A shifted Laplace rational filter for large-scale eigenvalue problems

Abstract: We present a rational filter for computing all eigenvalues of a symmetric definite eigenvalue problem lying in an interval on the real axis. The linear systems arising from the filter embedded in the subspace iteration framework, are solved via a preconditioned Krylov method. The choice of the poles of the filter is based on two criteria. On the one hand, the filter should enhance the eigenvalues in the interval of interest, which suggests that the poles should be chosen close to or in the interval. On the other hand, the choice of poles has an important impact on the convergence speed of the iterative method. For the solution of problems arising from vibrations, the two criteria contradict each other, since fast convergence of the eigensolver requires poles to be in or close to the interval, whereas the iterative linear system solver becomes cheaper when the poles lie further away from the eigenvalues. In the paper, we propose a selection of poles inspired by the shifted Laplace preconditioner for the Helmholtz equation. We show numerical experiments from finite element models of vibrations. We compare the shifted Laplace rational filter with rational filters based on quadrature rules for contour integration.