Bayesian analysis of a relativistic hadronic model constrained by recent astrophysical observations
B. A. de Moura S., C. H. Lenzi, O. Louren\c{c}o, M. Dutra

TL;DR
This paper employs Bayesian analysis to constrain the nuclear matter equation of state using recent astrophysical data, resulting in refined parameters consistent with neutron star observations and nuclear physics constraints.
Contribution
It introduces a Bayesian framework to constrain a relativistic hadronic model's parameters based on recent astrophysical measurements, improving understanding of neutron star properties.
Findings
Optimal ranges for bulk parameters like effective mass, incompressibility, and symmetry energy slope.
Predicted neutron star radius ranges consistent with observational data.
Agreement of model parametrizations with nuclear matter constraints and gravitational wave observations.
Abstract
We use Bayesian analysis in order to constrain the equation of state for nuclear matter from astrophysical data related to the recent measurements from the NICER mission, LIGO/Virgo collaboration, and probability distributions of mass and radius from other 12 sources, including thermonuclear busters, and quiescent low-mass X-ray binaries. For this purpose, we base our study on a relativistic hadronic mean field model including an interaction. Our results indicate optimal ranges for some bulk parameters at the saturation density, namely, effective mass, incompressibility, and symmetry energy slope (). For instance, we find MeV (Case 1) and MeV (Case 2) in a confidence interval for the 2 cases analyzed (different input ranges for related to the PREX-II data). The respective parametrizations are in…
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