Numerical inside view of hypermassive remnant models for GW170817

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Kastaun, W.; Ohme, F.: Numerical inside view of hypermassive remnant models for GW170817. In: Physical Review D 104 (2021), Nr. 2, 023001. DOI: https://doi.org/10.1103/physrevd.104.023001

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Abstract: 
The first multimessenger observation attributed to a merging neutron star binary provided an enormous amount of observational data. Unlocking the full potential of this data requires a better understanding of the merger process and the early postmerger phase, which are crucial for the later evolution that eventually leads to observable counterparts. In this work, we perform standard hydrodynamical numerical simulations of a system compatible with GW170817. We focus on a single equation of state and two mass ratios, while neglecting magnetic fields and neutrino radiation. We then apply newly developed postprocessing and visualization techniques to the results obtained for this basic setting. The focus lies on understanding the three-dimensional structure of the remnant, most notably the fluid flow pattern, and its evolution until collapse. We investigate the evolution of mass and angular momentum distribution up to collapse, as well as the differential rotation along and perpendicular to the equatorial plane. For the cases that we studied, the remnant cannot be adequately modeled as a differentially rotating axisymetric neutron star. Further, the dominant aspect leading to collapse is the gravitational wave radiation and not internal redistribution of angular momentum. We relate features of the gravitational wave signal to the evolution of the merger remnant and make the waveforms publicly available. Finally, we find that the three-dimensional vorticity field inside the disk is dominated by medium-scale disturbances and not the orbital velocity, with potential consequences for magnetic field amplification effects.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:An-Institute

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1 image of flag of United States United States 8 57.14%
2 image of flag of Germany Germany 5 35.71%
3 image of flag of Indonesia Indonesia 1 7.14%

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