Title
A Filtered Lanczos Procedure for Extreme and Interior Eigenvalue Problems.
Abstract
When combined with Krylov projection methods, polynomial filtering can provide a powerful method for extracting extreme or interior eigenvalues of large sparse matrices. This general approach can be quite efficient in the situation when a large number of eigenvalues is sought. However, its competitiveness depends critically on a good implementation. This paper presents a technique based on such a combination to compute a group of extreme or interior eigenvalues of a real symmetric (or complex Hermitian) matrix. The technique harnesses the effectiveness of the Lanczos algorithm with partial reorthogonalization and the power of polynomial filtering. Numerical experiments indicate that the method can be far superior to competing algorithms when a large number of eigenvalues and eigenvectors is to be computed.
Year
DOI
Venue
2012
10.1137/110836535
SIAM JOURNAL ON SCIENTIFIC COMPUTING
Keywords
Field
DocType
Lanczos algorithm,polynomial filtering,partial reorthogonalization,interior eigenvalue problems
Mathematical optimization,Lanczos resampling,Matrix (mathematics),Mathematical analysis,Lanczos algorithm,Polynomial filtering,Hermitian matrix,Mathematics,Sparse matrix,Eigenvalues and eigenvectors
Journal
Volume
Issue
ISSN
34
4
1064-8275
Citations 
PageRank 
References 
12
0.79
3
Authors
2
Name
Order
Citations
PageRank
Haw-ren Fang113213.24
Yousef Saad21940254.74