# Mitigation (qiskit.ignis.mitigation)¶

## Measurement¶

The measurement calibration is used to mitigate measurement errors. The main idea is to prepare all $$2^n$$ basis input states and compute the probability of measuring counts in the other basis states. From these calibrations, it is possible to correct the average results of another experiment of interest.

 complete_meas_cal([qubit_list, qr, cr, …]) Return a list of measurement calibration circuits for the full Hilbert space. tensored_meas_cal([mit_pattern, qr, cr, …]) Return a list of calibration circuits MeasurementFilter(cal_matrix, state_labels) Measurement error mitigation filter. TensoredFilter(cal_matrices, …) Tensored measurement error mitigation filter. CompleteMeasFitter(results, state_labels[, …]) Measurement correction fitter for a full calibration TensoredMeasFitter(results, mit_pattern[, …]) Measurement correction fitter for a tensored calibration.

## Expectation Value Measurement¶

The following classes allow mitigation of measurement errors when computing expectation values of diagonal operators from counts.

 expectation_value(counts[, diagonal, …]) Compute the expectation value of a diagonal operator from counts. expval_meas_mitigator_circuits(num_qubits[, …]) Generate measurement error mitigator circuits and metadata. ExpvalMeasMitigatorFitter(result, metadata) Expectation value measurement error mitigator calibration fitter. CTMPExpvalMeasMitigator(generators, rates[, …]) N-qubit CTMP measurement error mitigator. N-qubit measurement error mitigator. 1-qubit tensor product measurement error mitigator.