Pennylane-ionq

New features since last release

* Application of debiasing and sharpening for error mitigation is made available, with parameters set on device initialization. Error mitigation strategies that need to be set at runtime are defined in the `error_mitigation` dictionary (currently a single strategy, `debias`, is available). Whether or not to apply sharpening to the returned results is set via the parameter `sharpen`. A device using debiasing and sharpening to mitigate errors can be initialized as:

python import pennylane as qml

dev = qml.device("ionq.qpu", wires=2, error_mitigation={"debias": True}, sharpen=True)


For more details, see the [IonQ Guide on sharpening and debiasing](https://ionq.com/resources/debiasing-and-sharpening), or refer to the publication <https://arxiv.org/pdf/2301.07233.pdf> [(#75)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/75) [(#96)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/96)

Improvements 🛠

* The IonQ API version accessed via the plugin is updated from 0.1 to 0.3 [(75)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/75) [(#96)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/96)

* Use new `backend` field to specify `qpu`. [(81)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/81)

Contributors ✍️

This release contains contributions from (in alphabetical order):

Spencer Churchill, Lillian Frederiksen

Breaking changes 💔

* Support for Python 3.8 has been removed, and support for 3.11 has been added. [(78)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/78)

Improvements 🛠

* Added support for `qml.StatePrep` as a state preparation operation. [(77)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/77)

Contributors ✍️

This release contains contributions from (in alphabetical order):

Mudit Pandey,
Jay Soni

New features since last release

* Add support for various IonQ native gates. [(55)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/55)

Contributors

This release contains contributions from (in alphabetical order):

Jon Donovan

Improvements

* Added high level access to the `target` kwarg in the `SimulatorDevice` class for general IonQ devices. [(50)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/50)

Bug Fixes

* Since the histogram of probabilities returned from the remote simulator does not always sum exactly to one, the PennyLane device normalizes them to higher precision. [(53)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/53)

Contributors

This release contains contributions from (in alphabetical order):

Jon Donovan, Christina Lee, Antal Száva

Improvements

* Added support for Python 3.10. [(46)](https://github.com/PennyLaneAI/pennylane-forest/pull/46)

Bug fixes

* Parameters are converted to floats, unwrapping interface data types. [(41)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/41)

* If the response returns as a failure, an error is raised. If the user submits an empty circuit, a warning is raised. [(43)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/43)

Contributors

This release contains contributions from (in alphabetical order):

Christina Lee, Jay Soni, Antal Száva

Improvements

* Return samples from the `QPUDevice` directly instead of resampling from the returned results. [(32)](https://github.com/PennyLaneAI/PennyLane-IonQ/pull/32)

Contributors

This release contains contributions from (in alphabetical order):

Dave Bacon, Nathan Killoran