{
  "abstract": "Heat generation limits computation, classical and quantum, from single logic gates to entire data centers. However, an in principle limiting physical factor can sometimes be turned into a resource. In reservoir computing, energy dissipation is what gives a reservoir its fading memory. Here, we introduce a paradigm where the data injection itself is encoded on the time-dependent temperature of a thermal bath. We derive an exact expression for the nonlinear response of any fixed readout, and prove a rigorous memory-nonlinearity trade-off which turns out to be a structural necessity, rather than a tunable dynamical regime, since the same coupling that injects data also enforces equilibration. We illustrate both results with a driven qubit, using a single free parameter, and with a pair of coupled qubits, where the breaking of a discrete symmetry opens a fifteen-dimensional space to a single observable, yet that observable alone recovers just over half of it. This refutes the misconception that large Hilbert spaces guarantee computational power. Our results relocate the memory-nonlinearity trade-off from the reservoir's dynamics to its measurement channel, pointing to observable choice and bath engineering (instead of Hamiltonian control) as the physical levers for a thermally-native quantum reservoir computer.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2611.07187",
  "author_total": 2,
  "authors": [
    {
      "name": "Thiago Werlang"
    },
    {
      "name": "Daniel Valente"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dkw2n50w2wfxg.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2611.07187",
  "fulltext_url": null,
  "id": "dkw2n50w2wfxg",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2611.07187",
  "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",
      "cond-mat.stat-mech"
    ],
    [
      "arxiv",
      "quant-ph"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2611.07187",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dkw2n50w2wfxg.ris",
  "sources": [
    {
      "first_seen": "2026-11-06T18:21:30Z",
      "native_id": "2611.07187",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2611.07187"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    },
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.stat-mech",
      "subfield": "statistical-nonlinear"
    }
  ],
  "title": "Thermally-driven quantum reservoir computing",
  "title_text": "Thermally-driven quantum reservoir computing",
  "type": "preprint",
  "updated_at": "2026-11-08T21:20:39Z",
  "url": "https://research.draconitic.com/paper/dkw2n50w2wfxg",
  "venue": "arXiv",
  "versions": []
}