Related papers: Bayesian inferences on covariant density functiona…
Recent advancements in astrophysical observations of compact stars, particularly the new and updated NICER constraints, have provided mass-radius ($M$-$R$) data for pulsars spanning masses from 1 to $2\,M_{\odot }$. These data offer a…
Covariant density functionals have been successfully applied to the description of finite nuclei and dense nuclear matter. These functionals are often constructed by introducing density dependence into the nucleon-meson couplings, typically…
A modified version of the density dependent covariant density functional model proposed in [T. Malik, M. Ferreira, B. K. Agrawal and C. Provid\^encia, ApJ 930, 17 (2022)] is employed in a Bayesian analysis to determine the equation of state…
We present a theoretical framework to quantify statistical uncertainties in covariant density functional theory (CDFT) for both nuclear matter and finite nuclei, based on a relativistic point-coupling energy density functional (EDF). By…
We present a Bayesian framework for joint and coherent analyses of multimessenger binary neutron star signals. The method, implemented in our bajes infrastructure, incorporates a joint likelihood for multiple datasets, support for various…
The composition and properties of infinite nuclear matter under extreme conditions of temperature and pressure remain incompletely understood. In this work, we constrain the equation of state (EoS) of nuclear matter - constructed within the…
Based on the Skyrme-Hartree-Fock model (SHF) as well as its extension (the Korea-IBS-Daegu-SKKU (KIDS) model) and the relativistic mean-field (RMF) model, we have studied the constraints on the parameters of the nuclear matter equation of…
We construct an efficient parameterization of the pure neutron-matter equation of state (EoS) that incorporates the uncertainties from both chiral effective field theory ($\chi$EFT) and phenomenological potential calculations. This…
Accurate modeling of the neutron star crust is essential for interpreting multimessenger observations and constraining the nuclear equation of state (EoS). However, standard phenomenological EoS models often rely on heuristic extrapolations…
This study analyzes and contrasts different phenomenological methods used to model the nuclear equation of state (EOS) for neutron star matter based on covariant energy density functionals (CEDF). Using two complementary methodologies, we…
We investigate how vector-isoscalar and vector-isovector interactions can be determined within the density regime of neutron stars (NSs), while fulfilling nuclear and astrophysics constrains. We make use of the Chiral Mean Field (CMF)…
Using an explicitly isospin-dependent parametric Equation of State (EOS) for the core of neutron stars (NSs) within the Bayesian statistical approach, we infer the EOS parameters of super-dense neutron-rich nuclear matter from three sets of…
We investigate constraints on the high-density equation of state (EOS) of neutron star matter by analyzing the probability distributions of the endpoints of mass-radius M(R) sequences within a Bayesian weighting framework. Starting from two…
Utilizing various astrophysical constraints on neutron star structures, we carry out a Bayesian analysis on the density-dependent behaviors of coupling constants in RMF models as well as the nuclear matter properties at supranuclear…
The description of stellar interior remains as a big challenge for the nuclear astrophysics community. The consolidated knowledge is restricted to density regions around the saturation of hadronic matter $\rho _{0} = 2.8\times 10^{14} {\rm\…
Through continuous progress in nuclear theory and experiment and an increasing number of neutron-star observations, a multitude of information about the equation of state (EOS) for matter at extreme densities is available. To constrain the…
We systematically investigate how the choice between Gaussian and uniform likelihood functions in Bayesian inference affects the inferred bulk properties of compact stars and nuclear matter within covariant density functional-based…
We perform a Bayesian inference of the equation of state (EOS) of cold dense matter within a density-dependent relativistic mean-field (DD-RMF) model. An explicit inverse-mapping procedure reconstructs the density-dependent couplings from a…
Over the past decade, an abundance of information from neutron-star observations, nuclear experiments and theory has transformed our efforts to elucidate the properties of dense matter. However, at high densities relevant to the cores of…
In this work, we investigate neutron stars (NSs) in the strong field regime within the framework of symmetric teleparallel $f(Q)$ gravity, considering three representative models: linear, logarithmic, and exponential. While Bayesian studies…