cirq.experiments.xeb_fitting.benchmark_2q_xeb_fidelities

Simulate and benchmark two-qubit XEB circuits.

cirq.experiments.xeb_fitting.benchmark_2q_xeb_fidelities(
    sampled_df: pd.DataFrame,
    circuits: Sequence['cirq.Circuit'],
    cycle_depths: Optional[Sequence[int]] = None,
    param_resolver: "cirq.ParamResolverOrSimilarType" = None,
    pool: Optional['multiprocessing.pool.Pool'] = None
) -> pd.DataFrame

This uses the estimator from cirq.experiments.fidelity_estimation.least_squares_xeb_fidelity_from_expectations, but adapted for use on pandas DataFrames for efficient vectorized operation.

Args
`sampled_df`	The sampled results to benchmark. This is likely produced by a call to `sample_2q_xeb_circuits`.
`circuits`	The library of circuits corresponding to the sampled results in `sampled_df`.
`cycle_depths`	The sequence of cycle depths to benchmark the circuits. If not provided, we use the cycle depths found in `sampled_df`. All requested `cycle_depths` must be present in `sampled_df`.
`param_resolver`	If circuits contain parameters, resolve according to this ParamResolver prior to simulation
`pool`	If provided, execute the simulations in parallel.

Returns
A DataFrame with columns 'cycle_depth' and 'fidelity'.

cirq.experiments.xeb_fitting.benchmark_2q_xeb_fidelities

Args

Returns