Simulating neutron stars with a flexible enthalpy-based equation of state parametrization in SpECTRE

TL;DR

This paper introduces a new enthalpy-based equation of state parametrization for neutron star simulations, enabling more accurate modeling of complex nuclear behaviors and phase transitions in a computationally efficient manner.

Contribution

The authors develop and implement a novel enthalpy-based parametrization of the neutron star equation of state in the SpECTRE code, expanding simulation capabilities for complex nuclear physics.

Findings

Enthalpy parametrization captures a range of nuclear behaviors including phase transitions.

Comparable computational performance to existing parametrizations for simple models.

Enables simulation of complex hadronic models with phase transitions.

Abstract

Numerical simulations of neutron star mergers represent an essential step toward interpreting the full complexity of multimessenger observations and constraining the properties of supranuclear matter. Currently, simulations are limited by an array of factors, including computational performance and input physics uncertainties, such as the neutron star equation of state. In this work, we expand the range of nuclear phenomenology efficiently available to simulations by introducing a new analytic parametrization of cold, beta-equilibrated matter that is based on the relativistic enthalpy. We show that the new \emph{enthalpy parametrization} can capture a range of nuclear behavior, including strong phase transitions. We implement the enthalpy parametrization in the \texttt{SpECTRE} code, simulate isolated neutron stars, and compare performance to the commonly used spectral and polytropic parametrizations. We find comparable computational performance for nuclear models that are well represented by either parametrization, such as simple hadronic EoSs. We show that the enthalpy parametrization further allows us to simulate more complicated hadronic models or models with phase transitions that are inaccessible to current parametrizations.