The impacts of various symmetry energy parameters on the properties neutron stars (NSs) have been recently investigated, and outcomes are at variance, as summarized in Table III Phys. Rev. D 106, 063005 (2022). We systematically analyzed correlations slope curvature saturation density (${\ensuremath{\rho}}_{0}=0.16\phantom{\rule{0.16em}{0ex}}{\text{fm}}^{\ensuremath{-}3}$) with tidal deformability stellar radius nonspinning mass range...

The nuclear matter parameters (NMPs), those underlie in the construction of equation state (EoS) neutron star matter, are not directly accessible. Bayesian approach is applied to reconstruct posterior distributions NMPs from EoS matter. constraints on lower-order as imposed by finite nuclei observables incorporated through appropriately chosen prior distributions. calculations performed with two sets pseudo data whose true models known. median values second or higher order show sizeable...

We apply Bayesian approach to construct a large number of minimally constrained equations state (EOSs) and study their correlations with few selected properties neutron star (NS). Our set minimal constraints includes basic saturated nuclear matter low-density pure EOS which is obtained from precise next-to-next-to-next-to-leading-order (N$^{3}$LO) calculation in chiral effective field theory. The tidal deformability radius NS mass $1-2 M_\odot$ are found be strongly correlated the pressure...

In computer vision, the removal of rain streaks from individual photographs has drawn a lot interest. A saturated picture is broken down to an underlying image without any and map streak represent de-raining challenge as decomposition assignment. This study introduced DLD: Deep Learning-Based Single Image De-Raining Using Discrete Hartley Transformation, which different majority techniques now in use. The data cleansing phase this uses contrast-limited adaptive histogram equalization smooth...

We have attempted to mitigate the challenge of connecting neutron star (NS) properties with nuclear matter parameters that describe equations state (EOSs). The efforts correlate various individual been inconclusive. A principal component analysis is employed as a tool uncover connection between multiple and tidal deformability well radius stars within mass range $1.2--1.8{M}_{\ensuremath{\bigodot}}$. essential EOSs for at low densities derived using both uncorrelated uniform distributions...

Motivated by the recent observation of high-mass pulsars ($M \simeq 2 M_{\odot}$), we employ $\sigma$-cut potential on equation state (EOS) high-density matter and properties neutron stars within relativistic mean-field (RMF) model using TM1$^{*}$ parameter set. The is known to reduce contributions $\sigma$ field, resulting in a stiffer EOS at high densities hence leading larger star masses without affecting nuclear normal saturation density. We also analyzed effect same pure with hyperonic...

Abstract We derive an equation of state (EOS) for magnetized charge-neutral nuclear matter relevant a neutron star (NS). The calculations are performed within effective chiral model based on the generalization σ with nonlinear self-interactions mesons along ρ − cross-coupling term. This is extended by introducing contributions strong magnetic field charged particles. arising from effects Dirac sea baryons also included. resulting EOS dense used to investigate NS properties like its mass,...

A Bayesian method is used in this extensive work to generate a large set of minimally constrained equations state (EOSs) for matters neutron stars (NS). These EOSs are analyzed their correlations with key NS properties, such as the tidal deformability, radius, and maximum mass, within mass range $1.2-2M_\odot$. The observed connections between pressure $\beta$-equilibrated matter properties at different densities offer significant insights into behavior nearly model-independent manner. study...

We implemented symbolic regression techniques to identify suitable analytical functions that map various properties of neutron stars (NSs), obtained by solving the Tolman-Oppenheimer-Volkoff (TOV) equations, a few key parameters equation state (EoS). These models (SRMs) are then employed perform Bayesian inference with comprehensive dataset from nuclear physics experiments and astrophysical observations. The posterior distributions EoS using SRMs closely match those directly solutions TOV...

<title>Abstract</title> We implemented symbolic regression techniques to identify suitable analytical functions that map various properties of neutron stars (NSs), obtained by solving the Tolman-Oppenheimer-Volkoff (TOV) equations, a few key parameters equation state (EoS). These models (SRMs) are then employed perform Bayesian inference with comprehensive dataset from nuclear physics experiments and astrophysical observations. The posterior distributions EoS using SRMs closely match those...