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Deprecate least_squares functions in fidelity_estimation #5428

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Jun 1, 2022
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Deprecate least_squares functions in fidelity_estimation #5428

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15 changes: 15 additions & 0 deletions cirq-core/cirq/experiments/fidelity_estimation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@

import numpy as np

from cirq import _compat
from cirq.circuits import Circuit
from cirq.ops import QubitOrder, QubitOrderOrList
from cirq.sim import final_state_vector
Expand Down Expand Up @@ -224,6 +225,13 @@ def log_xeb_fidelity(
)


@_compat.deprecated(
deadline='v0.16',
fix=(
'Use cirq.experiments.xeb_fitting '
'(benchmark_2q_xeb_fidelities and fit_exponential_decays) instead.'
),
)
def least_squares_xeb_fidelity_from_expectations(
measured_expectations: Sequence[float],
exact_expectations: Sequence[float],
Expand Down Expand Up @@ -303,6 +311,13 @@ def least_squares_xeb_fidelity_from_expectations(
return fidelity, residuals


@_compat.deprecated(
deadline='v0.16',
fix=(
'Use cirq.experiments.xeb_fitting '
'(benchmark_2q_xeb_fidelities and fit_exponential_decays) instead.'
),
)
def least_squares_xeb_fidelity_from_probabilities(
hilbert_space_dimension: int,
observed_probabilities: Sequence[Sequence[float]],
Expand Down
45 changes: 27 additions & 18 deletions cirq-core/cirq/experiments/fidelity_estimation_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -176,12 +176,15 @@ def test_least_squares_xeb_fidelity_from_expectations():
exact_expectations_log.append(np.sum(probabilities * np.log(dim * probabilities)))
uniform_expectations_log.append(np.mean(np.log(dim * probabilities)))

f_lin, r_lin = cirq.experiments.least_squares_xeb_fidelity_from_expectations(
measured_expectations_lin, exact_expectations_lin, [1.0] * n_circuits
)
f_log, r_log = cirq.experiments.least_squares_xeb_fidelity_from_expectations(
measured_expectations_log, exact_expectations_log, uniform_expectations_log
)
with cirq.testing.assert_deprecated(
'Use cirq.experiments.xeb_fitting', deadline='v0.16', count=2
):
f_lin, r_lin = cirq.experiments.least_squares_xeb_fidelity_from_expectations(
measured_expectations_lin, exact_expectations_lin, [1.0] * n_circuits
)
f_log, r_log = cirq.experiments.least_squares_xeb_fidelity_from_expectations(
measured_expectations_log, exact_expectations_log, uniform_expectations_log
)

assert np.isclose(f_lin, 1 - depolarization, atol=0.01)
assert np.isclose(f_log, 1 - depolarization, atol=0.01)
Expand All @@ -192,9 +195,11 @@ def test_least_squares_xeb_fidelity_from_expectations():


def test_least_squares_xeb_fidelity_from_expectations_bad_length():
with pytest.raises(ValueError) as exception_info:
_ = cirq.experiments.least_squares_xeb_fidelity_from_expectations([1.0], [1.0], [1.0, 2.0])
assert '1, 1, and 2' in str(exception_info.value)
with pytest.raises(ValueError, match='1, 1, and 2'):
with cirq.testing.assert_deprecated('Use cirq.experiments.xeb_fitting', deadline='v0.16'):
_ = cirq.experiments.least_squares_xeb_fidelity_from_expectations(
[1.0], [1.0], [1.0, 2.0]
)


def test_least_squares_xeb_fidelity_from_probabilities():
Expand All @@ -221,15 +226,19 @@ def test_least_squares_xeb_fidelity_from_probabilities():
all_probabilities.append(probabilities)
observed_probabilities.append(probabilities[bitstrings])

f_lin, r_lin = cirq.least_squares_xeb_fidelity_from_probabilities(
dim, observed_probabilities, all_probabilities, None, True
)
f_log_np, r_log_np = cirq.least_squares_xeb_fidelity_from_probabilities(
dim, observed_probabilities, all_probabilities, np.log, True
)
f_log_math, r_log_math = cirq.least_squares_xeb_fidelity_from_probabilities(
dim, observed_probabilities, all_probabilities, math.log, False
)
# 2 deprecation warnings for each of the following
with cirq.testing.assert_deprecated(
'Use cirq.experiments.xeb_fitting', deadline='v0.16', count=6
):
f_lin, r_lin = cirq.least_squares_xeb_fidelity_from_probabilities(
dim, observed_probabilities, all_probabilities, None, True
)
f_log_np, r_log_np = cirq.least_squares_xeb_fidelity_from_probabilities(
dim, observed_probabilities, all_probabilities, np.log, True
)
f_log_math, r_log_math = cirq.least_squares_xeb_fidelity_from_probabilities(
dim, observed_probabilities, all_probabilities, math.log, False
)

assert np.isclose(f_lin, 1 - depolarization, atol=0.01)
assert np.isclose(f_log_np, 1 - depolarization, atol=0.01)
Expand Down