Perspective on AI and quantum open-source software

Abstract

Quantum open-source software provides essential infrastructure for quantum science, and artificial intelligence (AI) is reshaping its capabilities and transforming its development. However, verifying quantum software at scale remains difficult, and AI-generated contributions can increase the workload of maintainers. In this Perspective, we examine verification as a central requirement for reliable AI-assisted quantum software development and research. We analyze public repositories, records covering 110 repositories from five annual quantum open-source hackathons that we organize, and responses from more than 1600 participants in a community survey. Our analysis connects limitations in automated verification with the review burden on quantum software maintainers. We propose verification practices and contribution standards that require contributors to support their changes with reproducible evidence for maintainer review. We also examine how quantum open-source software can provide infrastructure for AI-driven research whose results the community can independently verify and build upon. We maintain an open-source companion repository to support reproducibility and help projects adopt and refine these proposals. Together, these contributions help the quantum open-source software community translate advances in AI into reliable quantum research through reproducible verification.

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Cite

BibTeX RIS

BibTeX

@misc{li2026perspective,
  title = {{Perspective on AI and quantum open-source software}},
  author = {Changhao Li and Bradley A. Chase and Veena Vijayakumar and Mathys Rennela and Alessandro Cosentino and Naixu Guo and Sebastian Hassinger and Farrokh Labib and Seun Omonije and Patrick Rebentrost and Vincent Russo and Nathan Shammah and William J. Zeng and Ben Castanon},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.38049},
  eprint = {2610.38049},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.38049},
  note = {CC BY 4.0},
}

RIS

TY  - UNPB
TI  - Perspective on AI and quantum open-source software
AU  - Changhao Li
AU  - Bradley A. Chase
AU  - Veena Vijayakumar
AU  - Mathys Rennela
AU  - Alessandro Cosentino
AU  - Naixu Guo
AU  - Sebastian Hassinger
AU  - Farrokh Labib
AU  - Seun Omonije
AU  - Patrick Rebentrost
AU  - Vincent Russo
AU  - Nathan Shammah
AU  - William J. Zeng
AU  - Ben Castanon
PY  - 2026
DA  - 2026/10/27
PB  - arXiv
DO  - 10.48550/arxiv.2610.38049
UR  - https://arxiv.org/abs/2610.38049
AB  - Quantum open-source software provides essential infrastructure for quantum science, and artificial intelligence (AI) is reshaping its capabilities and transforming its development. However, verifying quantum software at scale remains difficult, and AI-generated contributions can increase the workload of maintainers. In this Perspective, we examine verification as a central requirement for reliable AI-assisted quantum software development and research. We analyze public repositories, records covering 110 repositories from five annual quantum open-source hackathons that we organize, and responses from more than 1600 participants in a community survey. Our analysis connects limitations in automated verification with the review burden on quantum software maintainers. We propose verification practices and contribution standards that require contributors to support their changes with reproducible evidence for maintainer review. We also examine how quantum open-source software can provide infrastructure for AI-driven research whose results the community can independently verify and build upon. We maintain an open-source companion repository to support reproducibility and help projects adopt and refine these proposals. Together, these contributions help the quantum open-source software community translate advances in AI into reliable quantum research through reproducible verification.
ER  -

Abstract

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