1
Return

Pointwise a Posteriori Error Estimators for Multiple and Clustered Eigenvalue Computations

delete2026-07-31
delete0
PRE
AI
Z
Z. G. Li
梁启刚 (Qigang Liang)
X
Xuejun Xu *
DOI:10.1007/s10915-026-03378-6delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
In this work, we propose a pointwise a posteriori error estimator for conforming finite element approximations of eigenfunctions corresponding to multiple and clustered eigenvalues of elliptic operators. It is proven that the pointwise a posteriori error estimator is reliable and efficient, up to some logarithmic factors of the mesh size. The constants involved in the reliability and efficiency are independent of the gaps among the targeted eigenvalues, the mesh size and the number of mesh level. Specially, we obtain a by-product that edge residuals dominate the a posteriori error in the sense of $$L^{\infty }$$ -norm when the linear element is used. With the aid of the weighted Sobolev stability of the $$L^2$$ -projection, we also propose a new method to prove the reliability of the a posteriori error estimator for higher order finite elements. A key ingredient in the a posteriori error analysis is some new estimates for regularized derivative Green’s functions. Some numerical experiments verify our theoretical results.
Keywords:
Elliptic eigenvalue problems
Multiple and clustered eigenvalues
Maximum norm
Finite element methods
A posteriori error estimator

Journal

Journal of Scientific Computing cover
Journal of Scientific Computing
IF:
3.3
Papers:
652
Citations:
9.6K

Organization

S
School of Mathematical Sciences
Scholars:
525
Papers: 303
Citations: 1
Cited Papers

Cited Papers

Citing Papers

Citing Papers