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Relativistic MHD with Adaptive Mesh Refinement

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arxiv gr-qc/0605102 v2 pith:7XFJDKZR submitted 2006-05-17 gr-qc

Matthew Anderson , Eric Hirschmann , Steven L. Liebling , David Neilsen This is my paper · ORCID
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keywords resultsadaptiveequationsfluidmeshparallelrefinementrelativistic
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abstract

This paper presents a new computer code to solve the general relativistic magnetohydrodynamics (GRMHD) equations using distributed parallel adaptive mesh refinement (AMR). The fluid equations are solved using a finite difference Convex ENO method (CENO) in 3+1 dimensions, and the AMR is Berger-Oliger. Hyperbolic divergence cleaning is used to control the $\nabla\cdot {\bf B}=0$ constraint. We present results from three flat space tests, and examine the accretion of a fluid onto a Schwarzschild black hole, reproducing the Michel solution. The AMR simulations substantially improve performance while reproducing the resolution equivalent unigrid simulation results. Finally, we discuss strong scaling results for parallel unigrid and AMR runs.

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Cited by 2 Pith papers

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    astro-ph.GA 2026-08 conditional novelty 7.0 of 10

    A new conservative SPMHD scheme in SWIFT passes standard tests and achieves the first coupling of the EAGLE galaxy formation model to magnetohydrodynamics.

  2. Nonlinear Stability of Kerr-Sen Black Holes in Merging Binaries

    gr-qc 2026-06 unverdicted novelty 4.0 of 10

    Head-on binary black hole simulations in EMDA theory show dilaton and axion fields persist through merger, indicating nonlinear stability of Kerr-Sen black holes and scalarization of initially unscalarized solutions.

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