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arXiv 2302.00575gr-qc
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数值相对论中谱元素的自适应hp细化

Adaptive hp-Refinement for Spectral Elements in Numerical Relativity

Sarah Renkhoff, Daniela Cors, David Hilditch, Bernd Brügmann

AI总结:

本文为数值相对论代码bamps引入物理无关的自适应hp细化方法,并通过一维和二维示例验证其在性能、扩展性和精度上优于静态网格。

摘要:

当数值模拟需要处理具有广泛时间依赖长度尺度的物理问题时,动态自适应离散化可能成为首选方法。我们以完全自适应、物理无关的hp细化的形式,对数值相对论代码bamps进行了一次重大升级。我们描述了谱元素方法背景下网格细化的基础、在bamps中执行细化所使用的精确算法,以及用于驱动细化的若干指示函数。最后,我们测试了该代码在处理几个一维和二维示例问题时的性能、扩展性和精度,显示出相对于静态网格配置的明显改进。特别是,我们考虑了一个简单的非线性波动方程、一个与引力最小耦合的实标量场的演化,以及非线性引力波。

英文摘要:

When a numerical simulation has to handle a physics problem with a wide range of time-dependent length scales, dynamically adaptive discretizations can be the method of choice. We present a major upgrade to the numerical relativity code bamps in the form of fully adaptive, physics-agnostic hp-refinement. We describe the foundations of mesh refinement in the context of spectral element methods, the precise algorithm used to perform refinement in bamps, as well as several indicator functions used to drive it. Finally, we test the performance, scaling, and the accuracy of the code in treating several 1d and 2d example problems, showing clear improvements over static mesh configurations. In particular, we consider a simple non-linear wave equation, the evolution of a real scalar field minimally coupled to gravity, as well as nonlinear gravitational waves.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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