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Journal Article

GRHydro: A new open source general-relativistic magnetohydrodynamics code for the Einstein Toolkit

MPS-Authors

Mundim,  Bruno C.
AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Fulltext (public)

1304.5544.pdf
(Preprint), 4KB

CQG_31_1_015005.pdf
(Any fulltext), 4MB

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Citation

Moesta, P., Mundim, B. C., Faber, J. A., Haas, R., Noble, S. C., Bode, T., et al. (2014). GRHydro: A new open source general-relativistic magnetohydrodynamics code for the Einstein Toolkit. Classical and quantum gravity, 31(1): 015005. doi:10.1088/0264-9381/31/1/015005.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0014-F64F-0
Abstract
We present the new general-relativistic magnetohydrodynamics (GRMHD) capabilities of the Einstein Toolkit, an open-source community-driven numerical relativity and computational relativistic astrophysics code. The GRMHD extension of the Toolkit builds upon previous releases and implements the evolution of relativistic magnetised fluids in the ideal MHD limit in fully dynamical spacetimes using the same shock-capturing techniques previously applied to hydrodynamical evolution. In order to maintain the divergence-free character of the magnetic field, the code implements both hyperbolic divergence cleaning and constrained transport schemes. We present test results for a number of MHD tests in Minkowski and curved spacetimes. Minkowski tests include aligned and oblique planar shocks, cylindrical explosions, magnetic rotors, Alfv\'en waves and advected loops, as well as a set of tests designed to study the response of the divergence cleaning scheme to numerically generated monopoles. We study the code's performance in curved spacetimes with spherical accretion onto a black hole on a fixed background spacetime and in fully dynamical spacetimes by evolutions of a magnetised polytropic neutron star and of the collapse of a magnetised stellar core. Our results agree well with exact solutions where these are available and we demonstrate convergence. All code and input files used to generate the results are available on http://einsteintoolkit.org. This makes our work fully reproducible and provides new users with an introduction to applications of the code.