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cirq.experiments.xeb_fitting.characterize_phased_fsim_parameters_with_xeb

Run a classical optimization to fit phased fsim parameters to experimental data, and

cirq.experiments.xeb_fitting.characterize_phased_fsim_parameters_with_xeb(
    sampled_df: pd.DataFrame,
    parameterized_circuits: List['cirq.Circuit'],
    cycle_depths: Sequence[int],
    options: cirq.experiments.xeb_fitting.XEBCharacterizationOptions,
    initial_simplex_step_size: float = 0.1,
    xatol: float = 0.001,
    fatol: float = 0.001,
    verbose: bool = True,
    pool: Optional['multiprocessing.pool.Pool'] = None
) -> cirq.experiments.xeb_fitting.XEBCharacterizationResult

Used in the notebooks

Used in the tutorials

thereby characterize PhasedFSim-like gates.

sampled_df The DataFrame of sampled two-qubit probability distributions returned from sample_2q_xeb_circuits.
parameterized_circuits The circuits corresponding to those sampled in sampled_df, but with some gates parameterized, likely by using parameterize_circuit.
cycle_depths The depths at which circuits were truncated.
options A set of options that controls the classical optimization loop for characterizing the parameterized gates.
initial_simplex_step_size Set the size of the initial simplex for Nelder-Mead.
xatol The xatol argument for Nelder-Mead. This is the absolute error for convergence in the parameters.
fatol The fatol argument for Nelder-Mead. This is the absolute error for convergence in the function evaluation.
verbose Whether to print progress updates.
pool An optional multiprocessing pool to execute circuit simulations in parallel.