We perform a Bayesian analysis of the neutron star (NS) equation of state (EoS) based on a wide set of Skyrme functionals, derived from previous nuclear physics inferences. The novelty of this approach lies in starting from the full multidimensional posterior distribution of nuclear matter parameters, consistent with a comprehensive set of static and dynamic nuclear structure observables. We construct unified EoSs for $npe\mu$ matter, where the inner crust of the NS is treated using an extended Thomas-Fermi method, providing for the first time a fully consistent Bayesian treatment of the correlation of bulk with surface as well as with spin-orbit and effective mass parameters. We then employ a standard Bayesian framework to identify those EoSs that satisfy astrophysical constraints from NS mass measurements, the tidal deformability from GW170817, and NICER mass-radius observations. We also examine NS observables, such as the crustal moment of inertia, which is crucial in understanding pulsar glitches. Compared to previous works, we observe an increase in both the NS surface thickness and the crustal moment of inertia. less

For densities beyond nuclear saturation, there is still a large uncertainty in the equations of state (EoS) of dense matter that translate into uncertainties in the internal structure of neutron stars. The MUSES Calculation Engine provides a free and open-source composable workflow management system, which allows users to calculate the EoS of dense and hot matter that can be used, e.g. to describe neutron stars. For this work, we make use of two MUSES EoS modules, Crust Density Functional Theory and Chiral Mean Field model, with beta-equilibrium with leptons enforced in the Lepton module, then connected by the Synthesis module using different functions: hyperbolic tangent, Gaussian, bump, and smoothstep. We then calculate stellar structure using the QLIMR module and discuss how the different interpolating functions affect our results. less