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Eigendecomposition of the Discrete Double-Curl Operator with Application to Fast Eigensolver for Three-Dimensional Photonic Crystals
Author(s) -
Tsung-Ming Huang,
Han-En Hsieh,
Wen-Wei Lin,
Weichung Wang
Publication year - 2013
Publication title -
siam journal on matrix analysis and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.268
H-Index - 101
eISSN - 1095-7162
pISSN - 0895-4798
DOI - 10.1137/120872486
Subject(s) - eigenvalues and eigenvectors , lanczos resampling , mathematics , solver , conjugate gradient method , curl (programming language) , circulant matrix , eigendecomposition of a matrix , mathematical analysis , algorithm , mathematical optimization , computer science , physics , quantum mechanics , programming language
This article focuses on the discrete double-curl operator arising in the Maxwell equation that models three-dimensional photonic crystals with face-centered cubic lattice. The discrete double-curl operator is the degenerate coefficient matrix of the generalized eigenvalue problems (GEVP) due to the Maxwell equation. We derive an eigendecomposition of the degenerate coefficient matrix and explore an explicit form of orthogonal basis for the range and null spaces of this matrix. To solve the GEVP, we apply these theoretical results to project the GEVP to a standard eigenvalue problem (SEVP), which involves only the eigenspace associated with the nonzero eigenvalues of the GEVP, and therefore the zero eigenvalues are excluded and will not degrade the computational efficiency. This projected SEVP can be solved efficiently by the inverse Lanczos method. The linear systems within the inverse Lanczos method are well-conditioned and can be solved efficiently by the conjugate gradient method without using a precon...

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