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A multigrid-based preconditioned solver for the Helmholtz equation with a discretization by 25-point difference scheme

机译:25点差分方案离散化的Helmholtz方程的基于多网格的预处理求解器

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In this paper, a preconditioned iterative method is developed to solve the Helmholtz equation with perfectly matched layer (Helmholtz-PML equation). The complex shifted-Laplacian is generalized to precondition the Helmholtz-PML equation, which is discretized by an optimal 25-point finite difference scheme that we presented in Chen et al. (2011). A spectral analysis is given for the discrete preconditioned system from the perspective of linear fractal mapping, and Bi-CGSTAB is used to solve it. The multigrid method is employed to invert the preconditioner approximately, and a new matrix-based prolongation operator is constructed in the multigrid cycle. Numerical experiments are presented to illustrate the efficiency of the multigrid-based preconditioned Bi-CGSTAB method with the new prolongation operator. Numerical results are also given to compare the performance of the new prolongation operator with that of the prolongation operator based on the algebraic multigrid (AMG) principle.
机译:本文提出了一种预处理的迭代方法来求解具有完美匹配层的Helmholtz方程(Helmholtz-PML方程)。复位移拉普拉斯算子被广义化以预处理Helmholtz-PML方程,该方程通过我们在Chen等人中提出的最优25点有限差分方案离散化。 (2011)。从线性分形映射的角度对离散预处理系统进行了频谱分析,并使用Bi-CGSTAB对其进行了求解。采用多重网格方法对预处理器进行近似求逆,并在多重网格循环中构造了一个新的基于矩阵的延长算子。数值实验表明,使用新型延长算子,基于多重网格的预处理Bi-CGSTAB方法的效率。还给出了数值结果,以比较新的延长算子和基于代数多重网格(AMG)原理的延长算子的性能。

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