Prospects for the inference of inertial modes from hypermassive neutron stars with future gravitational-wave detectors

Abstract

Some recent, long-term numerical simulations of binary neutron star mergers have shown that the long-lived remnants produced in such mergers might be affected by convective instabilities. Those would trigger the excitation of inertial modes, providing a potential method to improve our understanding of the rotational and thermal properties of neutron stars through the analysis of the modes' imprint in the late post-merger gravitational-wave signal. In this paper we assess the detectability of those modes by injecting numerically generated post-merger waveforms into colored Gaussian noise of second-generation and future detectors. Signals are recovered using BayesWave, a Bayesian data-analysis algorithm that reconstructs them through a morphology-independent approach using series of sine-Gaussian wavelets. Our study reveals that current interferometers (i.e. the Handford-Livingston-Virgo network) recover the peak frequency of inertial modes only if the merger occurs at distances of up to 1 Mpc. For future detectors such as the Einstein Telescope, the range of detection increases by about a factor 10.

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Cited by in corpus (5)

• Identifying thermal effects in neutron star merger remnants with model-agnostic waveform reconstructions and third-generation detectors
• Robust and fast parameter estimation for gravitational waves from binary neutron star merger remnants
• Gravitational-wave model for neutron star merger remnants with supervised learning
• Exploring the Potential for Detecting Rotational Instabilities in Binary Neutron Star Merger Remnants with Gravitational Wave Detectors
• Self-consistent treatment of thermal effects in neutron-star post-mergers: observational implications for third-generation gravitational-wave detectors