Bayesian Exploration of Phenomenological EoS of Neutron/Hybrid Stars with Recent Observations

Particles

article

Emanuel V. Chimanski¹  Ronaldo V. Lobato²  Andre R. Goncalves⁴  Carlos A. Bertulani² 

[1] National Nuclear Data Center, Brookhaven National Laboratory;Department of Physics and Astronomy, Texas A&M University;Departamento de Física, Universidad de los Andes;Computer Engineering Directorate, Lawrence Livermore National Laboratory

关键词: Bayesian inference;    MCMC;    equation of state;    neutron star;    astrophysics;   

DOI  :  10.3390/particles6010011

学科分类：社会科学、人文和艺术（综合）

来源: mdpi

【 摘 要 】

The description of the stellar interior of compact stars remains as a big challenge for the nuclear astrophysics community. The consolidated knowledge is restricted to density regions around the saturation of hadronic matterρ 0= 2.8 ×10 14g cm− 3 , regimes where our nuclear models are successfully applied. As one moves towards higher densities and extreme conditions up to the quark/gluons deconfinement, little can be said about the microphysics of the equation of state (EoS). Here, we employ a Markov Chain Monte Carlo (MCMC) strategy to access the variability at high density regions of polytropic piecewise models for neutron star (NS) EoS or possible hybrid stars, i.e., a NS with a small quark-matter core. With a fixed description of the hadronic matter for low density, below the nuclear saturation density, we explore a variety of models for the high density regimes leading to stellar masses near to 2.5 M ⊙ , in accordance with the observations of massive pulsars. The models are constrained, including the observation of the merger of neutrons stars from VIRGO-LIGO and with the pulsar observed by NICER. In addition, we also discuss the possibility of the use of a Bayesian power regression model with heteroscedastic error. The set of EoS from the Laser Interferometer Gravitational-Wave Observatory (LIGO) was used as input and treated as the data set for the testing case.

【 授权许可】

CC BY