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CompactObject: Bayesian EOS inference for neutron stars

Authors: Chun Huang; Malik, Tuhin; Cartaxo, João; Shashwat Sourav; Wenli Yuan; Tianzhe Zhou; Xuezhi Liu; John Groger; Xieyuan Dong, Nicole Osborn; Nathan Whitsett; Zhiheng Wang; Providência, Constança; Micaela Oertel; Alexander Y Chen; Laura Tolos; Anna Watts

Ref.: Astrophysics Source Code Library ascl: 2511.030 (2025)

Abstract: CompactObject constrains the equation of state (EOS) of neutron stars using Bayesian inference. It includes modules for EOS generation (relativistic mean field, polytrope, quark or strange-star, speed-of-sound, or custom models), solving the Tolman─ Oppenheimer─ Volkoff equations to compute mass, radius, and tidal deformability, and performing Bayesian inference that incorporates astrophysical observations and theoretical constraints. Users can generate EOS samples, compute neutron star properties, and derive posterior distributions on EOS parameters. The CompactObject package also provides documentation and example workflows.

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