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Qulacs plugin for PennyLane, the cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations
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README.md

PennyLane Qulacs Plugin

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

Qulacs is a high-performance quantum circuit simulator for simulating large, noisy or parametric quantum circuits. Implemented in C/C++ and with python interface, Qulacs achieved both high speed circuit simulation and high usability.

This PennyLane plugin allows the use of the Qulacs simulator as device for PennyLane.

Features

  • Provides qulacs.simulator device to be used with PennyLane.
  • Combine Qulacs high performance simulator with PennyLane's automatic differentiation and optimization.

Installation

Installing the latest master version can be done directly using pip:

pip install git+https://github.com/soudy/pennylane-qulacs@master

or by cloning this repo:

git clone https://github.com/soudy/pennylane-qulacs
cd pennylane-qulacs
pip install .

Benchmarks

We ran a 100 executions of 4 layer quantum neural network strongly entangling layer and compared the runtimes between CPU and GPU.

Qulacs PennyLane plugin benchmarks Qulacs PennyLane plugin benchmarks table

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