Cookies

We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.


Durham Research Online
You are in:

A Posteriori Error Estimates for Elliptic Eigenvalue Problems Using Auxiliary Subspace Techniques

Giani, Stefano and Grubišic, Luka and Hakula, Harri and Ovall, Jeffrey S. (2021) 'A Posteriori Error Estimates for Elliptic Eigenvalue Problems Using Auxiliary Subspace Techniques.', Journal of scientific computing., 88 (3). p. 55.

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.

Item Type:Article
Full text:(AM) Accepted Manuscript
Download PDF
(1587Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1007/s10915-021-01572-2
Publisher 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
Date accepted:20 June 2021
Date deposited:21 June 2021
Date of first online publication:20 July 2021
Date first made open access:27 January 2023

Save or Share this output

Export:
Export
Look up in GoogleScholar