Quantum (Feb 2023)

Perceval: A Software Platform for Discrete Variable Photonic Quantum Computing

  • Nicolas Heurtel,
  • Andreas Fyrillas,
  • Grégoire de Gliniasty,
  • Raphaël Le Bihan,
  • Sébastien Malherbe,
  • Marceau Pailhas,
  • Eric Bertasi,
  • Boris Bourdoncle,
  • Pierre-Emmanuel Emeriau,
  • Rawad Mezher,
  • Luka Music,
  • Nadia Belabas,
  • Benoît Valiron,
  • Pascale Senellart,
  • Shane Mansfield,
  • Jean Senellart

DOI
https://doi.org/10.22331/q-2023-02-21-931
Journal volume & issue
Vol. 7
p. 931

Abstract

Read online

We introduce $Perceval$, an open-source software platform for simulating and interfacing with discrete-variable photonic quantum computers, and describe its main features and components. Its Python front-end allows photonic circuits to be composed from basic photonic building blocks like photon sources, beam splitters, phase-shifters and detectors. A variety of computational back-ends are available and optimised for different use-cases. These use state-of-the-art simulation techniques covering both weak simulation, or sampling, and strong simulation. We give examples of $Perceval$ in action by reproducing a variety of photonic experiments and simulating photonic implementations of a range of quantum algorithms, from Grover's and Shor's to examples of quantum machine learning. $Perceval$ is intended to be a useful toolkit for experimentalists wishing to easily model, design, simulate, or optimise a discrete-variable photonic experiment, for theoreticians wishing to design algorithms and applications for discrete-variable photonic quantum computing platforms, and for application designers wishing to evaluate algorithms on available state-of-the-art photonic quantum computers.