From Neutron Star Observables to the Equation of State. I. An Optimal Parametrization

TL;DR

This paper introduces an optimized parametrization method for the neutron star equation of state, enabling accurate mapping from observables like mass, radius, and moment of inertia using a minimal number of parameters.

Contribution

It presents a generic, optimized parametrization approach using piecewise polytropes and specific sampling densities, improving the accuracy of neutron star property predictions.

Findings

Reproduces radii within 0.5 km for extreme EoS

Achieves maximum mass prediction within 0.04 solar masses

Reproduces moment of inertia within 10% for most EoS

Abstract

The increasing number and precision of measurements of neutron star masses, radii, and, in the near future, moments of inertia offer the possibility of precisely determining the neutron star equation of state. One way to facilitate the mapping of observables to the equation of state is through a parametrization of the latter. We present here a generic method for optimizing the parametrization of any physically allowed EoS. We use mock equations of state that incorporate physically diverse and extreme behavior to test how well our parametrization reproduces the global properties of the stars, by minimizing the errors in the observables mass, radius, and the moment of inertia. We find that using piecewise polytropes and sampling the EoS with five fiducial densities between ~1-8 times the nuclear saturation density results in optimal errors for the smallest number of parameters. Specifically, it recreates the radii of the assumed EoS to within less than 0.5 km for the extreme mock equations of state and to within less than 0.12 km for 95% of a sample of 42 proposed, physically-motivated equations of state. Such a parametrization is also able to reproduce the maximum mass to within 0.04 M_sun and the moment of inertia of a 1.338 M_sun neutron star to within less than 10% for 95% of the proposed sample of equations of state.