A Realistic Projection for Constraining Neutron Star Equation of State with the LIGO-Virgo-KAGRA Detector Network in the A+ Era

TL;DR

This paper evaluates how the upgraded LIGO-Virgo-KAGRA network in the A+ era can better constrain neutron star equations of state by analyzing simulated gravitational wave signals and identifying biases in parameter estimation.

Contribution

It introduces reduced order quadrature techniques for efficient parameter estimation of BNS mergers and assesses EOS recovery accuracy with simulated data.

Findings

Tidal deformability estimates vary with mass

Biases in EOS constraints are identified and quantified

Postprocessing improves EOS recovery accuracy

Abstract

The LIGO-Virgo-KAGRA network in the upcoming A+ era with upgrades of both Advanced LIGO and Advanced Virgo will enable more frequent and precise observations of binary neutron star (BNS) mergers, improving constraints on the neutron star equation of state (EOS). In this study, we applied reduced order quadrature techniques for full parameter estimation of 3,000 simulated gravitational wave signals from BNS mergers at A+ sensitivity following three EOS models: HQC18, SLY230A, and MPA1. We found that tidal deformability tends to be overestimated at higher mass and underestimated at lower mass. We postprocessed the parameter estimation results to present our EOS recovery accuracies, identify biases within EOS constraints and their causes, and quantify the needed corrections.