Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction

Trevor Vincent1, Lee J. O'Riordan1, Mikhail Andrenkov1, Jack Brown1, Nathan Killoran1, Haoyu Qi1, and Ish Dhand1,2

1Xanadu, 777 Bay Street, Toronto, Canada
2Institute of Theoretical Physics and IQST, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany

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We introduce a new open-source software library $Jet$, which uses task-based parallelism to obtain speed-ups in classical tensor-network simulations of quantum circuits. These speed-ups result from i) the increased parallelism introduced by mapping the tensor-network simulation to a task-based framework, ii) a novel method of reusing shared work between tensor-network contraction tasks, and iii) the concurrent contraction of tensor networks on all available hardware. We demonstrate the advantages of our method by benchmarking our code on several Sycamore-53 and Gaussian boson sampling (GBS) supremacy circuits against other simulators. We also provide and compare theoretical performance estimates for tensor-network simulations of Sycamore-53 and GBS supremacy circuits for the first time.

In this work, we introduce the open-source software Jet, which is available at Jet models quantum systems with an arbitrary number of basis states using tensor-networks and a novel task-based framework. We show that Jet can simulate quantum systems faster than competing codes on a variety of computer hardware.

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Cited by

[1] Glen Evenbly, "A Practical Guide to the Numerical Implementation of Tensor Networks I: Contractions, Decompositions, and Gauge Freedom", arXiv:2202.02138, Frontiers in Applied Mathematics and Statistics 8, 806549 (2022).

[2] Alan Morningstar, Markus Hauru, Jackson Beall, Martin Ganahl, Adam G. M. Lewis, Vedika Khemani, and Guifre Vidal, "Simulation of Quantum Many-Body Dynamics with Tensor Processing Units: Floquet Prethermalization", PRX Quantum 3 2, 020331 (2022).

[3] John Brennan, Lee O'Riordan, Kenneth Hanley, Myles Doyle, Momme Allalen, David Brayford, Luigi Iapichino, and Niall Moran, "QXTools: A Julia framework for distributed quantum circuit simulation", The Journal of Open Source Software 7 70, 3711 (2022).

[4] Lukas Burgholzer, Alexander Ploier, and Robert Wille, "Simulation Paths for Quantum Circuit Simulation with Decision Diagrams", arXiv:2203.00703.

[5] Sergio Sánchez-Ramírez, Javier Conejero, Francesc Lordan, Anna Queralt, Toni Cortes, Rosa M Badia, and Artur Garcia-Saez, "RosneT: A Block Tensor Algebra Library for Out-of-Core Quantum Computing Simulation", arXiv:2201.06620.

[6] Diego Guala, Shaoming Zhang, Esther Cruz, Carlos A. Riofrío, Johannes Klepsch, and Juan Miguel Arrazola, "A practical overview of image classification with variational tensor-network quantum circuits", arXiv:2209.11058.

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