This paper introduces bootstrap multigrid methods for solving eigenvalue problems arising from the discretization of partial differential equations. Inspired by the full bootstrap algebraic multigrid (BAMG) setup algorithm that includes an AMG eigensolver, it is illustrated how the algorithm can be simplified for the case of a discretized partial differential equation (PDE), thereby developing a bootstrap geometric multigrid (BMG) approach. We illustrate numerically the efficacy of the BMG method for: (1) recovering eigenvalues having large multiplicity, (2) computing interior eigenvalues, and (3) approximating shifted indefinite eigenvalue problems. Numerical experiments are presented to illustrate the basic components and ideas behind the success of the overall bootstrap multigrid approach. For completeness, we present a simplified error analysis of a two-grid bootstrap algorithm for the Laplace-Beltrami eigenvalue problem.
翻译:本文介绍了解决部分差异方程式离散产生的半基因值问题的靴式多格方法。在全靴式代数多格(BAMG)设置算法(包括AMG )的启发下,说明了如何简化离散式半数方程式的算法(PDE),从而开发了一种靴式几何多格(BMG)方法。我们用数字方式说明了BMG方法的功效:(1) 回收具有巨大多重性的双基因值,(2) 计算内源值,以及(3) 近似超变异型非基因值问题。提出了数字实验,以说明整个靴式多格方法成功背后的基本组成部分和想法。关于完整性,我们提出了Laplace-Beltrami egenvalue问题的两格式靴式靴式算法的简化错误分析。