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Journal Articles Mathematics of Computation Year : 2020

Guaranteed a posteriori bounds for eigenvalues and eigenvectors: multiplicities and clusters

Abstract

This paper presents a posteriori error estimates for conforming numerical approximations of eigenvalue clusters of second-order self-adjoint elliptic linear operators with compact resolvent. Given a cluster of eigenvalues, we estimate the error in the sum of the eigenvalues, as well as the error in the eigenvectors represented through the density matrix, i.e., the orthogonal projector on the associated eigenspace. This allows us to deal with degenerate (multiple) eigenvalues within the framework. All the bounds are valid under the only assumption that the cluster is separated from the surrounding smaller and larger eigenvalues; we show how this assumption can be numerically checked. Our bounds are guaranteed and converge with the same speed as the exact errors. They can be turned into fully computable bounds as soon as an estimate on the dual norm of the residual is available, which is presented in two particular cases: the Laplace eigenvalue problem discretized with conforming finite elements, and a Schrödinger operator with periodic boundary conditions of the form $−∆ + V$ discretized with planewaves. For these two cases, numerical illustrations are provided on a set of test problems.
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Dates and versions

hal-02127954 , version 1 (13-05-2019)
hal-02127954 , version 2 (04-03-2020)
hal-02127954 , version 3 (10-08-2020)

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Eric Cancès, Geneviève Dusson, Yvon Maday, Benjamin Stamm, Martin Vohralík. Guaranteed a posteriori bounds for eigenvalues and eigenvectors: multiplicities and clusters. Mathematics of Computation, 2020, 89 (326), pp.2563-2611. ⟨10.1090/mcom/3549⟩. ⟨hal-02127954v3⟩
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