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- Title
Compressing H² Matrices for Translationally Invariant Kernels.
- Authors
Adams, R. J.; Young, J. C.; Gedney, S. D.
- Abstract
H² matrices provide compressed representations of the matrices obtained when discretizing surface and volume integral equations. The memory costs associated with storing H² matrices for static and low-frequency applications are O(N). However, when the H² representation is constructed using sparse samples of the underlying matrix, the translation matrices in the H² representation do not preserve any translational invariance present in the underlying kernel. In some cases, this can result in an H² representation with relatively large memory requirements. This paper outlines a method to compress an existing H² matrix by constructing a translationally invariant H² matrix from it. Numerical examples demonstrate that the resulting representation can provide significant memory savings.
- Subjects
MATRICES (Mathematics); INTEGRAL equations; SPARSE matrices
- Publication
Applied Computational Electromagnetics Society Journal, 2020, Vol 35, Issue 11, p1392
- ISSN
1054-4887
- Publication type
Article
- DOI
10.47037/2020.ACES.J.351165