Qiskit 0.26 release notes
0.26.1
Terra 0.17.4
Bug Fixes
- Fixed an issue with the
QuantumInstance
withBackendV1
backends with the`max_experiments
attribute set to a value less than the number of circuits to run. Previously theQuantumInstance
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. 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 aValueError
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 additionalverified
attribute which identifies if thequality
has been verified by a human. -
qiskit.providers.ibmq.experiment.Experiment
now has an additionalnotes
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
andHuman Good
enum values have been removed fromqiskit.providers.ibmq.experiment.constants.ResultQuality
. They are replaced withBad
andGood
values which should be used with theverified
attribute onqiskit.providers.ibmq.experiment.analysis_result.AnalysisResult
:Old Quality New Quality Verified Human Bad Bad True Computer Bad Bad False Computer Good Good False Human Good Good True Furthermore, the
NO_INFORMATION
enum has been renamed toUNKNOWN
. -
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
Other Notes
- The
qiskit.providers.ibmq.experiment.analysis_result.AnalysisResult
fit
attribute is now optional.