PySeshat: A Validated Python Pipeline for Binary-Star Orbit Determination and Al-Wardat Stellar Atmosphere Modeling
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.
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BibTeX
@misc{elkholy2026pyseshat,
title = {{PySeshat: A Validated Python Pipeline for Binary-Star Orbit Determination and Al-Wardat Stellar Atmosphere Modeling}},
author = {R. I. El-Kholy and Z. M. Hayman},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.06653},
eprint = {2609.06653},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.06653},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - PySeshat: A Validated Python Pipeline for Binary-Star Orbit Determination and Al-Wardat Stellar Atmosphere Modeling
AU - R. I. El-Kholy
AU - Z. M. Hayman
PY - 2026
DA - 2026/09/06
PB - arXiv
DO - 10.48550/arxiv.2609.06653
UR - https://arxiv.org/abs/2609.06653
AB - 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.
ER -