Tuesday, July 15

10:30 AM-12:30 PM
Law School, Room 290

MS19
Solving Large-Scale Nonsymmetric Eigenvalue Problems

Many important applications in chemistry, physics, and engineering lead to large, sparse nonsymmetric algebraic eigenvalue problems. These problems are a major challenge, with a number of competing methods available. Much progress has been made in recent years on theoretical and practical aspects of methods such as the Arnoldi and nonsymmetric Lanczos procedures, subspace iteration, and rational Krylov methods. The development of parallel methods for solving the nonsymmetric algebraic eigenvalue problem is still a major challenge. The speakers will describe how large-scale nonsymmetric eigenvalue problems arise in applications, discuss current methods of solution and their degree of success, explain some recent results and algorithmic developments, and summarize the software scene, including the development of templates.

Organizer: Nicholas J. Higham
University of Manchester, United Kingdom

10:30 The Numerical Solution of the Large-Scale Eigenvalue Problem with Orthogonal Projection Methods

Richard B. Lehoucq, Argonne National Laboratory

11:00 Challenging Large-Scale Non-Hermitian Eigenvalue Problems Arising in Applications

Zhaojun Bai, University of Kentucky
Speaker replaced by: David Day, Sandia National Laboratories

11:30 The Matrix Sign Function for Large Sparse Matrices

Ralph Byers and Chunyang He, University of Kansas

12:00 Templates for Eigenvalue Problems

James W. Demmel, University of California, Berkeley

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