{
  "abstract": "Sample-based quantum diagonalization has been used as an impurity solver in density matrix embedding theory (DMET), but always with fixed-form circuits and without comparison to classical selection at the same subspace size. We introduce GENIE, a DMET impurity solver in which a generative transformer learns the sampling circuit, trained on the quantum-selected configuration interaction energy. On N2, hydrogen chains, water and a hydrogen ring, we compare GENIE at equal determinant budget with classical selected configuration interaction (CIPSI, ASCI, heat-bath CI) and with DMET combined with sample-based quantum diagonalization (SQD). GENIE selects: for N2 at 200 determinants it is within a factor of 1.7 of CIPSI and 25 to 1000 times more accurate than the determinants a fixed circuit actually samples, while standard SQD reaches good energies mainly by filling the subspace. GENIE does not beat the best classical selection, and its circuits require fault-tolerant hardware. Its failures are governed by the compactness of the wavefunction relative to the budget, not by correlation strength. A cheap estimate from coupled-cluster amplitudes predicts this compactness. A router built on it never recommended GENIE where it then failed, apart from seed-to-seed variance, and it transferred unchanged to a blind test on new systems. We also identify two benchmarking pitfalls that can create apparent quantum advantages of one to two orders of magnitude.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.41957",
  "author_total": 2,
  "authors": [
    {
      "name": "Awadhoot Vijay Loharkar"
    },
    {
      "name": "Arcesio Castañeda Medina"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2se1q6texhwh0.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.41957",
  "fulltext_url": null,
  "id": "2se1q6texhwh0",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.41957",
  "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": null,
  "pdf_url": "https://arxiv.org/pdf/2610.41957",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/2se1q6texhwh0.ris",
  "sources": [
    {
      "first_seen": "2026-11-02T12:21:15Z",
      "native_id": "2610.41957",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.41957"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "GENIE: learned quantum circuits as embedding impurity solvers, and why compactness, not correlation strength, decides when they work",
  "title_text": "GENIE: learned quantum circuits as embedding impurity solvers, and why compactness, not correlation strength, decides when they work",
  "type": "preprint",
  "updated_at": "2026-11-04T15:20:51Z",
  "url": "https://research.draconitic.com/paper/2se1q6texhwh0",
  "venue": "arXiv",
  "versions": []
}