Direct Inference of Nuclear Equation-of-State Parameters from Gravitational-Wave Observations

TL;DR

This paper introduces neural network emulators for rapid TOV equation solutions, enabling direct inference of nuclear EOS parameters from gravitational wave data with high speed and accuracy, demonstrated on GW170817.

Contribution

The authors develop and implement neural network emulators for TOV equations, significantly accelerating EOS parameter inference from GW observations compared to traditional methods.

Findings

Emulators achieve nearly two orders of magnitude speed-up in TOV solutions.

Posteriors on EOS parameters are consistent with full TOV solver analyses.

Constraints on symmetry energy slope and curvature are obtained from GW data.

Abstract

The observation of neutron star mergers with gravitational waves (GWs) has provided a new method to constrain the dense-matter equation of state (EOS) and to better understand its nuclear physics. However, inferring nuclear microphysics from GW observations necessitates the sampling of EOS model parameters that serve as input for each EOS used during the GW data analysis. The sampling of the EOS parameters requires solving the Tolman-Oppenheimer-Volkoff (TOV) equations a large number of times -- a process that slows down each likelihood evaluation in the analysis on the order of a few seconds. Here, we employ emulators for the TOV equations built using multilayer perceptron neural networks to enable direct inference of nuclear EOS parameters from GW strain data. Our emulators allow us to rapidly solve the TOV equations, taking in EOS parameters and outputting the associated tidal deformability of a neutron star in only a few tens of milliseconds. We implement these emulators in \texttt{PyCBC} to directly infer the EOS parameters using the event GW170817, providing posteriors on these parameters informed solely by GWs. We benchmark these runs against analyses performed using the full TOV solver and find that the emulators achieve speed ups of nearly \emph{two orders of magnitude}, with negligible differences in the recovered posteriors. Additionally, we constrain the slope and curvature of the symmetry energy at the 90\% upper credible interval to be $L_{\rm sym}\lesssim106$ MeV and $K_{\rm sym}\lesssim26$ MeV.