Neutron-star cores contain matter at the highest densities in our Universe. This highly
compressed matter may undergo a phase transition where nuclear matter melts into …

We investigate the probable existence of dark matter in the interior of neutron stars. Despite
the current state of knowledge, the observational properties of neutron stars have not …

In this work, we propose a metamodeling technique to nuclear matter on the basis of a
relativistic density functional with density-dependent couplings. Identical density …

We exploit the great potential offered by Bayesian neural networks (BNNs) to directly
decipher the internal composition of neutron stars (NSs) based on their macroscopic …

Measurements of neutron star mass and radius or tidal deformability deliver unique insight
into the equation of state (EOS) of cold dense matter. EOS inference is very often done using …

The recently developed resummation technique known as renormalization group optimized
perturbation theory (RGOPT) is employed in the evaluation of the equation of state (EOS) …

This study is devoted to the inference problem of extracting the nuclear matter properties
directly from a set of mass-radius observations. We employ Bayesian neural networks …

In this work, we perform a comparative analysis between the density-dependent quark
model and the vector MIT bag model using Bayesian analysis. We use the equations of state …

We generate three families of extended covariant density functionals of nuclear matter that
have varying slope of symmetry energy and skewness at nuclear saturation density, but …

The difficulty in describing the equation of state (EOS) for nuclear matter at densities above
the saturation density (ρ 0) has led to the emergence of a multitude of models based on …