PennyLane-Qrack Plugin

Release

1.0.0

The PennyLane-Qrack plugin integrates the Qrack quantum computing framework with PennyLane’s quantum machine learning capabilities.

Performance can benefit greatly from following the Qrack repository “Quick Start” and “Power user considerations.”

This plugin is addapted from the PennyLane-Qulacs plugin, under the Apache License 2.0, with many thanks to the original developers!

PennyLane is a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations.

unitaryfund/qrack (formerly vm6502q/qrack) is a software library for quantum computing, written in C++ and with GPU support.

PennyLane Catalyst provides optional quantum just-in-time (QJIT) compilation, for improved performance.

Once PennyLane-Qrack is installed, the provided Qrack devices can be accessed straight away in PennyLane, without the need to import any additional packages.

Devices

Currently, PennyLane-Qrack provides one Qrack device for PennyLane:


Tutorials

Check out these demos to see the PennyLane-Qrack plugin in action:


You can use any of the qubit based demos from the PennyLane documentation, for example the tutorial on qubit rotation, and simply replace 'default.qubit' with the 'qrack.simulator' device:

dev = qml.device('qrack.simulator', wires=XXX)