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Journal Articles Quantum Year : 2023

Perceval: A Software Platform for Discrete Variable Photonic Quantum Computing

Abstract

We introduce P e r c e v a l , 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 P e r c e v a l 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. P e r c e v a l 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.
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Origin Publication funded by an institution

Dates and versions

hal-03874624 , version 1 (08-02-2024)

Identifiers

Cite

Nicolas Heurtel, Andreas Fyrillas, Grégoire De Gliniasty, Raphaël Le Bihan, Sébastien Malherbe, et al.. Perceval: A Software Platform for Discrete Variable Photonic Quantum Computing. Quantum, 2023, 7, pp.931. ⟨10.22331/q-2023-02-21-931⟩. ⟨hal-03874624⟩
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