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

Quantum Physics 2022-05-25 v1 Emerging Technologies

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

Keywords

Cite

@article{arxiv.2205.12142,
  title  = {QPack Scores: Quantitative performance metrics for application-oriented quantum computer benchmarking},
  author = {Huub Donkers and Koen Mesman and Zaid Al-Ars and Matthias Möller},
  journal= {arXiv preprint arXiv:2205.12142},
  year   = {2022}
}

Comments

23 pages, 45 figures

R2 v1 2026-06-24T11:27:12.843Z