{
  "abstract": "Precise stellar masses and physical parameters for binary and multiple star systems require, respectively, well-constrained orbital solutions and independent stellar-atmosphere modeling. Existing open-source software addresses these separately, and hierarchical triple systems additionally require simultaneous fitting of their inner and outer orbits, a treatment few existing tools provide. We present PySeshat, an open-source Python package unifying binary and hierarchical-triple orbit determination with stellar SED fitting in a single, validated pipeline. The package fits visual, spectroscopic, and combined binary orbits by least-squares, and hierarchical-triple orbits through two parallel formalisms, one of which fits both inner and outer orbits simultaneously rather than sequentially. Both share a common Bayesian posterior-sampling layer. A second module fits two-component synthetic spectra to a binary's combined, unresolved photometry to recover each component's temperature and radius. The software was validated against twelve real, published benchmark systems, cross-checked against three independent orbit-fitting packages and real space-telescope archive data. All twelve benchmark systems reach fit quality consistent with their published solutions. Comparing the simultaneous and sequential triple-fitting formalisms on the same real systems shows the simultaneous approach is not merely preferable but necessary: one system's orbital configuration cannot be represented by the sequential formalism at all. Fitting four independently published systems' photometry reveals a degeneracy in recovering individual temperatures for near-twin-temperature stellar components from unresolved light, independent of how much photometric data is available. The package provides a validated, open, and extensible pipeline for binary and multiple star system analysis, publicly released and freely installable.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.06653",
  "author_total": 2,
  "authors": [
    {
      "name": "R. I. El-Kholy"
    },
    {
      "name": "Z. M. Hayman"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/25s47y2pd7yea.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.06653",
  "fulltext_url": null,
  "id": "25s47y2pd7yea",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.06653",
  "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",
      "astro-ph.IM"
    ],
    [
      "arxiv",
      "astro-ph.SR"
    ],
    [
      "openalex",
      "3103|Stellar, planetary, and galactic studies"
    ]
  ],
  "openalex": "W7212077785",
  "pdf_url": "https://arxiv.org/pdf/2609.06653",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-06",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/25s47y2pd7yea.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:48Z",
      "native_id": "2609.06653",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.06653"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.IM",
      "subfield": "instrumentation-methods"
    },
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.SR",
      "subfield": "stellar"
    }
  ],
  "title": "PySeshat: A Validated Python Pipeline for Binary-Star Orbit Determination and Al-Wardat Stellar Atmosphere Modeling",
  "title_text": "PySeshat: A Validated Python Pipeline for Binary-Star Orbit Determination and Al-Wardat Stellar Atmosphere Modeling",
  "type": "preprint",
  "updated_at": "2026-10-30T12:19:48Z",
  "url": "https://research.draconitic.com/paper/25s47y2pd7yea",
  "venue": "arXiv",
  "versions": []
}