LocalReadoutError

class LocalReadoutError(physical_qubits=None, backend=None)[source]

An experiment for characterizing local readout error.

Overview

This class constructs a LocalReadoutMitigator containing a sequence of assignment matrices \(A\) characterizing the readout error for the given qubits from the experiment results. The full assignment matrix is accessible via the assignment_matrix() method.

Readout errors affect quantum computation during the measurement of the qubits in a quantum device. By characterizing the readout errors, it is possible to construct a readout error mitigator that is used both to obtain a more accurate distribution of the outputs, and more accurate measurements of expectation value for measurables.

The readout mitigator is generated from an assignment matrix: a \(2^n \times 2^n\) matrix \(A\) such that \(A_{y,x}\) is the probability to observe \(y\) given the true outcome should be \(x\). The assignment matrix is used to compute the mitigation matrix used in the readout error mitigation process itself.

A Local readout mitigator works under the assumption that readout errors are mostly local, meaning readout errors for different qubits are independent of each other. In this case, the assignment matrix is the tensor product of \(n\) \(2 \times 2\) matrices, one for each qubit, making it practical to store the assignment matrix in implicit form, by storing the individual \(2 \times 2\) assignment matrices. The corresponding class in Qiskit is the LocalReadoutMitigator in qiskit.result.

The experiment generates 2 circuits, corresponding to the states \(|0^n\rangle\) and \(|1^n\rangle\), measuring the error in all the qubits at once, and constructs the assignment matrix and local mitigator from the results.

See LocalReadoutErrorAnalysis documentation for additional information on local readout error experiment analysis.

References

[1] Sergey Bravyi, Sarah Sheldon, Abhinav Kandala, David C. Mckay, Jay M. Gambetta, Mitigating measurement errors in multi-qubit experiments, Phys. Rev. A 103, 042605 (2021), doi: 10.1103/PhysRevA.103.042605 (open)

User manual

Readout Mitigation

Analysis class reference

LocalReadoutErrorAnalysis

Experiment options

These options can be set by the set_experiment_options() method.

Options

  • Defined in the class BaseExperiment:

    • max_circuits (Optional[int])

      Default value: None
      The maximum number of circuits per job when running an experiment on a backend.

Example

from qiskit_experiments.library import LocalReadoutError

qubits = list(range(4))
exp = LocalReadoutError(physical_qubits=qubits, backend=backend)
exp.analysis.set_options(plot=True)
exp.set_run_options(shots=10000)

exp_data = exp.run().block_for_results()
display(exp_data.figure(0))
exp_data.analysis_results(dataframe=True)
../_images/qiskit_experiments.library.characterization.LocalReadoutError_1_0.png
name experiment components value quality backend run_time
58ff9f85 Local Readout Mitigator LocalReadoutError [Q0, Q1, Q2, Q3] <qiskit.result.mitigation.local_readout_mitiga... None aer_simulator_from(fake_perth) None

Initialization

Initialize a local readout error characterization experiment.

Parameters:

  • physical_qubits (Iterable[int] | None) – Optional, the backend qubits being characterized for readout error. If None all qubits on the provided backend will be characterized.

  • backend (Backend | None) – Optional, the backend to characterize.

Raises:

QiskitError – If args are not valid.

Attributes

analysis

Return the analysis instance for the experiment

backend

Return the backend for the experiment

experiment_options

Return the options for the experiment.

experiment_type

Return experiment type.

num_qubits

Return the number of qubits for the experiment.

physical_qubits

Return the device qubits for the experiment.

run_options

Return options values for the experiment run() method.

transpile_options

Return the transpiler options for the run() method.

Methods

circuits()[source]

Returns the experiment’s circuits

Return type:

List[QuantumCircuit]

config()

Return the config dataclass for this experiment

Return type:

ExperimentConfig

copy()

Return a copy of the experiment

Return type:

BaseExperiment

classmethod from_config(config)

Initialize an experiment from experiment config

Return type:

BaseExperiment

job_info(backend=None)

Get information about job distribution for the experiment on a specific backend.

Parameters:

backend (Backend) – Optional, the backend for which to get job distribution information. If not specified, the experiment must already have a set backend.

Returns:

A dictionary containing information about job distribution.

  • ”Total number of circuits in the experiment”: Total number of circuits in the experiment.

  • ”Maximum number of circuits per job”: Maximum number of circuits in one job based on backend and experiment settings.

  • ”Total number of jobs”: Number of jobs needed to run this experiment on the currently set backend.

Return type:

dict

Raises:

QiskitError – if backend is not specified.

run(backend=None, sampler=None, analysis='default', timeout=None, backend_run=None, **run_options)

Run an experiment and perform analysis.

Parameters:

  • backend (Backend | None) – Optional, the backend to run on. Will override existing backend settings.

  • sampler (BaseSamplerV2 | None) – Optional, the sampler to run the experiment on. If None then a sampler will be invoked from previously set backend

  • analysis (BaseAnalysis | None) – Optional, a custom analysis instance to use for performing analysis. If None analysis will not be run. If "default" the experiments analysis() instance will be used if it contains one.

  • timeout (float | None) – Time to wait for experiment jobs to finish running before cancelling.

  • backend_run (bool | None) – Use backend run (temp option for testing)

  • run_options – backend runtime options used for circuit execution.

Returns:

The experiment data object.

Raises:

QiskitError – If experiment is run with an incompatible existing ExperimentData container.

Return type:

ExperimentData

set_experiment_options(**fields)

Set the experiment options.

Parameters:

fields – The fields to update the options

Raises:

AttributeError – If the field passed in is not a supported options

set_run_options(**fields)

Set options values for the experiment run() method.

Parameters:

fields – The fields to update the options

See also

The Setting options for your experiment guide for code example.

set_transpile_options(**fields)

Set the transpiler options for run() method.

Parameters:

fields – The fields to update the options

Raises:

QiskitError – If initial_layout is one of the fields.

See also

The Setting options for your experiment guide for code example.