def test_planar_mps_decoder_positive_max_coset_probability(mode):
# parameters
code = PlanarCode(9, 9)
decoder = PlanarMPSDecoder(chi=48, mode=mode)
error_model = BiasedDepolarizingErrorModel(bias=100)
error_probability = 0.41
# logged run values
error = pt.unpack([
"c96aa012210dc2254031f15d9ce80c871fb864b510c91086e112a018f8aece7406638fdc00",
290
])
syndrome = pt.unpack(["8f59cd273bd1c027b3b925085af85f2aaf22", 144])
assert np.array_equal(syndrome, pt.bsp(error, code.stabilizers.T))
# debug
# print(code.ascii_art(syndrome, code.new_pauli(error)))
# decode
prob_dist = error_model.probability_distribution(error_probability)
any_recovery = decoder.sample_recovery(code, syndrome)
# coset probabilities
coset_ps, recoveries = decoder._coset_probabilities(
prob_dist, any_recovery)
print('mode={}, coset_ps={}'.format(mode, coset_ps))
max_coset_p, max_recovery = max(
zip(coset_ps, recoveries),
key=lambda coset_p_recovery: coset_p_recovery[0])
success = np.all(
pt.bsp(max_recovery.to_bsf() ^ error, code.logicals.T) == 0)
print('### success=', success)
assert mp.isfinite(
max_coset_p
) and max_coset_p > 0, 'Max coset probability not as expected'
def test_planar_mps_decoder_small_code_negative_coset_probability(chi, mode):
# parameters
code = PlanarCode(3, 3)
decoder = PlanarMPSDecoder(chi=chi, mode=mode)
error_model = DepolarizingErrorModel()
error_probability = 0.1
# logged run values
error = pt.unpack(["e0048000", 26])
syndrome = pt.bsp(error, code.stabilizers.T)
# debug
print()
print(code.ascii_art(syndrome, code.new_pauli(error)))
# decode
prob_dist = error_model.probability_distribution(error_probability)
any_recovery = decoder.sample_recovery(code, syndrome)
# coset probabilities
coset_ps, recoveries = decoder._coset_probabilities(
prob_dist, any_recovery)
print('chi={}, mode={}, coset_ps={}'.format(chi, mode, coset_ps))
max_coset_p, max_recovery = max(
zip(coset_ps, recoveries),
key=lambda coset_p_recovery: coset_p_recovery[0])
success = np.all(
pt.bsp(max_recovery.to_bsf() ^ error, code.logicals.T) == 0)
print('### success=', success)
assert mp.isfinite(
max_coset_p
) and max_coset_p > 0, 'Max coset probability not as expected'
assert np.all(
np.array(coset_ps) >= 0), 'At least one coset probability is negative'
def test_planar_mps_decoder_sample_recovery(error_pauli):
error = error_pauli.to_bsf()
code = error_pauli.code
syndrome = pt.bsp(error, code.stabilizers.T)
recovery_pauli = PlanarMPSDecoder.sample_recovery(code, syndrome)
recovery = recovery_pauli.to_bsf()
assert np.array_equal(pt.bsp(recovery, code.stabilizers.T), syndrome), (
'recovery {} does not give the same syndrome as the error {}'.format(
recovery, error))
assert np.all(pt.bsp(recovery ^ error, code.stabilizers.T) == 0), (
'recovery ^ error ({} ^ {}) does not commute with stabilizers.'.format(
recovery, error))
def test_planar_mps_decoder_zero_max_coset_probability(code, chi):
decoder = PlanarMPSDecoder(chi=chi, mode='c')
error_model = BiasedDepolarizingErrorModel(bias=1000)
random_seed = 69
# probabilities
probability = 0.4
prob_dist = error_model.probability_distribution(probability)
# error
error = error_model.generate(code, probability,
np.random.default_rng(random_seed))
# syndrome
syndrome = pt.bsp(error, code.stabilizers.T)
# any_recovery
any_recovery = decoder.sample_recovery(code, syndrome)
# coset probabilities
coset_ps, _ = decoder._coset_probabilities(prob_dist, any_recovery)
print(coset_ps)
max_coset_p = max(coset_ps)
assert mp.isfinite(
max_coset_p
) and max_coset_p > 0, 'Max coset probability out of bounds {}'.format(
coset_ps)