A Parallel Refined Jacobi-Davidson Method for Quadratic Eigenvalue Problems
Shunxu Wang · 2010
This paper presents a parallel refined Jacobi-Davidson method for computing extreme eigenpairs of quadratic eigenvalue problems. The method directly computes the refined Ritz pairs in the projection subspace, and expands the subspace by the solution of the correction equation. Combining with the restarting scheme, the method can solve several eigenpairs of quadratic eigenvalue problems. The numerical experiments on a parallel computer show that the parallel refined Jacobi-Davidson method for computing quadratic eigenvalue problems is very effective.