Bayesian inference of the crust–core transition density via the neutron-star radius and neutron-skin thickness data

In this work, we perform a Bayesian inference of the crust–core transition density ρ _t of neutron stars based on the neutron-star radius and neutron-skin thickness data using a thermodynamical method. Uniform and Gaussian distributions for the ρ _t prior were adopted in the Bayesian approach. It has a larger probability of having values higher than 0.1 fm ^-3 for ρ _t as the uniform prior and neutron-star radius data were used. This was found to be controlled by the curvature K_sym of the nuclear symmetry energy. This phenomenon did not occur if K_sym was not extremely negative, namely, K_sym> − 200 MeV. The value of ρ _t obtained was 0.075 ^+0.005_-0.01 fm ^-3 at a confidence level of 68 ρ _t , slope L, and curvature of the nuclear symmetry energy. The dependence of the three L– K_sym correlations predicted in the literature on crust–core density and pressure was quantitatively investigated. The most probable value of 0.08 fm ^-3 for ρ _t was obtained from the L– K_sym relationship proposed by Holt et al. while larger values were preferred for the other two relationships.