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Merged
perlinm merged 1 commit into from
May 12, 2026
+26 −17
Merged

Minor change to post-selection argument in code-capacity calculations #482

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37 changes: 23 additions & 14 deletions src/qldpc/codes/common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -729,7 +729,7 @@ def get_logical_error_rate_func(
num_samples: int,
max_error_rate: float = 0.3,
*,
discard_weights: Collection[int] = (),
discard_weight: int | Collection[int] = (),
**decoder_kwargs: Any,
) -> ErrorRateFunc:
"""Construct a function from physical --> logical error rate in a code capacity model.
Expand Down Expand Up @@ -760,6 +760,9 @@ def get_logical_error_rate_func(
F(p) = q_0(p) + sum_(k>0) q_k(p) F_k.
We thereby only need to sample errors of weight k > 0.
"""
if not isinstance(discard_weight, Collection):
discard_weight = [discard_weight]

decoder = decoders.get_decoder(self.matrix, **decoder_kwargs)

# sample errors of fixed weight and record failure/discard counts
Expand All @@ -769,7 +772,7 @@ def get_logical_error_rate_func(
for weight in range(1, len(sample_allocation)):
num_failures[weight], num_discards[weight] = (
self._estimate_decoding_infidelity_and_variance(
weight, sample_allocation[weight], decoder, discard_weights
weight, sample_allocation[weight], decoder, discard_weight
)
)
return ErrorRateFunc(
Expand All @@ -781,7 +784,7 @@ def _estimate_decoding_infidelity_and_variance(
error_weight: int,
num_samples: int,
decoder: decoders.Decoder,
discard_weights: Collection[int],
discard_weight: Collection[int],
) -> tuple[int, int]:
"""Sample and correct errors of a fixed weight. Return logical error and discard counts."""
num_failures = 0
Expand All @@ -795,7 +798,7 @@ def _estimate_decoding_infidelity_and_variance(
# decode the error
syndrome = self.matrix @ error
decoded_error = decoder.decode(syndrome.view(np.ndarray)).view(self.field)
if discard_weights and np.count_nonzero(decoded_error) in discard_weights:
if discard_weight and np.count_nonzero(decoded_error) in discard_weight:
num_discards += 1
elif np.any(decoded_error - error):
num_failures += 1
Expand Down Expand Up @@ -1942,7 +1945,7 @@ def get_logical_error_rate_func(
max_error_rate: float = 0.3,
pauli_bias: Sequence[float] | None = None,
*,
discard_weights: Collection[int] = (),
discard_weight: int | Collection[int] = (),
**decoder_kwargs: Any,
) -> ErrorRateFunc:
"""Construct a function from physical --> logical error rate in a code capacity model.
Expand All @@ -1963,6 +1966,9 @@ def get_logical_error_rate_func(
See help(qldpc.codes.ClassicalCode.get_logical_error_rate_func) for more details about how
this method works.
"""
if not isinstance(discard_weight, Collection):
discard_weight = [discard_weight]

# collect relative probabilities of Z, X, and Y errors
pauli_bias_zxy: npt.NDArray[np.floating] | None
if pauli_bias is not None:
Expand Down Expand Up @@ -1992,7 +1998,7 @@ def get_logical_error_rate_func(
decoder,
logical_ops,
pauli_bias_zxy,
discard_weights,
discard_weight,
)
)
return ErrorRateFunc(
Expand All @@ -2006,7 +2012,7 @@ def _estimate_decoding_fidelity_and_variance(
decoder: decoders.Decoder,
logical_ops: npt.NDArray[np.int_],
pauli_bias_zxy: npt.NDArray[np.floating] | None,
discard_weights: Collection[int],
discard_weight: Collection[int],
) -> tuple[int, int]:
"""Sample and correct errors of a fixed weight. Return logical error and discard counts."""
num_failures = 0
Expand All @@ -2032,7 +2038,7 @@ def _estimate_decoding_fidelity_and_variance(
error = np.concatenate([error_x, error_z]).view(self.field)
syndrome = syndrome_matrix @ error
decoded_error = decoder.decode(syndrome.view(np.ndarray)).view(self.field)
if discard_weights and math.symplectic_weight(decoded_error) in discard_weights:
if discard_weight and math.symplectic_weight(decoded_error) in discard_weight:
num_discards += 1 # pragma: no cover
elif np.any(logical_ops @ math.symplectic_conjugate(decoded_error - error)):
num_failures += 1
Expand Down Expand Up @@ -3022,7 +3028,7 @@ def get_logical_error_rate_func(
*,
decoder_x_kwargs: dict[str, Any] | None = None,
decoder_z_kwargs: dict[str, Any] | None = None,
discard_weights: Collection[int] = (),
discard_weight: int | Collection[int] = (),
**decoder_kwargs: Any,
) -> ErrorRateFunc:
"""Construct a function from physical --> logical error rate in a code capacity model.
Expand All @@ -3043,6 +3049,9 @@ def get_logical_error_rate_func(
See help(qldpc.codes.ClassicalCode.get_logical_error_rate_func) for more details about how
this method works.
"""
if not isinstance(discard_weight, Collection):
discard_weight = [discard_weight]

# collect relative probabilities of Z, X, and Y errors
pauli_bias_zxy: npt.NDArray[np.floating] | None
if pauli_bias is not None:
Expand Down Expand Up @@ -3087,7 +3096,7 @@ def get_logical_error_rate_func(
logicals_x,
logicals_z,
pauli_bias_zxy,
discard_weights,
discard_weight,
)
)
return ErrorRateFunc(
Expand All @@ -3103,7 +3112,7 @@ def _estimate_css_decoding_fidelity_and_variance(
logicals_x: npt.NDArray[np.int_],
logicals_z: npt.NDArray[np.int_],
pauli_bias_zxy: npt.NDArray[np.floating] | None,
discard_weights: Collection[int],
discard_weight: Collection[int],
) -> tuple[int, int]:
"""Sample and correct errors of a fixed weight. Return logical error and discard counts."""
num_failures = 0
Expand All @@ -3122,12 +3131,12 @@ def _estimate_css_decoding_fidelity_and_variance(
syndrome_z = self.matrix_x @ error_z
decoded_error_z = decoder_z.decode(syndrome_z.view(np.ndarray)).view(self.field)

if discard_weights and np.count_nonzero(decoded_error_z) in discard_weights:
if discard_weight and np.count_nonzero(decoded_error_z) in discard_weight:
num_discards += 1
continue

failure_z = np.any(logicals_x @ (decoded_error_z - error_z))
if not discard_weights and failure_z:
if not discard_weight and failure_z:
# If we are _not_ post-selecting and there _was_ a decoding failure, then there is
# no need to consider X-type errors, because we will record one failure either way.
num_failures += 1
Expand All @@ -3142,7 +3151,7 @@ def _estimate_css_decoding_fidelity_and_variance(
syndrome_x = self.matrix_z @ error_x
decoded_error_x = decoder_x.decode(syndrome_x.view(np.ndarray)).view(self.field)
if (
discard_weights and np.count_nonzero(decoded_error_x) in discard_weights
discard_weight and np.count_nonzero(decoded_error_x) in discard_weight
): # pragma: no cover
num_discards += 1
continue
Expand Down
6 changes: 3 additions & 3 deletions src/qldpc/codes/common_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -231,7 +231,7 @@ def test_classical_capacity() -> None:

# compute discard rates
logical_error_rate_func = code.get_logical_error_rate_func(
num_samples=4, max_error_rate=0.5, discard_weights=[1]
num_samples=4, max_error_rate=0.5, discard_weight=1
)
assert logical_error_rate_func(0, discard_rate=True) == (0, 0)
assert logical_error_rate_func(0.5, discard_rate=True) == (0.5, 0)
Expand Down Expand Up @@ -539,7 +539,7 @@ def test_quantum_capacity() -> None:

# compute discard rates (trivial deterministic example)
logical_error_rate_func = code.get_logical_error_rate_func(
num_samples=1, max_error_rate=1, discard_weights=[1]
num_samples=1, max_error_rate=1, discard_weight=1
)
assert logical_error_rate_func(0, discard_rate=True) == (0, 0)

Expand Down Expand Up @@ -746,6 +746,6 @@ def test_css_capacity() -> None:

# compute discard rates (trivial deterministic example)
logical_error_rate_func = code.get_logical_error_rate_func(
num_samples=1, max_error_rate=1, discard_weights=[1]
num_samples=1, max_error_rate=1, discard_weight=1
)
assert logical_error_rate_func(0, discard_rate=True) == (0, 0)