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arXiv · 2110.03137

Application-Oriented Performance Benchmarks for Quantum Computing

Thomas Lubinski·Sonika Johri·Paul Varosy·Jeremiah Coleman·Luning Zhao·Jason Necaise·Charles H. Baldwin·Karl Mayer·Timothy Proctor
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Abstract

In this work we introduce an open source suite of quantum application-oriented performance benchmarks that is designed to measure the effectiveness of quantum computing hardware at executing quantum applications. These benchmarks probe a quantum computer's performance on various algorithms and small applications as the problem size is varied, by mapping out the fidelity of the results as a function of circuit width and depth using the framework of volumetric benchmarking. In addition to estimating the fidelity of results generated by quantum execution, the suite is designed to benchmark certain aspects of the execution pipeline in order to provide end-users with a practical measure of both the quality of and the time to solution. Our methodology is constructed to anticipate advances in quantum computing hardware that are likely to emerge in the next five years. This benchmarking suite is designed to be readily accessible to a broad audience of users and provides benchmarks that correspond to many well-known quantum computing algorithms.

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Thomas Lubinski, Sonika Johri, Paul Varosy, Jeremiah Coleman, Luning Zhao, Jason Necaise, Charles H. Baldwin, Karl Mayer, Timothy Proctor. 2021-10-07. Application-Oriented Performance Benchmarks for Quantum Computing. https://doi.org/10.1109/tqe.2023.3253761

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