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首页> 外文期刊>SIAM Journal on Matrix Analysis and Applications >An optimal block iterative method and preconditioner for banded matrices with applications to PDEs on irregular domains
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An optimal block iterative method and preconditioner for banded matrices with applications to PDEs on irregular domains

机译:带状矩阵的最优块迭代方法和预处理器及其在不规则域上的PDE应用

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Classical Schwarz methods and preconditioners subdivide the domain of a PDE into subdomains and use Dirichlet transmission conditions at the artificial interfaces. Optimized Schwarz methods use Robin (or higher order) transmission conditions instead, and the Robin parameter can be optimized so that the resulting iterative method has an optimized convergence factor. The usual technique used to find the optimal parameter is Fourier analysis; but this is applicable only to certain regular domains, for example, a rectangle, and with constant coefficients. In this paper, we present a completely algebraic version of the optimized Schwarz method, including an algebraic approach to finding the optimal operator or a sparse approximation thereof. This approach allows us to apply this method to any banded or block banded linear system of equations, and in particular to discretizations of PDEs in two and three dimensions on irregular domains. With the computable optimal operator, we prove that the optimized Schwarz method converges in no more than two iterations, even for the case of many subdomains (which means that this optimal operator communicates globally). Similarly, we prove that when we use an optimized Schwarz preconditioner with this optimal operator, the underlying minimal residual Krylov subspace method (e.g., GMRES) converges in no more than two iterations. Very fast convergence is attained even when the optimal transmission operator is approximated by a sparse matrix. Numerical examples illustrating these results are presented.
机译:经典的Schwarz方法和预处理器将PDE的域细分为子域,并在人工接口上使用Dirichlet传输条件。优化的Schwarz方法改为使用Robin(或更高阶)传输条件,并且可以优化Robin参数,以便最终的迭代方法具有优化的收敛因子。用于找到最佳参数的常用技术是傅里叶分析。但这仅适用于某些规则域,例如矩形且系数恒定。在本文中,我们提出了一种优化的Schwarz方法的完全代数形式,其中包括一种用于找到最佳算子或其稀疏近似的代数方法。这种方法使我们可以将此方法应用于任何带状或块状线性方程组,尤其是不规则域上二维和三维上离散PDE的离散化。利用可计算的最优算子,我们证明了优化的Schwarz方法在不超过两个迭代的情况下收敛,即使对于许多子域也是如此(这意味着该最优算子可以进行全局通信)。同样,我们证明了,当我们使用带有该最优算子的优化Schwarz预条件器时,底层最小残留Krylov子空间方法(例如GMRES)在不超过两次迭代中即可收敛。即使通过稀疏矩阵近似最佳传输算子,也可以实现非常快的收敛。给出了说明这些结果的数值示例。

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