Algebraic Multilevel Methods for Markov Chains
Numerical Analysis
2018-01-03 v2
Abstract
A new algebraic multilevel algorithm for computing the second eigenvector of a column-stochastic matrix is presented. The method is based on a deflation approach in a multilevel aggregation framework. In particular a square and stretch approach, first introduced by Treister and Yavneh, is applied. The method is shown to yield good convergence properties for typical example problems.
Keywords
Cite
@article{arxiv.1711.04332,
title = {Algebraic Multilevel Methods for Markov Chains},
author = {Lukas Polthier},
journal= {arXiv preprint arXiv:1711.04332},
year = {2018}
}
Comments
19 pages, LaTex