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 |