mirror of https://github.com/Qiskit/qiskit.git
56 lines
2.8 KiB
YAML
56 lines
2.8 KiB
YAML
---
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features:
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Added the :class:`~qiskit.result.BaseReadoutMitigator` abstract base class
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for implementing classical measurement error mitigators. These objects
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are intended for mitigation measurement errors in
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:class:`~qiskit.result.Counts` objects returned from execution of circuits
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on backends with measurement errors.
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Readout mitigator classes have two main methods:
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* :meth:`~.BaseReadoutMitigator.expectation_value` which computes an
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mitigated expectation value and standard error of a diagonal operator from
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a noisy :class:`~qiskit.result.Counts` object.
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* :meth:`~.BaseReadoutMitigator.quasi_probabilities` that computes an error
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mitigated :class:`~qiskit.result.QuasiDistribution`, including standard
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error, from a noisy counts object.
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Note that currently the :mod:`qiskit.algorithms` module and the
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:class:`~qiskit.utils.QuantumInstance` class still use the legacy mitigators
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migrated from Qiskit Ignis in :mod:`qiskit.utils.mitigation`. It is planned
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to upgrade the module to use the new mitigator classes and deprecate the legacy
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mitgation code in a future release.
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Added the :class:`~qiskit.result.LocalReadoutMitigator` class for
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performing measurement readout error mitigation of local measurement
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errors. Local measurement errors are those that are described by a
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tensor-product of single-qubit measurement errors.
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This class can be initialized with a list of :math:`N` single-qubit of
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measurement error assignment matrices or from a backend using the readout
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error information in the backend properties.
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Mitigation is implemented using local assignment-matrix inversion which has
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complexity of :math:`O(2^N)` for :math:`N`-qubit mitigation of
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:class:`~qiskit.result.QuasiDistribution` and expectation values.
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Added the :class:`~qiskit.result.CorrelatedReadoutMitigator` class for
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performing measurement readout error mitigation of correlated measurement
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errors. This class can be initialized with a single :math:`2^N \times 2^N`
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measurement error assignment matrix that descirbes the error probabilities.
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Mitigation is implemented via inversion of assignment matrix which has
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mitigation complexity of :math:`O(4^N)` of
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:class:`~qiskit.result.QuasiDistribution` and expectation values.
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Added a :attr:`.QuasiDistribution.stddev_upper_bound`
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attribute and a kwarg to the constructor of the :class:`.QuasiDistribution`
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class, which is used for storing standard errors in quasi-probability
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estimates. This is used by :class:`~qiskit.result.BaseReadoutMitigator`
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classes to store the standard error in mitigated quasi probabilities.
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Added a :meth:`~qiskit.result.Counts.shots` method to
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:class:`qiskit.result.Counts` to return the sum of all outcomes in
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the counts.
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