Quantum (May 2022)

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

  • Trevor Vincent,
  • Lee J. O'Riordan,
  • Mikhail Andrenkov,
  • Jack Brown,
  • Nathan Killoran,
  • Haoyu Qi,
  • Ish Dhand

DOI
https://doi.org/10.22331/q-2022-05-09-709
Journal volume & issue
Vol. 6
p. 709

Abstract

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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.