kiloHertz gravitational waves from binary neutron star remnants: time-domain model and constraints on extreme matter

TL;DR

This paper introduces a new analytical waveform model for kilohertz gravitational waves from neutron star merger remnants, enabling detection and detailed analysis of signals to constrain the properties of dense matter.

Contribution

The authors develop a time-domain waveform model for postmerger signals that enhances detection capabilities and allows inference of neutron star properties and the equation of state.

Findings

Detection of postmerger signals with SNR as low as 8.

Ability to distinguish prompt collapse from remnant stars.

Precise measurement of neutron star radius and equation of state parameters.

Abstract

The remnant star of a neutron star merger is an anticipated loud source of kiloHertz gravitational waves that conveys unique information on the equation of state of hot matter at extreme densities. Observations of such signals are hampered by the photon shot noise of ground-based interferometers and pose a challenge for gravitational-wave astronomy. We develop an analytical time-domain waveform model for postmerger signals informed by numerical relativity simulations. The model completes effective-one-body waveforms for quasi-circular nonspinning binaries in the kiloHertz regime. We show that a template-based analysis can detect postmerger signals with a minimal signal-to-noise ratios (SNR) of 8, corresponding to GW170817-like events for third-generation interferometers. Using Bayesian model selection and the complete inspiral-merger-postmerger waveform model it is possible to infer whether the merger outcome is a prompt collapse to a black hole or a remnant star. In the latter case, the radius of the maximum mass (most compact) nonrotating neutron star can be determined to kilometer precision. We demonstrate the feasibility of inferring the stiffness of the equation of state at extreme densities using the quasiuniversal relations deduced from numerical-relativity simulations.