{
  "abstract": "Thermodynamic control seeks to realize desired functions at minimal thermodynamic cost, yet existing frameworks remain largely confined to slow driving regimes or state-to-state transport. Here we establish a thermodynamic optimal-control theory for Markov jump processes (MJPs) and chemical reaction networks (CRNs) that accommodates objectives over both states and reaction fluxes beyond slow-driving limit. By deriving the thermodynamic Hamilton--Jacobi--Bellman equation, we demonstrate that the optimal dynamics take the form of a perturbed generalized-gradient flow driven by the value function. A convex representation of the entropy-production rate via generalized means identifies its Legendre--Fenchel dual as the dissipation function. The resulting dynamics shares the thermodynamic structure of CRNs and admits an information-geometric characterization. We further derive a thermodynamic Pontryagin equation by recasting the control problem in terms of thermodynamic forces, providing a complementary description of optimal trajectories and clarifying connections to thermodynamic optimal transport. Our results establish a thermodynamic and geometric foundation for controlling MJPs and CRNs beyond mere transport, opening avenues for optimizing biological processes and finite-time thermodynamic operations in far-from-equilibrium regimes.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2611.01734",
  "author_total": 3,
  "authors": [
    {
      "name": "Tetsuya J. Kobayashi"
    },
    {
      "name": "Alix Robin"
    },
    {
      "name": "Shuhei A. Horiguchi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/47m9cj2zv0pm1.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2611.01734",
  "fulltext_url": null,
  "id": "47m9cj2zv0pm1",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2611.01734",
  "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",
      "math-ph"
    ],
    [
      "arxiv",
      "math.MP"
    ],
    [
      "arxiv",
      "physics.bio-ph"
    ],
    [
      "arxiv",
      "physics.chem-ph"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2611.01734",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/47m9cj2zv0pm1.ris",
  "sources": [
    {
      "first_seen": "2026-11-03T12:20:59Z",
      "native_id": "2611.01734",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2611.01734"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "arxiv:physics.chem-ph",
      "subfield": "physical"
    },
    {
      "field": "mathematics",
      "origin": "arxiv:math-ph",
      "subfield": "mathematical-physics"
    },
    {
      "field": "physics",
      "origin": "arxiv:physics.bio-ph",
      "subfield": "biological-medical"
    }
  ],
  "title": "Optimal Control of Chemical Reaction Networks with Thermodynamic Cost",
  "title_text": "Optimal Control of Chemical Reaction Networks with Thermodynamic Cost",
  "type": "preprint",
  "updated_at": "2026-11-05T15:20:22Z",
  "url": "https://research.draconitic.com/paper/47m9cj2zv0pm1",
  "venue": "arXiv",
  "versions": []
}