Lessons for adaptive mesh refinement in numerical relativity
Lessons for adaptive mesh refinement in numerical relativity
复制标题
数值相对论中自适应网格细化的经验教训
DOI:
10.1088/1361-6382/ac6fa9
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发表时间:
2022
影响因子:
3.5
通讯作者:
Radia M
中科院分区:
文献类型:
--
作者:
Radia M
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, eg 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.
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DOI:
10.1017/9781009253161
发表时间:
2023-02
期刊:
--
影响因子:
--
作者:
S. Hawking;G. Ellis
通讯作者:
S. Hawking;G. Ellis
影响因子:
5
作者:
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通讯作者:
D. Traykova;K. Clough;T. Helfer;E. Berti;P. Ferreira;L. Hui
DOI:
--
发表时间:
2004
期刊:
影响因子:
--
作者:
H. Stephani
通讯作者:
H. Stephani
DOI:
10.14288/1.0085709
发表时间:
2002
期刊:
--
影响因子:
--
作者:
F. Pretorius
通讯作者:
F. Pretorius
影响因子:
3.5
作者:
K. Clough
通讯作者:
K. Clough