Filtered subspace iteration for selfadjoint operators
Jeffrey Ovall
Portland State University
Abstract:
We consider the problem of computing a cluster of eigenvalues, and
its associated eigenspace, of a (possibly unbounded) selfadjoint
operator in a Hilbert space. A rational function of the operator is
constructed such that the eigenspace of interest is its dominant
eigenspace, and a subspace iteration procedure is used to
approximate this eigenspace. The computed space is then used to
obtain approximations of the eigenvalues of interest. An eigenvalue
and eigenspace convergence analysis that considers both iteration
error and discretization error is provided. A realization of the
proposed approach for a model second-order elliptic operator is
based on a discontinuous Petrov-Galerkin discretization of the
resolvent, and a variety of numerical experiments illustrate its
performance.