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Qiskit 0.26 release notes


0.26.1

Terra 0.17.4

Bug Fixes

  • Fixed an issue with the QuantumInstance with BackendV1 backends with the `max_experiments attribute set to a value less than the number of circuits to run. Previously the QuantumInstance would not correctly split the circuits to run into separate jobs, which has been corrected.

Aer 0.8.2

No change

Ignis 0.6.0

No change

Aqua 0.9.1

No change

IBM Q Provider 0.13.1

No change


0.26.0

Terra 0.17.3

Prelude

This release includes 2 new classes, ProbDistribution and QuasiDistribution, which were needed for compatibility with the recent qiskit-ibmq-provider release’s beta support for the qiskit-runtime(opens in a new tab). These were only added for compatibility with that new feature in the qiskit-ibmq-provider release and the API for these classes is considered experimental and not considered stable for the 0.17.x release series. The interface may change when 0.18.0 is released in the future.

Bug Fixes

  • Fixed an issue in plot_histogram() function where a ValueError would be raised when the function run on distributions with unequal lengths.

Aer 0.8.2

No change

Ignis 0.6.0

No change

Aqua 0.9.1

No change

IBM Q Provider 0.13.1

Prelude

This release introduces a new feature Qiskit Runtime Service. Qiskit Runtime is a new architecture offered by IBM Quantum that significantly reduces waiting time during computational iterations. You can execute your experiments near the quantum hardware, without the interactions of multiple layers of classical and quantum hardware slowing it down.

Qiskit Runtime allows authorized users to upload their Qiskit quantum programs, which are Python code that takes certain inputs, performs quantum and maybe classical computation, and returns the processing results. The same or other authorized users can then invoke these quantum programs by simply passing in the required input parameters.

Note that Qiskit Runtime is currently in private beta for select account but will be released to the public in the near future.

New Features

  • qiskit.providers.ibmq.experiment.analysis_result.AnalysisResult now has an additional verified attribute which identifies if the quality has been verified by a human.

  • qiskit.providers.ibmq.experiment.Experiment now has an additional notes attribute which can be used to set notes on an experiment.

  • This release introduces a new feature Qiskit Runtime Service. Qiskit Runtime is a new architecture that significantly reduces waiting time during computational iterations. This new service allows authorized users to upload their Qiskit quantum programs, which are Python code that takes certain inputs, performs quantum and maybe classical computation, and returns the processing results. The same or other authorized users can then invoke these quantum programs by simply passing in the required input parameters.

    An example of using this new service:

    from qiskit import IBMQ
     
    provider = IBMQ.load_account()
    # Print all avaiable programs.
    provider.runtime.pprint_programs()
     
    # Prepare the inputs. See program documentation on input parameters.
    inputs = {...}
    options = {"backend_name": provider.backend.ibmq_montreal.name()}
     
    job = provider.runtime.run(program_id="runtime-simple",
                               options=options,
                               inputs=inputs)
    # Check job status.
    print(f"job status is {job.status()}")
     
    # Get job result.
    result = job.result()

Upgrade Notes

  • The deprecated Human Bad, Computer Bad, Computer Good and Human Good enum values have been removed from qiskit.providers.ibmq.experiment.constants.ResultQuality. They are replaced with Bad and Good values which should be used with the verified attribute on qiskit.providers.ibmq.experiment.analysis_result.AnalysisResult:

    Old QualityNew QualityVerified
    Human BadBadTrue
    Computer BadBadFalse
    Computer GoodGoodFalse
    Human GoodGoodTrue

    Furthermore, the NO_INFORMATION enum has been renamed to UNKNOWN.

  • The qiskit.providers.ibmq.IBMQBackend.defaults() method now always returns pulse defaults if they are available, regardless whether open pulse is enabled for the provider.

Bug Fixes

  • Fixes the issue wherein passing in a noise model when sending a job to an IBMQ simulator would raise a TypeError. Fixes #894(opens in a new tab)

Other Notes

  • The qiskit.providers.ibmq.experiment.analysis_result.AnalysisResult fit attribute is now optional.
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