An Asymptotically Causal Metamodel for Neutron Star Equations of State

TL;DR

This paper introduces an improved nuclear metamodel for neutron star equations of state, ensuring causal high-density behavior and enabling detailed Bayesian analysis of neutron star properties.

Contribution

It revises a non-relativistic metamodel to better enforce causality and accurately reproduce microscopic equations of state, expanding neutron star modeling capabilities.

Findings

Reduced models discarded due to superluminal speeds.

Enhanced accuracy in pressure and composition predictions.

Facilitated Bayesian inference of neutron star features.

Abstract

Nuclear metamodels - phenomenological parametrizations of the energy of nuclear matter - are convenient tools to explore the space of realistic neutron star configurations constrained by astrophysical and nuclear data. While much recent work has focused on composition-agnostic barotropic models, the metamodel approach is designed to describe the composition dependence of the relevant thermodynamic potential. We revise a previously proposed non-relativistic metamodel by introducing a more controlled high-density behaviour, improving both its causal properties and its accuracy in reproducing the pressure and the beta-equilibrium composition of microscopically motivated equations of state. Since causality is automatically enforced at high density, the fraction of discarded models due to superluminal sound speeds is substantially reduced, facilitating metamodel-based explorations of equilibrium neutron star configurations. We further assess our framework by performing a Bayesian inference of neutron star properties beyond standard observables such as masses and radii, exploiting the metamodel's ability to probe composition-dependent quantities including the dUrca threshold and the Ledoux criterion for g-mode stability.