{
  "abstract": "AI agents are increasingly capable of constructing quantum algorithms and proofs, yet machine-checked proofs alone cannot guarantee that the intended problem is solved or that resource claims match the verified computation. Here we introduce Lean-QuantumAlg, a Lean 4 framework for trustworthy AI-assisted development of quantum algorithms. Its Algorithm-Solves-Problem contract binds correctness, success probability, borrowed-state restoration and quantum and classical resource bounds to a single execution, while separating the guarantees that Lean checks from the problem specifications and execution models that humans review. We demonstrate the framework on nine AI-formalized quantum algorithms, from Grover search to quantum attacks on RSA-2048 and P-256, with less than 1% of each algorithm's imported source code requiring statement-level human review once the shared framework has been audited. By integrating reusable mathematical foundations, certified algorithmic primitives and execution-grounded verification, Lean-QuantumAlg provides a basis for AI agents to construct and certify quantum algorithms, opening a path toward scalable AI-driven discovery of quantum algorithms.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.30216",
  "author_total": 5,
  "authors": [
    {
      "name": "Lei Zhang"
    },
    {
      "name": "Mingrui Jing"
    },
    {
      "name": "Yusheng Zhao"
    },
    {
      "name": "Jiahong Liu"
    },
    {
      "name": "Xin Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1zerjjgaz3snw.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.30216",
  "fulltext_url": null,
  "id": "1zerjjgaz3snw",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.30216",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "quant-ph"
    ],
    [
      "openalex",
      "1702|Quantum Computing Algorithms and Architecture"
    ]
  ],
  "openalex": "W7223336041",
  "pdf_url": "https://arxiv.org/pdf/2610.30216",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-23",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1zerjjgaz3snw.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:35:15Z",
      "native_id": "2610.30216",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.30216"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "Lean-QuantumAlg: A Framework for AI Agents to Produce Quantum Algorithms that Humans Can Trust",
  "title_text": "Lean-QuantumAlg: A Framework for AI Agents to Produce Quantum Algorithms that Humans Can Trust",
  "type": "preprint",
  "updated_at": "2026-10-30T12:35:15Z",
  "url": "https://research.draconitic.com/paper/1zerjjgaz3snw",
  "venue": "arXiv",
  "versions": []
}