Adaptive FEM with optimal convergence rate for non-self-adjoint eigenvalue problems

Fuente: arXiv
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Autori principali: Wang, Shixi, Bi, Hai, Yang, Yidu
Natura: Preprint
Pubblicazione: 2026
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author Wang, Shixi
Bi, Hai
Yang, Yidu
author_facet Wang, Shixi
Bi, Hai
Yang, Yidu
contents In this paper, we first discuss the optimal convergence of the adaptive finite element methods for non-self-adjoint eigenvalue problems. We present new theoretical error estimators and computable error estimators for multiple and clustered eigenvalues with the help of the error estimators of finite element solutions for the corresponding source problems, and prove the equivalence between these two estimators. We propose an adaptive algorithm for the eigenvalue cluster and demonstrate that it achieves the optimal convergence rate.We also provide numerical experiments to support our theoretical findings.
format Preprint
id arxiv_https___arxiv_org_abs_2603_12973
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Adaptive FEM with optimal convergence rate for non-self-adjoint eigenvalue problems
Wang, Shixi
Bi, Hai
Yang, Yidu
Numerical Analysis
Spectral Theory
In this paper, we first discuss the optimal convergence of the adaptive finite element methods for non-self-adjoint eigenvalue problems. We present new theoretical error estimators and computable error estimators for multiple and clustered eigenvalues with the help of the error estimators of finite element solutions for the corresponding source problems, and prove the equivalence between these two estimators. We propose an adaptive algorithm for the eigenvalue cluster and demonstrate that it achieves the optimal convergence rate.We also provide numerical experiments to support our theoretical findings.
title Adaptive FEM with optimal convergence rate for non-self-adjoint eigenvalue problems
topic Numerical Analysis
Spectral Theory
url https://arxiv.org/abs/2603.12973