We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

A Memory Efficient Spectral Indicator Method for Eigenvalue Problems

Formal Metadata

Title
A Memory Efficient Spectral Indicator Method for Eigenvalue Problems
Alternative Title
A Memory Efficient Spectral Indicator Method
Title of Series
Number of Parts
22
Author
License
CC Attribution - NonCommercial - NoDerivatives 4.0 International:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
Identifiers
Publisher
Release Date
Language

Content Metadata

Subject Area
Genre
Abstract
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.