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Bayesian inference of neutron-star observables based on effective nuclear interactions
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abstract
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 state (EOS) from adopted astrophysical observables using a Bayesian approach. While the masses and radii of neutron stars generally favors a stiff isoscalar EOS and a moderately soft nuclear symmetry energy, model dependence on the constraints is observed and mostly originates from the incorporation of higher-order EOS parameters and difference between relativistic and non-relativistic models. At twice saturation density, the value of the symmetry energy is constrained to be $48^{+15}_{-11}$ MeV in the standard SHF model, $48^{+8}_{-15}$ MeV in the KIDS model, and $48^{+5}_{-6}$ MeV in the RMF model, around their maximum {\it a posteriori} values within $68\%$ confidence intervals. Our study helps to obtain a robust constraint on nuclear matter EOS, and meanwhile, to understand the model dependence of the results.
Forward citations
Cited by 2 Pith papers
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Bayesian inferences on covariant density functionals from multimessenger astrophysical data: The impacts of likelihood functions of low density matter constraints
Using a uniform instead of Gaussian likelihood for low-density nuclear constraints leaves neutron star radii and masses nearly unchanged, but shifts the inferred nuclear incompressibility.
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Bayesian constraints on covariant density functional equations of state of compact stars with new NICER mass-radius measurements
Bayesian fits that include the 2024 NICER results for PSR J0437 and J1231 narrow the allowed radius range for canonical-mass neutron stars to roughly 12.5 to 12.8 km in covariant density functional models.
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