Towards mitigation of apparent tension between nuclear physics and astrophysical observations by improved modeling of neutron star matter

TL;DR

This paper uses a Bayesian approach with a hybrid neutron star matter model to better constrain the equation of state, resolving tensions between nuclear physics models and astrophysical observations.

Contribution

It introduces a hybrid EoS formulation combining empirical nuclear parameters and piecewise polytropes, improving constraints on neutron star properties and addressing existing tensions.

Findings

Predicted neutron star radius: 12.57 km with uncertainties

Predicted tidal deformability: 550 with uncertainties

Hybrid EoS resolves tension between nuclear models and observations

Abstract

Observations of neutron stars (NSs) by the LIGO-Virgo and NICER collaborations have provided reasonably precise measurements of their various macroscopic properties. In this paper, we employ a Bayesian framework to combine them and place improved joint constraints on the properties of NS equation of state (EoS). We use a hybrid EoS formulation that employs a parabolic expansion-based nuclear empirical parameterization around the nuclear saturation density augmented by a generic 3-segment piecewise polytrope model at higher densities. Within the $90 \%$ credible level this parameterization predicts $R_{1.4} = 12.57_{-0.92}^{+0.73}$ km and $\Lambda_{1.4} = 550_{-225}^{+223}$ for the radius and dimensionless tidal deformability, respectively, of a $1.4 M_{\odot}$ NS. Finally, we show how the construction of the full NS EoS based solely on the nuclear empirical parameters at saturation density leads to certain tension with the astrophysical data, and how the hybrid approach provides a resolution to it.