Lessons for adaptive mesh refinement in numerical relativity
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Authors
Clough, Katy
Figueras, Pau
Lim, Eugene A
Aurrekoetxea, Josu C
França, Tiago
Helfer, Thomas
Publication Date
2022-05-13Journal Title
Classical and Quantum Gravity
ISSN
0264-9381
Publisher
IOP Publishing
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Radia, M., Sperhake, U., Drew, A., Clough, K., Figueras, P., Lim, E. A., Ripley, J., et al. (2022). Lessons for adaptive mesh refinement in numerical relativity. Classical and Quantum Gravity https://doi.org/10.1088/1361-6382/ac6fa9
Abstract
We demonstrate the flexibility and utility of the Berger-Rigoutsos Adaptive
Mesh Refinement (AMR) algorithm used in the open-source numerical relativity
code GRChombo for generating gravitational waveforms from binary black-hole
inspirals, and for studying other problems involving non-trivial matter
configurations. We show that GRChombo can produce high quality binary
black-hole waveforms through a code comparison with the established numerical
relativity code Lean. 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 GRChombo.
Keywords
gr-qc, gr-qc, astro-ph.HE, hep-ph
Sponsorship
STFC (1936371)
Science and Technology Facilities Council (1936371)
European Research Council (646597)
Science and Technology Facilities Council (ST/P000673/1)
Science and Technology Facilities Council (ST/R002452/1)
Science and Technology Facilities Council (ST/R00689X/1)
STFC (ST/W001667/1)
Embargo Lift Date
2023-05-13
Identifiers
External DOI: https://doi.org/10.1088/1361-6382/ac6fa9
This record's URL: https://www.repository.cam.ac.uk/handle/1810/337210
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