Abstract
We discuss several techniques for finding leading eigenvalues and eigenvectors for large sparse matrices. The techniques are demonstrated on a scalar Helmholtz equation derived from a model semiconductor rib waveguide problem. We compare the simple inverse iteration approach with more sophisticated methods, including minimum degree reordering, Arnoldi and Lanczos methods. We then propose a new Arnoldi method designed particularly for the constrained generalized eigenvalue problem, a formulation arising naturally from the scalar waveguide problem.
| Original language | English (US) |
|---|---|
| Pages | 645-652 |
| Number of pages | 8 |
| State | Published - Jan 1 1996 |
| Event | Proceedings of the 1996 12th Annual Review of Progress in Applied Computational Electromagnetics. Part 1 (of 2) - Monterey, CA, USA Duration: Mar 18 1996 → Mar 22 1996 |
Other
| Other | Proceedings of the 1996 12th Annual Review of Progress in Applied Computational Electromagnetics. Part 1 (of 2) |
|---|---|
| City | Monterey, CA, USA |
| Period | 3/18/96 → 3/22/96 |
Fingerprint Dive into the research topics of 'Methods for large sparse eigenvalue problems from waveguide analysis'. Together they form a unique fingerprint.
Cite this
Peng, C., & Boley, D. (1996). Methods for large sparse eigenvalue problems from waveguide analysis. 645-652. Paper presented at Proceedings of the 1996 12th Annual Review of Progress in Applied Computational Electromagnetics. Part 1 (of 2), Monterey, CA, USA, .