Inverse-mapped density-dependent relativistic mean-field inference of the neutron-star equation of state with multi-messenger constraints

Abstract: We perform a Bayesian inference of the equation of state (EOS) of cold dense matter within a density-dependent relativistic mean-field (DD-RMF) model. An explicit inverse-mapping procedure reconstructs the density-dependent couplings from a physically interpretable ten-dimensional parameter set while enforcing thermodynamic consistency together with stability and causality conditions. The EOS is constrained by complementary multi-messenger data including chiral effective field theory calculations at low density, heavy-ion collision flow information at intermediate densities, NICER mass-radius posteriors, and the existence of approximately two-solar-mass pulsars. The combined constraints strongly restrict both isoscalar and isovector sectors. In particular, the chiral effective field theory band favors a relatively soft symmetry-energy slope around 38 MeV, corresponding to a compact canonical neutron-star radius of about 11.6 km. To reconcile the intermediate-density softness suggested by heavy-ion data with the high-density stiffness required by massive pulsars, the posterior prefers a moderately large Dirac effective mass at saturation together with correlated high-density limits of the scalar and vector couplings. The resulting sound-speed profile remains causal and shows significant stiffening above the conformal limit at several times nuclear saturation density, indicating strongly interacting matter in neutron-star cores. Evidence diagnostics indicate strong compatibility among the adopted constraints within the present DD-RMF framework.