Works on My QPU: Reproducibility in Quantum Computing Research

arXiv:2607.08348v2 Announce Type: replace Abstract: Quantum computing research increasingly depends on complex software stacks, yet the reproducibility of published results does not receive the priority and longevity mandated by recommendations of large international scientific bodies and best practices in software-centric systems research. In this paper, we present a combined manual and automated large-scale analysis of the reproducibility landscape in quantum computing research, quantify shortcomings, and derive actionable steps forward. We manually evaluate a curated sample of 127 papers using a five-question framework that covers code availability, environment specification, documentation, hardware description, and executability. To place these findings in a broader context, we conduct an automated large-scale screening of nearly 5000 quantum computing papers for the same reproducibility indicators. Our manual analysis reveals that only 24.4% of the sampled papers provide code artefacts, and among those, 64.5% fail to execute successfully in a clean environment. This assessment is corroborated by a large-scale automated analysis that yields a consistent code availability rate of 26.8%. Further, it shows that approximately one-third of the papers with accessible code lack machine-readable environment specifications. The results in this paper indicate that reproducibility is not yet consistently achieved in quantum computing research. In response, we outline a set of practical recommendations that address the observed failure modes and illustrate how reproducibility can be improved in practice.

Abstract:Quantum computing research increasingly depends on complex software stacks, yet the reproducibility of published results does not receive the priority and longevity mandated by recommendations of large international scientific bodies and best practices in software-centric systems research. In this paper, we present a combined manual and automated large-scale analysis of the reproducibility landscape in quantum computing research, quantify shortcomings, and derive actionable steps forward. We manually evaluate a curated sample of 127 papers using a five-question framework that covers code availability, environment specification, documentation, hardware description, and executability. To place these findings in a broader context, we conduct an automated large-scale screening of nearly 5000 quantum computing papers for the same reproducibility indicators. Our manual analysis reveals that only 24.4% of the sampled papers provide code artefacts, and among those, 64.5% fail to execute successfully in a clean environment. This assessment is corroborated by a large-scale automated analysis that yields a consistent code availability rate of 26.8%. Further, it shows that approximately one-third of the papers with accessible code lack machine-readable environment specifications. The results in this paper indicate that reproducibility is not yet consistently achieved in quantum computing research. In response, we outline a set of practical recommendations that address the observed failure modes and illustrate how reproducibility can be improved in practice.

arXiv:2607.08348 [quant-ph]

(or arXiv:2607.08348v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2607.08348 Focus to learn more arXiv-issued DOI via DataCite

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Works on My QPU: Reproducibility in Quantum Computing Research

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