Bayesian analysis finds that the likely ranges of light dark-matter fermion mass and exponential density-profile parameter in hyperon-containing neutron stars are nearly independent of the hadronic model for symmetry-energy slopes between 40 and 58 MeV, with HESS J1731-347 and GW170817 data playing,
Properties of Neutron Stars with hyperon cores in parameterized hydrostatic conditions
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abstract
Models of neutron stars (NSs) with hyperon cores are constructed with an effective chiral model in mean-field approximation. The hyperon couplings are fixed by reproducing their experimentally determined binding energies. The impact of these couplings on population of different particles and the equation of state (EoS) are studied in this work. The global properties of NSs like gravitational mass, radius, baryonic mass and central density are calculated using parameterized Tolman-Oppenheimer-Volkoff equations (PTOV) with special emphasis on two effects of pressure - one contributing to total mass density and the other to self gravity of the star. We find that with PTOV solutions in static conditions, a softer EoS (including hyperons) can also lead to massive stellar configurations of NSs, which are in well agreement with the observed maximum mass bound of $\approx 2 M_{\odot}$ (PSR J0348-0432). Estimates of $R_{1.4}$ and $R_{1.6}$, obtained with the PTOV equations are consistent with the recent findings of the same from the data analysis of gravitational waves (GW170817) observation. Keywords: Neutron Star; Hyperons; Equation of State; parameterized Tolman-Oppenheimer-Volkoff equations
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Bayesian analysis of density profile of light dark matter elucidating the properties of dark matter admixed neutron stars in the presence of hyperons
Bayesian analysis finds that the likely ranges of light dark-matter fermion mass and exponential density-profile parameter in hyperon-containing neutron stars are nearly independent of the hadronic model for symmetry-energy slopes between 40 and 58 MeV, with HESS J1731-347 and GW170817 data playing,