Amazon Braket PennyLane Plugin
The Amazon Braket PennyLane plugin offers four Amazon Braket quantum devices to work with PennyLane:
braket.aws.qubit for running with the Amazon Braket service’s quantum devices, both QPUs and simulators
braket.local.qubit for running the Amazon Braket SDK’s local simulator where you can optionally specify the backend (“default”, “braket_sv”, “braket_dm” etc)
braket.aws.ahs for running with the Amazon Braket service’s analog Hamiltonian simulation QPUs
braket.local.ahs for running analog Hamiltonian simulation on Amazon Braket SDK’s local simulator
The Amazon Braket Python SDK is an open source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket.
PennyLane is a machine learning library for optimization and automatic differentiation of hybrid quantum-classical computations.
The plugin documentation can be found here: https://amazon-braket-pennylane-plugin-python.readthedocs.io/en/latest/.
Features
Provides four devices to be used with PennyLane:
Two gate-based devices, braket.aws.qubit for running on the Amazon Braket service, and braket.local.qubit for running on the Amazon Braket SDK’s local simulator.
Two analog Hamiltonian simulation devices, braket.aws.ahs for running on QPU via the Amazon Braket service, and braket.local.ahs for running on the Amazon Braket SDK’s local simulator.
Combines Amazon Braket with PennyLane’s automatic differentiation and optimization.
For the gate-based devices:
Both devices support most core qubit PennyLane operations.
All PennyLane observables are supported.
Provides custom PennyLane operations to cover additional Braket operations: ISWAP, PSWAP, and many more. Every custom operation supports analytic differentiation.
For the analog Hamiltonian simulation devices:
The devices support ParametrizedEvolution operators created via the PennyLane pulse programming module.
PennyLane observables in the measurement (Z) basis are supported
Provides translation of user-defined pulse level control to simulation and hardware implementation
Installation
Before you begin working with the Amazon Braket PennyLane Plugin, make sure that you installed or configured the following prerequisites:
Download and install Python 3.11 or greater. If you are using Windows, choose the option Add Python to environment variables before you begin the installation.
Make sure that your AWS account is onboarded to Amazon Braket, as per the instructions here.
Download and install PennyLane:
pip install pennylane
You can then install the latest release of the PennyLane-Braket plugin as follows:
pip install amazon-braket-pennylane-pluginYou can also install the development version from source by cloning this repository and running a pip install command in the root directory of the repository:
git clone https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python.git
cd amazon-braket-pennylane-plugin-python
pip install .You can check your currently installed version of amazon-braket-pennylane-plugin with pip show:
pip show amazon-braket-pennylane-pluginor alternatively from within Python:
from braket import pennylane_plugin
pennylane_plugin.__version__Tests
Make sure to install test dependencies first:
pip install -e "amazon-braket-pennylane-plugin-python[test]"Unit tests
Run the unit tests using:
tox -e unit-testsTo run an individual test:
tox -e unit-tests -- -k 'your_test'To run linters, doc, and unit tests:
toxIntegration tests
To run the integration tests, set the AWS_PROFILE as explained in the amazon-braket-sdk-python README:
export AWS_PROFILE=Your_Profile_NameRunning the integration tests creates an S3 bucket in the same account as the AWS_PROFILE with the following naming convention amazon-braket-pennylane-plugin-integ-tests-{account_id}.
Run the integration tests with:
tox -e integ-testsTo run an individual integration test:
tox -e integ-tests -- -k 'your_test'Documentation
To build the HTML documentation, run:
tox -e docsThe documentation can then be found in the doc/build/documentation/html/ directory.
Contributing
We welcome contributions - simply fork the repository of this plugin, and then make a pull request containing your contribution. All contributers to this plugin will be listed as authors on the releases.
We also encourage bug reports, suggestions for new features and enhancements, and even links to cool projects or applications built with the plugin.
Support
Source Code: https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python
Issue Tracker: https://github.com/amazon-braket/amazon-braket-pennylane-plugin-python/issues
General Questions: https://quantumcomputing.stackexchange.com/questions/ask (add the tag amazon-braket)
PennyLane Forum: https://discuss.pennylane.ai
If you are having issues, please let us know by posting the issue on our Github issue tracker, or by asking a question in the forum.
License
This project is licensed under the Apache-2.0 License.
1 maintainer
Metadata
1 maintainer
Release files for amazon-braket-pennylane-plugin 1.36.0
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