PennyLane plugin for Cirq
PennyLane is a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations.
Cirq is a Python library for writing, manipulating, and optimizing quantum circuits and running them against quantum computers and simulators.
This PennyLane plugin allows to use both the software and hardware backends of Cirq as devices for PennyLane.
- Access to Cirq’s simulator backend via the cirq.simulator device
- Support for all PennyLane core functionality
Plugin Name requires both PennyLane and Cirq. It can be installed via pip:
$ python -m pip install pennylane-cirq
Once Pennylane Cirq is installed, the provided Cirq devices can be accessed straight away in PennyLane.
You can instantiate these devices for PennyLane as follows:
import pennylane as qml dev = qml.device('cirq.simulator', wires=2, shots=100, analytic=True)
These devices can then be used just like other devices for the definition and evaluation of QNodes within PennyLane. For more details, see the plugin usage guide and refer to the PennyLane documentation.
We welcome contributions - simply fork the Plugin Name repository, and then make a pull request containing your contribution. All contributors to PennyLane-Cirq 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 on PennyLane and Cirq.
- Source Code: https://github.com/XanaduAI/pennylane-cirq
- Issue Tracker: https://github.com/XanaduAI/pennylane-cirq/issues
If you are having issues, please let us know by posting the issue on our GitHub issue tracker.
Plugin Name is free and open source, released under the Apache License, Version 2.0.
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