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) – xarray.Dataset A dataset containing counts from the experiment and configurations

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

Returns:

ndarray

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.

Xndarray

Superoperator estimate array where reconstructed CPT superoperators in standard basis are stacked along the first axis.

Endarray

Current POVM estimate

rhondarray

Current initial state estimate

K_targetndarray

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_targetndarray

Target gate superoperator estimate array where reconstructed CPT superoperators in standard basis are stacked along the first axis.

E_targetndarray

Target POVM

rho_targetndarray

Target initial state

Return type:

K