The Eleventh Marcel Grossmann Meeting 2008
DOI: 10.1142/9789812834300_0200
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Adaptive Mesh Refinement and Relativistic MHD

Abstract: We solve the general relativistic magnetohydrodynamics equations using distributed parallel adaptive mesh refinement. We discuss strong scaling tests of the code, and present evolutions of Michel accretion and a TOV star.

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Cited by 5 publications
(4 citation statements)
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“…The complexity of the field equations and the physical set-up of the binary black hole problem requires solution in a parallel computing environment, and adaptive mesh refinement (AMR) to adequately resolve all the relevant length scales (the only code at present not employing AMR is the LazEv code [260], however there a non-linear "fisheye" coordinate transformation is used to resolve the length scales in the vicinity of the binary). Some of the parallel/AMR software presently used is the Cactus Computational Toolkit [261] with the Carpet thorn for AMR [262], paramesh [263], PAMR/AMRD [264], HAD [265] and BAM [266]. Descriptions of some of the more computational aspects of the merger codes can be found in [228,229,231,255,260,266,268,269].…”
Section: F Numerical Algorithmsmentioning
confidence: 99%
“…The complexity of the field equations and the physical set-up of the binary black hole problem requires solution in a parallel computing environment, and adaptive mesh refinement (AMR) to adequately resolve all the relevant length scales (the only code at present not employing AMR is the LazEv code [260], however there a non-linear "fisheye" coordinate transformation is used to resolve the length scales in the vicinity of the binary). Some of the parallel/AMR software presently used is the Cactus Computational Toolkit [261] with the Carpet thorn for AMR [262], paramesh [263], PAMR/AMRD [264], HAD [265] and BAM [266]. Descriptions of some of the more computational aspects of the merger codes can be found in [228,229,231,255,260,266,268,269].…”
Section: F Numerical Algorithmsmentioning
confidence: 99%
“…The advantage here is twofold: AMR ensures that small emergent features remain well-resolved at all times, but also that only those regions which require this extra resolution gets refined, thus allowing more problems to fit within a given memory footprint. To the best of our knowledge, PAMR/AMRD [25] and HAD [26] are the only two codes with full adaptive mesh refinement (AMR) capabilities in numerical GR.…”
Section: Introductionmentioning
confidence: 99%
“…Examples of these include the Einstein Toolkit, with its related Cactus (Löffler et al, 2012;Schnetter et al, 2004), and Kranc (Husa et al, 2006) infrastructure used by LEAN (Sperhake, 2007;Zilhao et al, 2010) and Canuda (Witek et al, 2019). Other notable but non-public codes include BAM (Bruegmann et al, 2008;Marronetti et al, 2007), AMSS-NCKU (Galaviz et al, 2010), PAMR/AMRD and HAD (East et al, 2012;Neilsen et al, 2007). Codes such as SPeC (Pfeiffer et al, 2003) and bamps (Hilditch et al, 2016) implement the generalised harmonic formulation of the Einstein equations using a pseudospectral method, and discontinuous Galerkin methods are used in SpECTRE (Cao et al, 2018;Deppe et al, 2021;Kidder et al, 2017).…”
Section: Statement Of Needmentioning
confidence: 99%