qiskit.ignis.mitigation.TensoredFilter

__init__(cal_matrices, substate_labels_list)

Initialize a tensored measurement error mitigation filter using the cal_matrices from a tensored measurement calibration fitter.

Parameters

• cal_matrices (matrix) – the calibration matrices for applying the correction.
• substate_labels_list (list) – for each calibration matrix a list of the states (as strings, states in the subspace)

apply(raw_data, method='least_squares')

Apply the calibration matrices to results.

Parameters

• raw_data (dict or Result) –

  The data to be corrected. Can be in one of two forms:

  • A counts dictionary from results.get_counts
  • A Qiskit Result

• method (str) –

  fitting method. The following methods are supported:

  • ’pseudo_inverse’: direct inversion of the cal matrices.
  • ’least_squares’: constrained to have physical probabilities.
  • If None, ‘least_squares’ is used.

Returns

The corrected data in the same form as raw_data

Return type

dict or Result

Raises

QiskitError – if raw_data is not in a one of the defined forms.

Return cal_matrices.

Return the number of qubits. See also MeasurementFilter.apply()

Return _qubit_list_sizes.

Return _substate_labels_list