Bayesian inferences on covariant density functionals from multimessenger astrophysical data: Influences of parametrizations of density-dependent couplings

Covariant density functionals have been successfully applied to the description of finite nuclei and dense nuclear matter. These functionals are often constructed by introducing density dependence into the nucleon-meson couplings, typically through functions that depend only on the vector, i.e., proper baryon density. In this work, we employ a Bayesian framework to investigate how different parametrizations, characterized by distinct functional forms and by their dependencies on vector and scalar densities, affect the properties of dense matter and compact stars. Our analysis demonstrates that although all considered parametrizations yield broadly comparable inferences, the differences in the equation of state and the symmetry energy remain significant at suprasaturation densities, reflecting the sensitivity to the chosen functional form of the density dependence. We find that allowing the nuclear saturation properties in the isoscalar channel, including the skewness coefficient $Q_{sat}$, to be freely adjusted provides adequate flexibility for the current modeling of nuclear and neutron star matter. In contrast, the isovector channel requires further refinement, with freedom extended at least up to the curvature coefficient $K_{sym}$ to capture variations in the symmetry energy and particle composition at high densities. This work advances prior studies by implementing a rational-function parametrization of the density dependence, informed and constrained by multimessenger astrophysical observations.