Monday, July 13

MS22
Some Recent Developments in Matrix Methods in Computational Electromagnetics

2:00 PM-4:00 PM
Room: Sidney Smith 1088

This minisymposium has been moved from Tuesday to Monday.

The session will feature four papers that will review different aspects of matrix methods as applied to problems in Computational Electromagnetics (CEM). The first of these is a paper by Tausch and White of MIT, which will not only discuss techniques for sparsification of matrices via the use of the wavelets and Multipole methods, but will also cover issues related to preconditioning of matrices for iterative solution. This will be followed by an interesting discussion of algorithms for the solution of Quadratic Eigenmatrix Equations in Computational Electromagnetics by Lee and Liu of WPU. The spectral convergence issue, related to the Interior Source Method with Point Matching, will be addressed by a paper by Nicolaides and Kangro of CMU. And, finally, various parallel algorithms for Sparse Matrix problems arising in CEM will be discussed by Sameh, Sarin and Grama of Purdue.

2:00 Solving Quadratic Eigenmatrix Equations in Computational Electromagnetics

Jin-Fa Lee and Chibing Liu, Worcester Polytechnic Institute

2:30 Parallel Algorithms for Sparse Matrix Problems in Computational Electromagnetics

Ahmed Sameh, Vivek Sarin and Ananth Grama, Purdue University, West Lafayette

3:00 Wavelet and Multipole Sparsification for Integral Equations on Multiply Connected Domains

Johannes Tausch and Jacob White, Massachusetts Institute of Technology

3:30 Spectral Convergence of the Interior Source Method with Point Matching

Roy Nicolaides, Carnegie Mellon University; and Urve Kangro, Tartu University, Estonia