Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction
Trevor Vincent, Lee J. O apos Riordan, Mikhail Andrenkov, Jack Brown, Nathan Killoran, Haoyu Qi, Ish Dhand
Abstract
We introduce a new open-source software library <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>J</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi></mml:math>, 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.