Communications on Applied Mathematics and Computation ›› 2025, Vol. 7 ›› Issue (2): 606-636.doi: 10.1007/s42967-024-00372-3

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A Domain Decomposition Method for Nonconforming Finite Element Approximations of Eigenvalue Problems

Qigang Liang1,2, Wei Wang3, Xuejun Xu1,2   

  1. 1 School of Mathematical Science, Tongji University, Shanghai 200092, China;
    2 Key Laboratory of Intelligent Computing and Applications (Tongji University), Ministry of Education, Shanghai 200092, China;
    3 LSEC, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2023-04-23 Revised:2023-12-29 Accepted:2024-01-06 Online:2025-06-20 Published:2025-04-21
  • Supported by:
    The first author is supported by the China Postdoctoral Science Foundation (No. 2023M742662). The third author is supported by the National Natural Science Foundation of China (Grant Nos. 12071350 and 12331015).

Abstract: Since the nonconforming finite elements (NFEs) play a significant role in approximating PDE eigenvalues from below, this paper develops a new and parallel two-level preconditioned Jacobi-Davidson (PJD) method for solving the large scale discrete eigenvalue problems resulting from NFE discretization of 2mth (m = 1, 2) order elliptic eigenvalue problems. Combining a spectral projection on the coarse space and an overlapping domain decomposition (DD), a parallel preconditioned system can be solved in each iteration. A rigorous analysis reveals that the convergence rate of our two-level PJD method is optimal and scalable. Numerical results supporting our theory are given.

Key words: PDE eigenvalue problems, Nonconforming finite elements (NFEs), Preconditioned Jacobi-Davidson (PJD) method, Overlapping domain decomposition (DD)

CLC Number: