CompactObject: An open-source Python package for full-scope neutron star equation of state inference
Abstract
The CompactObject package is an open-source software framework developed to constrain the neutron star equation of state (EOS) through Bayesian statistical inference. It integrates astrophysical observational constraints from X-ray timing, gravitational wave events, and radio measurements, as well as nuclear experimental constraints derived from perturbative Quantum Chromodynamics (pQCD) and Chiral Effective Field Theory (EFT). The package supports a diverse range of EOS models, including meta-model like and several physics-motivated EOS models. It comprises three independent components: an EOS generator module that currently provides seven EOS choices, a Tolman-Oppenheimer-Volkoff (TOV) equation solver, that allows the determination of the Mass Radius and Tidal deformability as observables, and a comprehensive Bayesian inference workflow module, including a complete pipeline for implementing EOS Bayesian inference. Each component can be used independently in different scientific research contexts, such as nuclear physics and astrophysics. In addition, CompactObject is designed to work in synergy with existing software such as CompOSE, allowing the use of the CompOSE EOS database to extend the EOS options available.
Cite
@article{arxiv.2411.14615,
title = {CompactObject: An open-source Python package for full-scope neutron star equation of state inference},
author = {Chun Huang and Tuhin Malik and João Cartaxo and Shashwat Sourav and Wenli Yuan and Tianzhe Zhou and Xuezhi Liu and John Groger and Xieyuan Dong and Nicole Osborn and Nathan Whitsett and Zhiheng Wang and Constança Providência and Micaela Oertel and Alexander Y. Chen and Laura Tolos and Anna Watts},
journal= {arXiv preprint arXiv:2411.14615},
year = {2024}
}
Comments
submitted to JOSS, Github page: https://github.com/ChunHuangPhy/CompactObject , Documentation: https://chunhuangphy.github.io/CompactObject/