General relativistic hydrodynamics on a moving-mesh I: static space–times
ABSTRACT We present the moving-mesh general relativistic hydrodynamics solver for static space–times as implemented in the code, MANGA. Our implementation builds on the architectures of MANGA and the numerical relativity python package NRPy+. We review the general algorithm to solve these equations...
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| Published in | Monthly notices of the Royal Astronomical Society Vol. 496; no. 1; pp. 206 - 214 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford University Press
21.07.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0035-8711 1365-8711 1365-2966 1365-2966 |
| DOI | 10.1093/mnras/staa1532 |
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| Summary: | ABSTRACT
We present the moving-mesh general relativistic hydrodynamics solver for static space–times as implemented in the code, MANGA. Our implementation builds on the architectures of MANGA and the numerical relativity python package NRPy+. We review the general algorithm to solve these equations and, in particular, detail the time-stepping; Riemann solution across moving faces; conversion between primitive and conservative variables; validation and correction of hydrodynamic variables; and mapping of the metric to a Voronoi moving-mesh grid. We present test results for the numerical integration of an unmagnetized Tolman–Oppenheimer–Volkoff star for 24 dynamical times. We demonstrate that at a resolution of 106 mesh generating points, the star is stable and its central density drifts downwards by 2 per cent over this time-scale. At a lower resolution, the central density drift increases in a manner consistent with the adopted second-order spatial reconstruction scheme. These results agree well with the exact solutions, and we find the error behaviour to be similar to Eulerian codes with second-order spatial reconstruction. We also demonstrate that the new code recovers the fundamental mode frequency for the same TOV star but with its initial pressure depleted by 10 per cent. |
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| ISSN: | 0035-8711 1365-8711 1365-2966 1365-2966 |
| DOI: | 10.1093/mnras/staa1532 |