Application of the Jacobi-Davidson method for spectral low-rank preconditioning in computational electromagnetics problems
DOI10.1007/s40324-014-0025-6zbMath1322.78015OpenAlexW2034346462MaRDI QIDQ2353267
Publication date: 9 July 2015
Published in: S\(\vec{\text{e}}\)MA Journal (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40324-014-0025-6
preconditioningiterative methodscomputational electromagneticsJacobi-Davidsonspectral low-rank updates
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Iterative numerical methods for linear systems (65F10) Basic methods for problems in optics and electromagnetic theory (78Mxx) Preconditioners for iterative methods (65F08)
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- Computational experience with sequential and parallel, preconditioned Jacobi--Davidson for large, sparse symmetric matrices
- Sparse symmetric preconditioners for dense linear systems in electromagnetism
- Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems
- An Iterative Solution Method for Linear Systems of Which the Coefficient Matrix is a Symmetric M-Matrix
- Jacobi--Davidson Style QR and QZ Algorithms for the Reduction of Matrix Pencils
- Parallel Preconditioning with Sparse Approximate Inverses
- ARPACK Users' Guide
- A Class of Spectral Two-Level Preconditioners
- The Fast Multipole Method I: Error Analysis and Asymptotic Complexity
- A Jacobi–Davidson Iteration Method for Linear Eigenvalue Problems
- Combining Fast Multipole Techniques and an Approximate Inverse Preconditioner for Large Electromagnetism Calculations
- A fast algorithm for particle simulations
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