Title
Detecting Localization in an Invariant Subspace
Abstract
A normalized eigenvector, or, more interestingly, an invariant subspace, is localized if its significant entries are defined by just part(s) of the matrix and negligible elsewhere. This paper presents two new procedures to detect such localization in eigenvectors of a symmetric tridiagonal matrix. The procedures are intended for use before the actual eigenvector computation. If localization is found, one may reduce costs by computing the vectors just from the relevant matrix regions. Practical eigensolvers from numerical libraries such as LAPACK and ScaLAPACK already inspect a given tridiagonal $T$ for off-diagonal entries that are of small magnitude relative to the matrix norm. These so-called splitting points indicate that $T$ breaks into smaller blocks, each one defining a subset of eigenvalues and localized eigenvectors. However, localization can occur even when none of the off-diagonals is particularly small. Our study investigates this more complicated phenomenon in the context of invariant subspaces belonging to isolated eigenvalue clusters.
Year
DOI
Venue
2011
10.1137/09077624X
SIAM J. Scientific Computing
Keywords
DocType
Volume
relevant matrix region,small magnitude,invariant subspace,detecting localization,actual eigenvector computation,normalized eigenvector,invariant subspaces,matrix norm,symmetric tridiagonal matrix,localized eigenvectors,complicated phenomenon,envelope,localization,inverse iteration
Journal
33
Issue
ISSN
Citations 
6
1064-8275
2
PageRank 
References 
Authors
0.42
9
2
Name
Order
Citations
PageRank
Christof Vömel116817.80
Beresford N. Parlett245060.59