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Parallel subspace correction methods for nearly singular systems

机译:近似奇异系统的并行子空间校正方法

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摘要

In this paper we consider the parallel subspace correction (PSC) methods for the nearly singular systems. We apply the PSC methods as the preconditioners when we solve the nearly singular systems by the conjugate gradient methods. Our focus is to estimate the condition number of the preconditioned systems. We deduce the parameter independent estimates on the PSC preconditioners for the nearly singular systems, under appropriate assumptions on subspace decomposition. The main assumption is that the kernel of the singular part of the system can be decomposed into a sum of local kernel subspaces. Our estimates can be applied into actual problems, and two examples are analyzed in this paper. One is the elliptic problem with large jumps in the coefficients, the other is the planar nearly incompressible elasticity problem with the Scott-Vogelius finite element discretization.Weprove that the related parallel multilevel methods for both examples are convergent uniformly, with respect to the coefficients and the mesh size.
机译:在本文中,我们考虑了近似奇异系统的并行子空间校正(PSC)方法。当我们用共轭梯度法求解几乎奇异的系统时,我们将PSC方法用作前提条件。我们的重点是估计预处理系统的条件数。在子空间分解的适当假设下,我们推导了几乎奇异系统的PSC预条件器上的参数独立估计。主要假设是可以将系统奇异部分的内核分解为局部内核子空间的总和。我们的估计可以应用于实际问题,并在本文中分析两个示例。一个是系数大跳的椭圆问题,另一个是斯科特-沃格留斯有限元离散化的平面几乎不可压缩的弹性问题,我们证明两个实例的相关并行多级方法在系数和网格尺寸。

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