pygsti.algorithms.fiducialselection.create_meas_cache

pygsti.algorithms.fiducialselection.create_meas_cache#

create_meas_cache(model, available_meas_fid_list, circuit_cache=None)#

Make a dictionary structure mapping native measurements and circuits to numpy column vectors corresponding to the transpose of the effective measurement effects.

This can then be passed into ‘create_meas_mxs’ to more efficiently generate the matrices for score function evaluation.

Parameters:

  • model (Model) – The model (associates operation matrices with operation labels).

  • available_meas_fid_list (list of Circuits) – Full list of all fiducial circuits available for constructing an informationally complete measurements.

  • circuit_cache (dict) – dictionary of PTMs for the circuits in the available_meas_fid_list

Returns:

A dictionary with keys given be tuples of the form (native_povm, native_povm_effect, ckt) with corresponding entries being the numpy vectors for the transpose of that effective measurement effect.

Return type:

tuple with dictionary and lists of POVM and Effect Key pairs.