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Lessons for adaptive mesh refinement in numerical relativity

Miren Radia, Ulrich Sperhake, Amelia Drew, Katy Clough, Pau Figueras, Eugene A. Lim, Justin L. Ripley, Josu C. Aurrekoetxea, Tiago França, Thomas Helfer

2022Classical and Quantum Gravity47 citationsDOIOpen Access PDF

Abstract

Abstract We demonstrate the flexibility and utility of the Berger–Rigoutsos adaptive mesh refinement (AMR) algorithm used in the open-source numerical relativity (NR) code GRC hombo for generating gravitational waveforms from binary black-hole (BH) inspirals, and for studying other problems involving non-trivial matter configurations. We show that GRC hombo can produce high quality binary BH waveforms through a code comparison with the established NR code L ean . We also discuss some of the technical challenges involved in making use of full AMR (as opposed to, e.g. moving box mesh refinement), including the numerical effects caused by using various refinement criteria when regridding. We suggest several ‘rules of thumb’ for when to use different tagging criteria for simulating a variety of physical phenomena. We demonstrate the use of these different criteria through example evolutions of a scalar field theory. Finally, we also review the current status and general capabilities of GRC hombo .

Topics & Concepts

Adaptive mesh refinementNumerical relativityPhysicsScalar (mathematics)Black hole (networking)Binary numberAlgorithmTheory of relativityCode (set theory)General relativityWaveformField (mathematics)Polygon meshTheoretical physicsComputer scienceProgramming languagePure mathematicsGeometryQuantum mechanicsComputer graphics (images)ThermodynamicsLink-state routing protocolSet (abstract data type)Routing protocolRouting (electronic design automation)MathematicsArithmeticComputer networkVoltagePulsars and Gravitational Waves ResearchAstrophysical Phenomena and ObservationsBlack Holes and Theoretical Physics
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