Dr Stefano Giani stefano.giani@durham.ac.uk
Associate Professor
A Posteriori Error Estimates for Elliptic Eigenvalue Problems Using Auxiliary Subspace Techniques
Giani, Stefano; Grubišic, Luka; Hakula, Harri; Ovall, Jeffrey S.
Authors
Luka Grubišic
Harri Hakula
Jeffrey S. Ovall
Abstract
We propose an a posteriori error estimator for high-order p- or hp-finite element discretizations of selfadjoint linear elliptic eigenvalue problems that is appropriate for estimating the error in the approximation of an eigenvalue cluster and the corresponding invariant subspace. The estimator is based on the computation of approximate error functions in a space that complements the one in which the approximate eigenvectors were computed. These error functions are used to construct estimates of collective measures of error, such as the Hausdorff distance between the true and approximate clusters of eigenvalues, and the subspace gap between the corresponding true and approximate invariant subspaces. Numerical experiments demonstrate the practical effectivity of the approach.
Citation
Giani, S., Grubišic, L., Hakula, H., & Ovall, J. S. (2021). A Posteriori Error Estimates for Elliptic Eigenvalue Problems Using Auxiliary Subspace Techniques. Journal of Scientific Computing, 88(3), Article 55. https://doi.org/10.1007/s10915-021-01572-2
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 20, 2021 |
Online Publication Date | Jul 20, 2021 |
Publication Date | 2021-09 |
Deposit Date | Jun 21, 2021 |
Publicly Available Date | Jun 21, 2021 |
Journal | Journal of Scientific Computing |
Print ISSN | 0885-7474 |
Electronic ISSN | 1573-7691 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Volume | 88 |
Issue | 3 |
Article Number | 55 |
DOI | https://doi.org/10.1007/s10915-021-01572-2 |
Files
Accepted Journal Article
(1.6 Mb)
PDF
Copyright Statement
This is a post-peer-review, pre-copyedit version of an article published in Journal of Scientific Computing. The final authenticated version is available online at: https://doi.org/10.1007/s10915-021-01572-2
You might also like
An hp-adaptive discontinuous Galerkin method for phase field fracture
(2023)
Journal Article
Convolutional neural network framework for wind turbine electromechanical fault detection
(2023)
Journal Article
On Effects of Concentrated Loads on Perforated Sensitive Shells of Revolution
(2023)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search