{
  "abstract": "How much can the action of an unknown unitary dynamics on one family of states reveal about its action elsewhere? We develop a general framework for out-of-distribution quantum dynamics learning based on the first and second moments of the input distribution. These define a notion of the bias and expressivity of an ensemble, which together control generalization between arbitrary mixed-state training and testing distributions. Our framework shows that only studying the action of a unitary on random real states can learn its action on random complex states, that tensor products of unbiased pure-state ensembles preserve expressivity, and that single-qubit risks are independent of bias. It also recovers earlier locally scrambling results as loose special cases and yields tight product-to-Haar bounds. We conclude with a series of no-go results and limited generalization bounds for learning certain channels, which further serve to underscore the distinctive role of unitarity in enabling out-of-distribution generalization.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.03690",
  "author_total": 3,
  "authors": [
    {
      "name": "Joachim Favre"
    },
    {
      "name": "Armando Angrisani"
    },
    {
      "name": "Zoë Holmes"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8byq3p88ynqmc.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.03690",
  "fulltext_url": null,
  "id": "8byq3p88ynqmc",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.03690",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "quant-ph"
    ],
    [
      "openalex",
      "1702|Quantum Computing Algorithms and Architecture"
    ]
  ],
  "openalex": "W7220470287",
  "pdf_url": "https://arxiv.org/pdf/2610.03690",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-29",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8byq3p88ynqmc.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:36:28Z",
      "native_id": "2610.03690",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.03690"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "Universal Bounds for Out-of-Distribution Unitary Learning",
  "title_text": "Universal Bounds for Out-of-Distribution Unitary Learning",
  "type": "preprint",
  "updated_at": "2026-11-01T12:20:47Z",
  "url": "https://research.draconitic.com/paper/8byq3p88ynqmc",
  "venue": "arXiv",
  "versions": []
}