{
  "abstract": "Decoded quantum interferometry (DQI) is a novel paradigm for tackling approximate optimization problems on quantum computers. This framework comes with strong performance guarantees and exploits a well-established duality between optimization and coding theory. A central question, however, is whether DQI can actually provably outperform all polynomial-time classical algorithms. In this work, we establish such an advantage in an oracle setting: we consider an optimization task called folded optimal polynomial intersection (folded OPI), where the acceptance sets are chosen randomly and accessed through membership oracles. We establish a strict gap between the approximation ratio achievable by any polynomial-time classical algorithm and the approximation ratio achieved by the DQI algorithm. Our proof builds on Jordan et al.'s DQI framework for approximate optimization and extends the classical lower-bound method underlying Yamakawa and Zhandry's exact-search oracle separation to approximation. Building on recent developments by Sun and Wootters, Horinaga and Yamakawa, and Jo, we further show that a modified version of the DQI algorithm achieves a strictly higher score guarantee on typical sampled folded OPI instances. As a concrete example, for code rate $0.3$, DQI achieves expected scores of approximately $0.85$. In contrast, exceeding the classical threshold of $0.65$ by any fixed amount with constant probability on sampled instances requires super-polynomially many classical membership queries.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.02145",
  "author_total": 5,
  "authors": [
    {
      "name": "Maximilian J. Kramer"
    },
    {
      "name": "Elies Gil-Fuster"
    },
    {
      "name": "Benjamin D. M. Jones"
    },
    {
      "name": "Jens Eisert"
    },
    {
      "name": "Franz J. Schreiber"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cq7ytd2c47c77.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.02145",
  "fulltext_url": null,
  "id": "cq7ytd2c47c77",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.02145",
  "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",
      "cs.CC"
    ],
    [
      "arxiv",
      "cs.DS"
    ],
    [
      "arxiv",
      "quant-ph"
    ],
    [
      "openalex",
      "1702|Quantum Computing Algorithms and Architecture"
    ]
  ],
  "openalex": "W7216195416",
  "pdf_url": "https://arxiv.org/pdf/2610.02145",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-02",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/cq7ytd2c47c77.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:26:45Z",
      "native_id": "2610.02145",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.02145"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "A provable quantum advantage for approximate optimization via decoded quantum interferometry",
  "title_text": "A provable quantum advantage for approximate optimization via decoded quantum interferometry",
  "type": "preprint",
  "updated_at": "2026-10-30T12:26:45Z",
  "url": "https://research.draconitic.com/paper/cq7ytd2c47c77",
  "venue": "arXiv",
  "versions": []
}