{
  "abstract": "Machine-learned interatomic potentials enable multireference-quality reaction dynamics but do not retain the electronic structure underlying the predicted energies and forces. Recovering this information by independently performing complete active space self-consistent field (CASSCF) calculations is both expensive and potentially inconsistent. We introduce the Complete Active-Space Wave Function Reconstruction (CAS-WR) model, which learns the geometry-dependent electronic structure from CASSCF data and reconstructs the CAS wave function without repeated orbital optimization. Combined with uncertainty-based active learning, CAS-WR is demonstrated for the Diels--Alder reaction and \\ce{TiC+}-catalyzed C--H activation. The approach enables trajectory-resolved analysis of multiconfigurational electronic structure across reactive ensembles. Preliminary applications to excited-state proton transfer and transition-metal photocatalysis suggest that CAS-WR can provide a general route toward recovering electronic structure along complex ground- and excited-state reactive dynamics.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2611.06779",
  "author_total": 5,
  "authors": [
    {
      "name": "Aniruddha Seal"
    },
    {
      "name": "Bhavnesh Jangid"
    },
    {
      "name": "Helen S. Clifford"
    },
    {
      "name": "Andrew L. Ferguson"
    },
    {
      "name": "Laura Gagliardi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/an86pg61jtbct.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2611.06779",
  "fulltext_url": null,
  "id": "an86pg61jtbct",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2611.06779",
  "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",
      "physics.chem-ph"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2611.06779",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/an86pg61jtbct.ris",
  "sources": [
    {
      "first_seen": "2026-11-05T15:20:56Z",
      "native_id": "2611.06779",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2611.06779"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "arxiv:physics.chem-ph",
      "subfield": "physical"
    }
  ],
  "title": "Machine Learning the Complete Active-Space Wavefunction Reconstruction",
  "title_text": "Machine Learning the Complete Active-Space Wavefunction Reconstruction",
  "type": "preprint",
  "updated_at": "2026-11-09T00:20:21Z",
  "url": "https://research.draconitic.com/paper/an86pg61jtbct",
  "venue": "arXiv",
  "versions": []
}