def more_repetitions(self, accumulator: BitstringAccumulator) -> int:
if len(accumulator.bitstrings) == 0:
return self.repetitions_per_chunk
cov = accumulator.covariance()
n_terms = cov.shape[0]
sum_variance = np.sum(cov)
var_of_the_e = sum_variance / len(accumulator.bitstrings)
vpt = var_of_the_e / n_terms
if vpt <= self.variance_bound:
# Done
return 0
return self.repetitions_per_chunk
def measure_grouped_settings(
circuit: 'cirq.Circuit',
grouped_settings: Dict[InitObsSetting, List[InitObsSetting]],
sampler: 'cirq.Sampler',
stopping_criteria: StoppingCriteria,
*,
readout_symmetrization: bool = False,
circuit_sweep: 'cirq.study.sweepable.SweepLike' = None,
) -> List[BitstringAccumulator]:
"""Measure a suite of grouped InitObsSetting settings.
This is a low-level API for accessing the observable measurement
framework. See also `measure_observables` and `measure_observables_df`.
Args:
circuit: The circuit. This can contain parameters, in which case
you should also specify `circuit_sweep`.
grouped_settings: A series of setting groups expressed as a dictionary.
The key is the max-weight setting used for preparing single-qubit
basis-change rotations. The value is a list of settings
compatible with the maximal setting you desire to measure.
Automated routing algorithms like `group_settings_greedy` can
be used to construct this input.
sampler: A sampler.
stopping_criteria: A StoppingCriteria object that can report
whether enough samples have been sampled.
readout_symmetrization: If set to True, each `meas_spec` will be
split into two runs: one normal and one where a bit flip is
incorporated prior to measurement. In the latter case, the
measured bit will be flipped back classically and accumulated
together. This causes readout error to appear symmetric,
p(0|0) = p(1|1).
circuit_sweep: Additional parameter sweeps for parameters contained
in `circuit`. The total sweep is the product of the circuit sweep
with parameter settings for the single-qubit basis-change rotations.
"""
qubits = sorted(
{q
for ms in grouped_settings.keys() for q in ms.init_state.qubits})
qubit_to_index = {q: i for i, q in enumerate(qubits)}
needs_init_layer = _needs_init_layer(grouped_settings)
measurement_param_circuit = _with_parameterized_layers(
circuit, qubits, needs_init_layer)
grouped_settings = {
_pad_setting(max_setting, qubits): settings
for max_setting, settings in grouped_settings.items()
}
circuit_sweep = study.UnitSweep if circuit_sweep is None else study.to_sweep(
circuit_sweep)
# meas_spec provides a key for accumulators.
# meas_specs_todo is a mutable list. We will pop things from it as various
# specs are measured to the satisfaction of the stopping criteria
accumulators = {}
meas_specs_todo = []
for max_setting, circuit_params in itertools.product(
grouped_settings.keys(), circuit_sweep.param_tuples()):
# The type annotation for Param is just `Iterable`.
# We make sure that it's truly a tuple.
circuit_params = dict(circuit_params)
meas_spec = _MeasurementSpec(max_setting=max_setting,
circuit_params=circuit_params)
accumulator = BitstringAccumulator(
meas_spec=meas_spec,
simul_settings=grouped_settings[max_setting],
qubit_to_index=qubit_to_index,
)
accumulators[meas_spec] = accumulator
meas_specs_todo += [meas_spec]
while True:
meas_specs_todo, repetitions = _check_meas_specs_still_todo(
meas_specs=meas_specs_todo,
accumulators=accumulators,
stopping_criteria=stopping_criteria,
)
if len(meas_specs_todo) == 0:
break
flippy_meas_specs, repetitions = _subdivide_meas_specs(
meas_specs=meas_specs_todo,
repetitions=repetitions,
qubits=qubits,
readout_symmetrization=readout_symmetrization,
)
resolved_params = [
flippy_ms.param_tuples(needs_init_layer=needs_init_layer)
for flippy_ms in flippy_meas_specs
]
resolved_params = _to_sweep(resolved_params)
results = sampler.run_sweep(program=measurement_param_circuit,
params=resolved_params,
repetitions=repetitions)
assert len(results) == len(
flippy_meas_specs
), 'Not as many results received as sweeps requested!'
for flippy_ms, result in zip(flippy_meas_specs, results):
accumulator = accumulators[flippy_ms.meas_spec]
bitstrings = np.logical_xor(flippy_ms.flips,
result.measurements['z'])
accumulator.consume_results(
bitstrings.astype(np.uint8, casting='safe'))
return list(accumulators.values())