Parallel Multi-Step Spectral Indicator Methods for Nonlinear Eigenvalue Problems

We consider nonlinear eigenvalue problems to compute all eigenvalues in a specified region on the complex plane. Based on domain decomposition and contour integrals, two scalable parallel multi-step methods are proposed. The first method uses the spectral indicator method to find eigenvalues and calls a linear eigensolver to compute the associated eigenvectors. The second method divides the region into subregions and uses the spectral indicator method to decide candidate regions that contain eigenvalues, computes eigenvalues in each candidate subregion using Beyn’s method; and verifies each eigenvalue by substituting it back to the system and computes the smallest eigenvalue. Each step of the two methods is carried out in parallel. Both methods are robust, accurate, and do not require prior knowledge of the number and distribution of the eigenvalues in the region. Examples are presented to show the performance of the two methods.