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

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arxiv 2205.12142 v1 pith:BKVE3RTP submitted 2022-05-24 quant-ph cs.ET

classification quant-phcs.ET
keywords quantumbenchmarkqpackscoresapplication-orientedbenchmarkingcomputerperformance
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum Computer Benchmarking: An Explorative Systematic Literature Review

    quant-ph 2025-09 conditional novelty 6.0 of 10

    A systematic review of 329 quantum benchmarking studies yields a stack-aligned taxonomy and definitions for hardware-, software-, and application-focused benchmarks.

  2. Quantum Fidelity-per-Cost: A Metric for Evaluation of Quantum Computing Systems

    quant-ph 2026-07 conditional novelty 5.5 of 10

    Cost-aware ranking of cloud QPUs via QFC disagrees with fidelity-only ranking; billing model, not hardware, fixes how the score scales with shot count.

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