Detection and parameter estimation of binary neutron star merger remnants

Paul J. Easter; Sudarshan Ghonge; Paul D. Lasky; Andrew R. Casey; James A. Clark; Francisco Hernandez Vivanco; Katerina Chatziioannou

doi:10.1103/PhysRevD.102.043011

paper

Detection and parameter estimation of binary neutron star merger remnants

arXiv:2006.04396 · doi:10.1103/PhysRevD.102.043011

Abstract

Detection and parameter estimation of binary neutron star merger remnants can shed light on the physics of hot matter at supranuclear densities. Here we develop a fast, simple model that can generate gravitational waveforms, and show it can be used for both detection and parameter estimation of post-merger remnants. The model consists of three exponentially-damped sinusoids with a linear frequency-drift term. The median fitting factors between the model waveforms and numerical-relativity simulations exceed 0.90. We detect remnants at a post-merger signal-to-noise ratio of $\geq 7$ using a Bayes-factor detection statistic with a threshold of 3000. We can constrain the primary post-merger frequency to $\pm_{1.2}^{1.4} %$ at post-merger signal-to-noise ratios of 15 with an increase in precision to $\pm_{0.2}^{0.3} %$ for post-merger signal-to-noise ratios of 50. The tidal coupling constant can be constrained to $\pm_{12}^{9} %$ at post-merger signal-to-noise ratios of 15, and $\pm 5%$ at post-merger signal-to-noise ratios of 50 using a hierarchical inference model.

Detection and parameter estimation of binary neutron star merger remnants

Abstract

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