def _get_xeb_result(
qubit_pair: GridQubitPair,
circuits: List['cirq.Circuit'],
measurement_results: Sequence[List[np.ndarray]],
num_circuits: int,
repetitions: int,
cycles: List[int],
) -> CrossEntropyResult:
# pytest-cov is unable to detect that this function is called by a
# multiprocessing Pool
# coverage: ignore
simulator = sim.Simulator()
# Simulate circuits to get bitstring probabilities
all_and_observed_probabilities: Dict[int, List[Tuple[
np.ndarray, np.ndarray]]] = collections.defaultdict(list)
empirical_probabilities: Dict[
int, List[np.ndarray]] = collections.defaultdict(list)
for i, circuit in enumerate(circuits):
step_results = simulator.simulate_moment_steps(circuit,
qubit_order=qubit_pair)
moment_index = 0
for depth, measurements in zip(cycles, measurement_results[i]):
while moment_index < 2 * depth:
step_result = next(step_results)
moment_index += 1
# copy=False is safe because state_vector_to_probabilities will copy anyways
amplitudes = step_result.state_vector(copy=False)
probabilities = value.state_vector_to_probabilities(amplitudes)
_, counts = np.unique(measurements, return_counts=True)
empirical_probs = counts / len(measurements)
empirical_probs = np.pad(empirical_probs,
(0, 4 - len(empirical_probs)),
mode='constant')
all_and_observed_probabilities[depth].append(
(probabilities, probabilities[measurements]))
empirical_probabilities[depth].append(empirical_probs)
# Compute XEB result
data = []
purity_data = []
for depth in cycles:
all_probabilities, observed_probabilities = zip(
*all_and_observed_probabilities[depth])
empirical_probs = np.asarray(empirical_probabilities[depth]).flatten()
fidelity, _ = least_squares_xeb_fidelity_from_probabilities(
hilbert_space_dimension=4,
observed_probabilities=observed_probabilities,
all_probabilities=all_probabilities,
observable_from_probability=None,
normalize_probabilities=True,
)
purity = purity_from_probabilities(4, empirical_probs)
data.append(CrossEntropyPair(depth, fidelity))
purity_data.append(SpecklePurityPair(depth, purity))
return CrossEntropyResult( # type: ignore
data=data,
repetitions=repetitions,
purity_data=purity_data)
def _get_xeb_result(qubit_pair: GridQubitPair, circuits: List['cirq.Circuit'],
measurement_results: Sequence[List[np.ndarray]],
num_circuits: int, repetitions: int,
cycles: List[int]) -> CrossEntropyResult:
# pytest-cov is unable to detect that this function is called by a
# multiprocessing Pool
# coverage: ignore
simulator = sim.Simulator()
# Simulate circuits to get bitstring probabilities
all_and_observed_probabilities = collections.defaultdict(
list) # type: Dict[int, List[Tuple[np.ndarray, np.ndarray]]]
for i, circuit in enumerate(circuits):
step_results = simulator.simulate_moment_steps(circuit,
qubit_order=qubit_pair)
moment_index = 0
for depth, measurements in zip(cycles, measurement_results[i]):
while moment_index < 2 * depth:
step_result = next(step_results)
moment_index += 1
amplitudes = step_result.state_vector()
probabilities = np.abs(amplitudes)**2
all_and_observed_probabilities[depth].append(
(probabilities, probabilities[measurements]))
# Compute XEB result
data = []
for depth in cycles:
all_probabilities, observed_probabilities = zip(
*all_and_observed_probabilities[depth])
fidelity, _ = least_squares_xeb_fidelity_from_probabilities(
hilbert_space_dimension=4,
observed_probabilities=observed_probabilities,
all_probabilities=all_probabilities,
observable_from_probability=None,
normalize_probabilities=True)
data.append(CrossEntropyPair(depth, fidelity))
return CrossEntropyResult( # type: ignore
data=data, repetitions=repetitions)