Direct nonparametric multimessenger constraints on the equation of state of cold dense nuclear matter

TL;DR

This paper introduces a novel Bayesian method combining astrophysical data and quantum chromodynamics calculations to nonparametrically constrain the neutron star equation of state, revealing preferences among different nuclear matter models.

Contribution

It develops a new inference approach that simultaneously samples binary neutron star parameters and the nonparametric EOS, integrating diverse observational data and high-density QCD calculations.

Findings

Standard pressure constraint at twice nuclear saturation density: $4.3^{+0.6}_{-0.6} imes 10^{34}$ dyne/cm²

Hyperonic priors predict higher tidal deformabilities for 1.4 solar mass neutron stars

Hadronic priors are favored by current astrophysical observations

Abstract

We utilize the now substantial amount of astrophysical observations of neutron stars (NSs), along with perturbative quantum chromodynamics (pQCD) calculations at high density, to directly constrain the NS equation of state (EOS). To this end, we construct nonparametric EOS priors by using Gaussian processes trained on 75 EOSs, which include models with either hadrons, hyperons, or quarks at high densities. We create a prior using the full EOS sample (model agnostic), and one prior for each EOS family to test model discrimination. We introduce a novel inference approach, which allows the simultaneous sampling of intrinsic and extrinsic parameters of binary NS mergers, as well as a nonparametric equation of state. We showcase this method in a Bayesian updating scheme by first performing a complete analysis of the binary NS merger event GW170817 with minimal assumptions, and sequentially adding information from x-ray and radio NS observations, along with pQCD calculations. Besides providing standard constraints, such as the pressure at twice nuclear saturation density $p(2\rho_\text{sat})=4.3^{+0.6}_{-0.6}\,\times 10^{34}\text{dyne/cm}^{2}$, at $95\%$ confidence level, for the model agnostic prior, our methodology shows how the choice of EOS families used in conditioning changes the inferred astrophysical properties of the EOS, namely tidal deformability and maximum supported NS mass. We find hyperonic priors predicting higher tidal deformabilities for a $1.4M_\odot$ NS, and hadronic priors being preferred by the considered astrophysical data.