QPack Scores: Quantitative performance metrics for application-oriented quantum computer benchmarking

• URL: http://arxiv.org/abs/2205.12142v1
• Date: Tue, 24 May 2022 15:18:24 GMT
• Title: QPack Scores: Quantitative performance metrics for application-oriented quantum computer benchmarking
• Authors: Huub Donkers, Koen Mesman, Zaid Al-Ars, Matthias M\"oller
• Abstract summary: This paper presents the benchmark score definitions of QPack, an application-oriented cross-platform benchmarking suite for quantum computers and simulators. A comparison is made between various quantum computer simulators, running both locally and on vendors' remote cloud services.
• Score: 1.0323063834827415
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents the benchmark score definitions of QPack, an application-oriented cross-platform benchmarking suite for quantum computers and simulators, which makes use of scalable Quantum Approximate Optimization Algorithm and Variational Quantum Eigensolver applications. Using a varied set of benchmark applications, an insight of how well a quantum computer or its simulator performs on a general NISQ-era application can be quantitatively made. This paper presents what quantum execution data can be collected and transformed into benchmark scores for application-oriented quantum benchmarking. Definitions are given for an overall benchmark score, as well as sub-scores based on runtime, accuracy, scalability and capacity performance. Using these scores, a comparison is made between various quantum computer simulators, running both locally and on vendors' remote cloud services. We also use the QPack benchmark to collect a small set of quantum execution data of the IBMQ Nairobi quantum processor. The goal of the QPack benchmark scores is to give a holistic insight into quantum performance and the ability to make easy and quick comparisons between different quantum computers

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