1. High-resolution numerical relativity simulations of spinning binary neutron star mergers
- Author
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Sebastiano Bernuzzi, Bernd Bruegmann, Tim Dietrich, and Wolfgang Tichy
- Subjects
High Energy Astrophysical Phenomena (astro-ph.HE) ,Field (physics) ,010308 nuclear & particles physics ,Gravitational wave ,Computer science ,media_common.quotation_subject ,Phase (waves) ,Binary number ,FOS: Physical sciences ,General Relativity and Quantum Cosmology (gr-qc) ,01 natural sciences ,General Relativity and Quantum Cosmology ,Computational physics ,Neutron star ,Numerical relativity ,0103 physical sciences ,Waveform ,Eccentricity (behavior) ,Astrophysics - High Energy Astrophysical Phenomena ,010306 general physics ,media_common - Abstract
The recent detection of gravitational waves and electromagnetic counterparts emitted during and after the collision of two neutron stars marks a breakthrough in the field of multi-messenger astronomy. Numerical relativity simulations are the only tool to describe the binary's merger dynamics in the regime when speeds are largest and gravity is strongest. In this work we report state-of-the-art binary neutron star simulations for irrotational (non-spinning) and spinning configurations. The main use of these simulations is to model the gravitational-wave signal. Key numerical requirements are the understanding of the convergence properties of the numerical data and a detailed error budget. The simulations have been performed on different HPC clusters, they use multiple grid resolutions, and are based on eccentricity reduced quasi-circular initial data. We obtain convergent waveforms with phase errors of 0.5-1.5 rad accumulated over approximately 12 orbits to merger. The waveforms have been used for the construction of a phenomenological waveform model which has been applied for the analysis of the recent binary neutron star detection. Additionally, we show that the data can also be used to test other state-of-the-art semi-analytical waveform models., Comment: published as proceeding for the 26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing. PDP 2018 IEEE Catalog Number: CFP18169
- Published
- 2018
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