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New upper bounds for the spectral variation of a general matrix

Numerical Analysis 2020-09-09 v3 Numerical Analysis

Abstract

Let ACn×nA\in\mathbb{C}^{n\times n} be a normal matrix with spectrum {λi}i=1n\{\lambda_{i}\}_{i=1}^{n}, and let A~=A+ECn×n\widetilde{A}=A+E\in\mathbb{C}^{n\times n} be a perturbed matrix with spectrum {λ~i}i=1n\{\widetilde{\lambda}_{i}\}_{i=1}^{n}. If A~\widetilde{A} is still normal, the celebrated Hoffman--Wielandt theorem states that there exists a permutation π\pi of {1,,n}\{1,\ldots,n\} such that (i=1nλ~π(i)λi2)1/2EF\big(\sum_{i=1}^{n}|\widetilde{\lambda}_{\pi(i)}-\lambda_{i}|^{2}\big)^{1/2}\leq\|E\|_{F}, where F\|\cdot\|_{F} denotes the Frobenius norm of a matrix. This theorem reveals the strong stability of the spectrum of a normal matrix. However, if AA or A~\widetilde{A} is non-normal, the Hoffman--Wielandt theorem does not hold in general. In this paper, we present new upper bounds for (i=1nλ~π(i)λi2)1/2\big(\sum_{i=1}^{n}|\widetilde{\lambda}_{\pi(i)}-\lambda_{i}|^{2}\big)^{1/2}, provided that both AA and A~\widetilde{A} are general matrices. Some of our estimates improve or generalize the existing ones.

Keywords

Cite

@article{arxiv.1703.02422,
  title  = {New upper bounds for the spectral variation of a general matrix},
  author = {Xuefeng Xu},
  journal= {arXiv preprint arXiv:1703.02422},
  year   = {2020}
}