert_entry(1,3);
pcm.insert_entry(1,4);
pcm.insert_entry(1,5);
pcm.insert_entry(1,6);

// ldpc::sparse_matrix_util::print_sparse_matrix(pcm);

auto bpd = UfDecoder(pcm);
ASSERT_TRUE(bpd.pcm_max_bit_degree_2);
tsl::robin_set<int> boundary_bits = {0,1,2,4,5,6};
ASSERT_EQ(bpd.planar_code_boundary_bits,boundary_bits);
auto syndrome = vector<uint8_t>{1,1};
auto weights = vector<double>{-1,0,0,10,0,0,-1};
auto decoding = bpd.peel_decode(syndrome, weights,1);

// ldpc::sparse_matrix_util::print_vector(decoding);
auto expected_decoding = vector<uint8_t>(7,0);
expected_decoding[0] = 1;
expected_decoding[6] = 1;
ASSERT_EQ(decoding,expected_decoding);



}

TEST(UfDecoder, peeling_with_boundaries_edge_case){

auto pcm = ldpc::gf2sparse::GF2Sparse<ldpc::bp::BpEntry>(20,41);
pcm.insert_entry(0,0);pcm.insert_entry(0,5);pcm.insert_entry(0,25);pcm.insert_entry(1,1);pcm.insert_entry(1,6);pcm.insert_entry(1,25);pcm.insert_entry(1,26);pcm.insert_entry(2,2);pcm.insert_entry(2,7);pcm.insert_entry(2,26);pcm.insert_entry(2,27);pcm.insert_entry(3,3);pcm.insert_entry(3,8);pcm.insert_entry(3,27);pcm.insert_entry(3,28);pcm.insert_entry(4,4);pcm.insert_entry(4,9);pcm.insert_entry(4,28);pcm.insert_entry(5,5);pcm.insert_entry(5,10);pcm.insert_entry(5,29);pcm.insert_entry(6,6);pcm.insert_entry(6,11);pcm.insert_entry(6,29);pcm.insert_entry(6,30);pcm.insert_entry(7,7);pcm.insert_entry(7,12);pcm.insert_entry(7,30);pcm.insert_entry(7,31);pcm.insert_entry(8,8);pcm.insert_entry(8,13);pcm.insert_entry(8,31);pcm.insert_entry(8,32);pcm.insert_entry(9,9);pcm.insert_entry(9,14);pcm.insert_entry(9,32);pcm.insert_entry(10,10);pcm.insert_entry(10,15);pcm.insert_entry(10,33);pcm.insert_entry(11,11);pcm.insert_entry(11,16);pcm.insert_entry(11,33);pcm.insert_entry(11,34);pcm.insert_entry(12,12);pcm.insert_entry(12,17);pcm.insert_entry(12,34);pcm.insert_entry(12,35);pcm.insert_entry(13,13);pcm.insert_entry(13,18);pcm.insert_entry(13,35);pcm.insert_entry(13,36);pcm.insert_entry(14,14);pcm.insert_entry(14,19);pcm.insert_entry(14,36);pcm.insert_entry(15,15);pcm.insert_entry(15,20);pcm.insert_entry(15,37);pcm.insert_entry(16,16);pcm.insert_entry(16,21);pcm.insert_entry(16,37);pcm.insert_entry(16,38);pcm.insert_entry(17,17);pcm.insert_entry(17,22);pcm.insert_entry(17,38);pcm.insert_entry(17,39);pcm.insert_entry(18,18);pcm.insert_entry(18,23);pcm.insert_entry(18,39);pcm.insert_entry(18,40);pcm.insert_entry(19,19);pcm.insert_entry(19,24);pcm.insert_entry(19,40);
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Could you indicate what matrix that is? would be important for intuition and to keep the test 'alive' in the future

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Hi. This was just a specific test from the Python Monte Carlo tests that was failing. I ported the pcm and the syndrome over to CPP for debugging. It seems to be resolved now so this test can be deleted.


auto error_rate = std::vector<double>(41,0.18);
auto bpd = ldpc::bp::BpDecoder(pcm, error_rate, 1, ldpc::bp::MINIMUM_SUM, ldpc::bp::PARALLEL, 0.625);

auto syndrome_sparse = std::vector<int>{3, 5, 7, 8, 12, 17, 18, 19};

auto syndrome = std::vector<uint8_t>(pcm.m,0);
for(int i : syndrome_sparse){
syndrome[i] = 1;
}

bpd.decode(syndrome);

ASSERT_FALSE(bpd.converge);

auto ufd = UfDecoder(pcm);

// ldpc::sparse_matrix_util::print_vector(bpd.log_prob_ratios);

auto decoding = ufd.peel_decode(syndrome, bpd.log_prob_ratios,1);

auto decoding_syndrome = pcm.mulvec(decoding);

ASSERT_EQ(decoding_syndrome,syndrome);



}



Expand Down
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27 changes: 27 additions & 0 deletions python_test/test_belief_find.py
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@@ -0,0 +1,27 @@
import pytest
import numpy as np
from ldpc.belief_find_decoder import BeliefFindDecoder
from ldpc.codes import hamming_code, rep_code, ring_code

def test_peeling_input():

pcm = rep_code(3)
decoder = BeliefFindDecoder(pcm, error_rate = 0.1, uf_method="peeling")

pcm = ring_code(3)
decoder = BeliefFindDecoder(pcm, error_rate = 0.1, uf_method="peeling")

pcm = hamming_code(3)

# decoder = BeliefFindDecoder(pcm, error_rate = 0.1, uf_method="peeling")

with pytest.raises(ValueError):
decoder = BeliefFindDecoder(pcm, error_rate = 0.1, uf_method="peeling")


if __name__ == "__main__":
test_peeling_input()




47 changes: 42 additions & 5 deletions python_test/test_qcodes.py
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Expand Up @@ -61,8 +61,8 @@ def quantum_mc_sim(hx, lx, error_rate, run_count, seed, DECODER, run_label, DEBU


def test_400_16_6_hgp():
hx = scipy.sparse.load_npz("/home/luca/Documents/codeRepos/ldpc/python_test/pcms/hx_400_16_6.npz")
lx = scipy.sparse.load_npz("/home/luca/Documents/codeRepos/ldpc/python_test/pcms/lx_400_16_6.npz")
hx = scipy.sparse.load_npz("pcms/hx_400_16_6.npz")
lx = scipy.sparse.load_npz("pcms/lx_400_16_6.npz")

error_rate = 0.03
run_count = 1000
Expand Down Expand Up @@ -99,7 +99,7 @@ def test_400_16_6_hgp():
decoder = BpLsdDecoder(hx, error_rate=error_rate, max_iter=max_iter, bp_method="ms", ms_scaling_factor=0.625,
schedule="parallel", bits_per_step=1, lsd_order=0)
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder,
f"Min-sum LSD parallel schedule osd={osd_order}")
f"Min-sum LSD-0 parallel schedule")

decoder = BpLsdDecoder(hx, error_rate=error_rate, max_iter=5, bp_method="ms", ms_scaling_factor=0.625,
schedule="parallel", bits_per_step=1, lsd_order=osd_order)
Expand All @@ -110,7 +110,7 @@ def test_toric_20():
hx = scipy.sparse.load_npz("python_test/pcms/hx_toric_20.npz")
lx = scipy.sparse.load_npz("python_test/pcms/lx_toric_20.npz")

error_rate = 0.05
error_rate = 0.03
run_count = 500
seed = 42
max_iter = 10
Expand Down Expand Up @@ -141,6 +141,43 @@ def test_toric_20():
schedule="parallel", bits_per_step=1, osd_order=5)
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder,"Min-sum LSD parallel schedule")

def test_surface_20():
hx = scipy.sparse.load_npz("python_test/pcms/hx_surface_20.npz")
lx = scipy.sparse.load_npz("python_test/pcms/lx_surface_20.npz")

error_rate = 0.01
run_count = 10000
seed = 42
max_iter = 5

print(hx.shape)

print(f"Code: [[761, 1, 20]] Surface, error rate: {error_rate}, bp iterations:, {max_iter}, run count: {run_count}, seed: {seed}")
print("...................................................")
print()

decoder = BpOsdDecoder(hx, error_rate=error_rate, max_iter=max_iter, bp_method="ms", ms_scaling_factor = 0.625, schedule="parallel", osd_method = "osd0")
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder, "Min-sum osd-0 parallel schedule")

decoder = BpOsdDecoder(hx, error_rate=error_rate, max_iter=max_iter, bp_method="ms", ms_scaling_factor = 0.625, schedule="parallel", osd_method = "osd_cs", osd_order = 5)
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder,"Min-sum osd-cs-5 parallel schedule")

decoder = BpOsdDecoder(hx, error_rate=error_rate, max_iter=max_iter, bp_method="ms", ms_scaling_factor = 0.625, schedule="parallel", osd_method = "osd_e", osd_order = 5)
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder,"Min-sum osd-e-5 parallel schedule")

decoder = BpOsdDecoder(hx, error_rate=error_rate, max_iter=max_iter, bp_method="ms", ms_scaling_factor = 0.625, schedule="serial", osd_method = "osd0")
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder,"Min-sum osd-0 serial schedule")

decoder = BpOsdDecoder(hx, error_rate=error_rate, max_iter=max_iter, bp_method="ps", schedule="parallel", osd_method = "osd0")
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder,"Prod-sum osd-0 parallel schedule")

decoder = BeliefFindDecoder(hx, error_rate=error_rate, max_iter=max_iter, bp_method="ms", ms_scaling_factor=0.625, schedule="parallel", uf_method="peeling", bits_per_step=1)
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder,"Belief-find parallel schedule")

decoder = BpLsdDecoder(hx, error_rate=error_rate, max_iter=max_iter, bp_method="ms", ms_scaling_factor=0.625,
schedule="parallel", bits_per_step=1, lsd_order=5)
ler, min_logical, speed, _ = quantum_mc_sim(hx, lx, error_rate, run_count, seed, decoder,"Min-sum LSD parallel schedule")


def test_cl_size():
hx = scipy.sparse.load_npz("python_test/pcms/hx_400_16_6.npz")
Expand Down Expand Up @@ -210,4 +247,4 @@ def test_failing_case_lsd_w():

if __name__ == "__main__":

test_failing_case_lsd_w()
test_surface_20()
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