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Nuclear density functional theory provides a unified description of finite nuclei and bulk nuclear matter, and is widely used to model the neutron star (NS) equation of state. However, extrapolations to suprasaturation densities require a quantified treatment of uncertainties arising from parameter estimation and functional choices. We present an updated Bayesian inference of a Skyrme energy density functional augmented by a flexible metamodel density dependence at high density. Nuclear observables are computed using a Gaussian emulator of the publicly available Milano code, enabling efficient exploration of a high-dimensional parameter space. Relative to previous analyses, we extend the calibration set with isospin-sensitive data, including masses and charge radii along selected Ca and Sn isotopic chains, and updated constraints from giant monopole resonances. The resulting posteriors are further constrained by neutron-matter calculations and astrophysical observations, including recent NICER measurements, yielding consistent crust and core properties of catalyzed NS compatible with current constraints. Bulk nuclear-matter parameters are well approximated by a multivariate Gaussian with covariance matrix provided for direct reuse, while several finite-nucleus parameters exhibit pronounced non-Gaussianity.
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Anonymous et al. (2026) studied this question.
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