An a posteriori estimator of eigenvalue/eigenvector error for penalty-type discontinuous Galerkin methods

Stefano Giani, Luka Grubišić, Harri Hakula and Jeffrey S. Ovall

Applied Mathematics and Computation, 2018, vol. 319, issue C, 562-574

Abstract: We provide an abstract framework for analyzing discretization error for eigenvalue problems discretized by discontinuous Galerkin methods such as the local discontinuous Galerkin method and symmetric interior penalty discontinuous Galerkin method. The analysis applies to clusters of eigenvalues that may include degenerate eigenvalues. We use asymptotic perturbation theory for linear operators to analyze the dependence of eigenvalues and eigenspaces on the penalty parameter. We first formulate the DG method in the framework of quadratic forms and construct a companion infinite dimensional eigenvalue problem. With the use of the companion problem, the eigenvalue/vector error is estimated as a sum of two components. The first component can be viewed as a “non-conformity” error that we argue can be neglected in practical estimates by properly choosing the penalty parameter. The second component is estimated a posteriori using auxiliary subspace techniques, and this constitutes the practical estimate.

Keywords: Eigenvalue problem; Finite element method; A posteriori error estimates; Discontinuous Galerkin method (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:319:y:2018:i:c:p:562-574

DOI: 10.1016/j.amc.2017.07.007

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