LinearOperator Set Tomography Tools Python Package


Package Contents


tuple_replace_at_index(tup, ix, val)


Loads a pygsti dataset from file.


Flattens an irregualr list.

form_ct_data_matrix(ds, number_of_regions, settings[, ...])

do_basic_crosstalk_detection(ds, number_of_regions, ...)

Implements crosstalk detection on multiqubit data (fine-grained data with entries for each experiment).

crosstalk_detection_experiment2(pspec, lengths, ...[, ...])

pygsti.extras.crosstalk.tuple_replace_at_index(tup, ix, val)

Loads a pygsti dataset from file.

This is a wrapper that just checks the first line, and replaces it with the newer outcome specification format if its the old type.


Flattens an irregualr list. From

pygsti.extras.crosstalk.form_ct_data_matrix(ds, number_of_regions, settings, filter_lengths=None)
pygsti.extras.crosstalk.do_basic_crosstalk_detection(ds, number_of_regions, settings, confidence=0.95, verbosity=1, name=None, assume_independent_settings=True, filter_lengths=None)

Implements crosstalk detection on multiqubit data (fine-grained data with entries for each experiment).


dspyGSTi DataSet or numpy array

The multiqubit data to analyze. If this is a numpy array, it must contain time series data and it must be 2-dimensional with each entry being a sequence of settings and measurment outcomes for each qubit region. A region is a set of one or more qubits and crosstalk is assessed between regions. The first n entries are the outcomes and the following entries are settings.

number_of_regions: int, number of regions in experiment

settings: list of length number_of_regions, indicating the number of settings for each qubit region.

confidence : float, optional

verbosity : int, optional

name : str, optional

filter_lengthslist of lengths. If this is not empty the dataset will be filtered and the analysis will only be

done on the sequences of lengths specified in this list. This argument is only used if the dataset is passed in as a pyGSTi DataSet


resultsCrosstalkResults object

The results of the crosstalk detection analysis. This contains: output skeleton graph and DAG from PC Algorithm indicating regions with detected crosstalk, all of the input information.

pygsti.extras.crosstalk.crosstalk_detection_experiment2(pspec, lengths, circuits_per_length, circuit_population_sz, multiplier=3, idle_prob=0.1, structure='1Q', descriptor='A set of crosstalk detections experiments', verbosity=1)