pygsti.extras.rpe.rpetools.analyze_rpe_data

pygsti.extras.rpe.rpetools.analyze_rpe_data#

analyze_rpe_data(input_dataset, true_or_target_model, string_list_d, rpeconfig_inst, do_consistency_check=False, k_list=None)#

Compute angle estimates and compare to true or target values for alpha, epsilon, and theta. (“True” will typically be used for simulated data, when the true angle values are known a priori; “target” will typically be used for experimental data, where we do not know the true angle values, and can only compare to our desired angles.)

Parameters:

  • input_dataset (DataSet) – The dataset containing the RPE experiments.

  • true_or_target_model (Model) – The model used to generate the RPE data OR the target model.

  • string_list_d (dict) – The dictionary of operation sequence lists used for the RPE experiments. This should be generated via make_rpe_string_list_d.

  • rpeconfig_inst (RPEconfig object) – Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns:

resultsD – A dictionary of the results. The keys of the dictionary are:

  • ’alphaHatList’ : List (ordered by k) of alpha estimates.

  • ’epsilonHatList’ : List (ordered by k) of epsilon estimates.

  • ’thetaHatList’ : List (ordered by k) of theta estimates.

  • ’alphaErrorList’ : List (ordered by k) of difference between true alpha and RPE estimate of alpha.

  • ’epsilonErrorList’ : List (ordered by k) of difference between true epsilon and RPE estimate of epsilon.

  • ’thetaErrorList’ : List (ordered by k) of difference between true theta and RPE estimate of theta.

  • ’PhiFunErrorList’ : List (ordered by k) of _sin_phi2 values.

Return type:

dict