Bayesian Quantification of Observability and Equation of State of Twin Stars
Xavier Grundler, Bao-An Li

TL;DR
This paper uses Bayesian methods with neutron star radius data to quantify the likelihood and properties of twin stars, revealing their robustness and potential to constrain the neutron star equation of state.
Contribution
It introduces a Bayesian framework with a flexible meta-model to analyze the observability and EOS of twin stars using current observational data.
Findings
12-18% of EOSs produce twin stars
Twin star scenarios are observable with current measurement accuracy
EOS parameters depend on twin star category and presence
Abstract
The possibility of discovering twin stars, two neutron stars (NSs) with the same mass but different radii, is usually studied in forward modelings by using a restricted number of NS matter equation of state (EOS) encapsulating a first-order phase transition from hadronic to quark matter (QM). Informing our likelihood function with the NS radius data from GW170817 and using a meta-model with 9-parameters capable of mimicking most NS EOSs available in the literature, we conduct a Bayesian quantification of the observability and underlying EOSs of twin stars. Of the accepted EOSs, between 12-18\% yield twin stars, depending on the restrictions we place on the second branch. The possibility of twin stars remains robust even under recent observational constraints. We show that many of these twin star scenarios are observable with currently available levels of accuracy in measuring NS radii.…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Geophysics and Gravity Measurements · Spacecraft Dynamics and Control
