Title	A Memory Efficient Spectral Indicator Method
Creator	Sun, Jiguang
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2018-07-03T11:16
Description	Recently a novel family of eigensolvers, called spectral indicator methods (SIMs), was proposed. Given regions of the complex plane, SIMs compute indicators and use them to detect eigenvalues. Regions that contain eigenvalues are subdivided and the procedure is repeated until eigenvalues are isolated with a specified precision. In this talk, by a special way of using Cayley transformation and Krylov subspaces, a memory efficient eigensolver for sparse eigenvalue problems is proposed. The method uses little memory and is particularly suitable for the computation of many eigenvalues of large problems. The eigensolver is realized in Matlab and tested using various matrices.
Extent	30.0
Subject	Mathematics; Numerical analysis; Computer science; Global analysis
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: Michigan State University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2019-03-20
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0377211
URI	http://hdl.handle.net/2429/68981
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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