Greedy algorithms for high-dimensional eigenvalue problems
Numerical Analysis
2013-04-10 v1
Abstract
In this article, we present two new greedy algorithms for the computation of the lowest eigenvalue (and an associated eigenvector) of a high-dimensional eigenvalue problem, and prove some convergence results for these algorithms and their orthogonalized versions. The performance of our algorithms is illustrated on numerical test cases (including the computation of the buckling modes of a microstructured plate), and compared with that of another greedy algorithm for eigenvalue problems introduced by Ammar and Chinesta.
Cite
@article{arxiv.1304.2631,
title = {Greedy algorithms for high-dimensional eigenvalue problems},
author = {Eric Cancès and Virginie Ehrlacher and Tony Lelièvre},
journal= {arXiv preprint arXiv:1304.2631},
year = {2013}
}
Comments
33 pages, 5 figures