pygsti.drivers.bootstrap.gauge_optimize_models

pygsti.drivers.bootstrap.gauge_optimize_models#

gauge_optimize_models(gs_list, target_model, gate_metric='frobenius', spam_metric='frobenius', plot=True)#

Optimizes the “spam weight” parameter used when gauge optimizing a set of models.

This function gauge optimizes multiple times using a range of spam weights and takes the one the minimizes the average spam error multiplied by the average gate error (with respect to a target model).

Parameters:

  • gs_list (list) – The list of Model objects to gauge optimize (simultaneously).

  • target_model (Model) – The model to compare the gauge-optimized gates with, and also to gauge-optimize them to.

  • gate_metric ({ "frobenius", "fidelity", "tracedist" }, optional) – The metric used within the gauge optimization to determining error in the gates.

  • spam_metric ({ "frobenius", "fidelity", "tracedist" }, optional) – The metric used within the gauge optimization to determining error in the state preparation and measurement.

  • plot (bool, optional) – Whether to create a plot of the model-target discrepancy as a function of spam weight (figure displayed interactively).

Returns:

The list of Models gauge-optimized using the best spamWeight.

Return type:

list