Demonstrating the feasibility of probing the neutron star equation of state with second-generation gravitational wave detectors

TL;DR

This study demonstrates that second-generation gravitational wave detectors can, with a few tens of detections, effectively constrain the neutron star equation of state through Bayesian analysis of binary inspiral signals.

Contribution

First fully Bayesian analysis showing feasibility of constraining neutron star equations of state with realistic gravitational wave data.

Findings

Few tens of detections suffice for strong constraints

Bayesian methods outperform Fisher matrix estimates

Constraints are effective even for soft equations of state

Abstract

Fisher matrix and related studies have suggested that with second-generation gravitational wave detectors, it may be possible to infer the equation of state of neutron stars using tidal effects in binary inspiral. Here we present the first fully Bayesian investigation of this problem. We simulate a realistic data analysis setting by performing a series of numerical experiments of binary neutron star signals hidden in detector noise, assuming the projected final design sensitivity of the Advanced LIGO- Virgo network. With an astrophysical distribution of events (in particular, uniform in co-moving volume), we find that only a few tens of detections will be required to arrive at strong constraints, even for some of the softest equations of state in the literature. Thus, direct gravitational wave detection will provide a unique probe of neutron star structure.