iqm.benchmarks.compressive_gst.gst_analysis.run_mgst_wrapper

iqm.benchmarks.compressive_gst.gst_analysis.run_mgst_wrapper#

iqm.benchmarks.compressive_gst.gst_analysis.run_mgst_wrapper(dataset: Dataset, y: ndarray) → tuple[ndarray, ndarray, ndarray, ndarray, ndarray, ndarray, ndarray, ndarray]#

Wrapper function for mGST algorithm execution which prepares an initialization and sets the alg. parameters.

Parameters:

  • dataset (Dataset) – A dataset containing counts from the experiment and configurations

  • y (ndarray) – The circuit outcome probabilities as a num_povm x num_circuits array

Returns:

  • K, Kraus estimate array where each subarray along the first axis contains a set of Kraus operators. The second axis enumerates Kraus operators for a gate specified by the first axis.

  • X, superoperator estimate array where reconstructed CPT superoperators in standard basis are stacked along the first axis.

  • E, current POVM estimate

  • rho, current initial state estimate

  • K_target, target gate Kraus array where each subarray along the first axis contains a set of Kraus operators. The second axis enumerates Kraus operators for a gate specified by the first axis.

  • X_target, target gate superoperator estimate array where reconstructed CPT superoperators in standard basis are stacked along the first axis.

  • E_target, target POVM

  • rho_target, target initial state

Return type:

tuple[ndarray, ndarray, ndarray, ndarray, ndarray, ndarray, ndarray, ndarray]

Contents