Perturbation, extraction and refinement of invariant pairs for matrix polynomials

Perturbation, extraction and refinement of invariant pairs for matrix polynomials
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矩阵多项式不变对的扰动、提取和细化

DOI:
10.1016/j.laa.2010.06.029
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发表时间:
2011
影响因子:
1.1
通讯作者:
Betcke T
Betcke T
中科院分区:
数学3区
文献类型:
--
作者:
Betcke T

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概括特征向量的概念,不变子空间经常在线性特征值问题的背景下使用,从而在需要计算多个特征值和/或特征向量的应用中产生概念上优雅且数值稳定的公式。对于多项式特征值问题,可以预期类似的好处,其中不变子空间的概念需要替换为不变对的概念。迄今为止,人们对这种不变对的数值方面知之甚少。本文的目的就是填补这一空白。研究了矩阵多项式扰动下不变对的行为,并给出了一阶扰动展开式。从计算的角度来看,我们研究如何从矩阵多项式的线性化中最好地提取不变对。此外,我们直接基于多项式公式描述了有效的细化过程。来自许多应用的矩阵多项式的数值实验证明了我们的提取和精炼程序的有效性。
Generalizing the notion of an eigenvector, invariant subspaces are frequently used in the context of linear eigenvalue problems, leading to conceptually elegant and numerically stable formulations in applications that require the computation of several eigenvalues and/or eigenvectors. Similar benefits can be expected for polynomial eigenvalue problems, for which the concept of an invariant subspace needs to be replaced by the concept of an invariant pair. Little has been known so far about numerical aspects of such invariant pairs. The aim of this paper is to fill this gap. The behavior of invariant pairs under perturbations of the matrix polynomial is studied and a first-order perturbation expansion is given. From a computational point of view, we investigate how to best extract invariant pairs from a linearization of the matrix polynomial. Moreover, we describe efficient refinement procedures directly based on the polynomial formulation. Numerical experiments with matrix polynomials from a number of applications demonstrate the effectiveness of our extraction and refinement procedures.
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