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Newton

100 years of quantum at the APS Global Summit

Published Apr 1, 2025• 0 citations
Publisher
DOI
10.1016/j.newton.2025.100070

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It is believed that random quantum circuits are difficult to simulate classically. These have been used to demonstrate quantum supremacy: the execution of a computational task on a quantum computer that is infeasible for any classical computer. The task underlying the assertion of quantum supremacy by Arute et al. (Nature, 574, 505--510 (2019)) was initially estimated to require Summit, the world's most powerful supercomputer today, approximately 10,000 years. The same task was performed on the Sycamore quantum processor in only 200 seconds. In this work, we present a tensor network-based classical simulation algorithm. Using a Summit-comparable cluster, we estimate that our simulator can perform this task in less than 20 days. On moderately-sized instances, we reduce the runtime from years to minutes, running several times faster than Sycamore itself. These estimates are based on explicit simulations of parallel subtasks, and leave no room for hidden costs. The simulator's key ingredient is identifying and optimizing the "stem" of the computation: a sequence of pairwise tensor contractions that dominates the computational cost. This orders-of-magnitude reduction in classical simulation time, together with proposals for further significant improvements, indicates that achieving quantum supremacy may require a period of continuing quantum hardware developments without an unequivocal first demonstration.
The maximum energy of the EPR model on a weighted graph is known to be upper-bounded by the sum of the total weight and the value of maximum-weight fractional matching~(MWFM). Recently, Apte, Parekh and Sud~(APS) conjecture that the bound could be strengthened by replacing MWFM with maximum weight matching~(MWM). Here we test this conjecture on a special class of regular graphs that Henning and Yeo constructed many years ago. On this class of regular graphs, MWMs achieve tight lower bounds. As for the maximum energy of the EPR model, we have recently devised a new algorithm called Fractional Entanglement Distribution~(FED) based on quasi-homogeneous fractional matchings, which could achieve rather high accuracy. Applying the FED algorithm to the EPR model on Henning-Yeo graphs, we could thus obtain energy as high as possible and matching value as low as possible, and then make high-precision tests of the APS conjecture. Nevertheless, our numerical results do not show any evidence that the APS conjecture could be violated.