pygsti.algorithms.core.gram_rank_and_eigenvalues

pygsti.algorithms.core.gram_rank_and_eigenvalues#

gram_rank_and_eigenvalues(dataset, prep_fiducials, effect_fiducials, target_model)#

Returns the rank and singular values of the Gram matrix for a dataset.

Parameters:

  • dataset (DataSet) – The data used to populate the Gram matrix

  • prep_fiducials (list of Circuits) – Fiducial Circuits used to construct a informationally complete effective preparation.

  • effect_fiducials (list of Circuits) – Fiducial Circuits used to construct a informationally complete effective measurement.

  • target_model (Model) – A model used to make sense of circuit elements, and to compute the theoretical gram matrix eigenvalues (returned as svalues_target).

Returns:

  • rank (int) – the rank of the Gram matrix

  • svalues (numpy array) – the singular values of the Gram matrix

  • svalues_target (numpy array) – the corresponding singular values of the Gram matrix generated by target_model.