Modern methods for the iterative computation of eigenpairs of matrices of high dimension
Henk A. van der Vorst · ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik · 2004
Abstract We give an overview of computational methods for the eigenproblem Ax = λx and related eigenproblems, in particular those for large matrices. Subspace methods, including the Lanczos and Arnoldi methods, have become increasingly popular. We will highlight a quite recent subspace method for the iterative computation of a few eigenvalues and eigenvectors of high‐dimensional eigenproblems: The so‐called Jacobi‐Davidson method. The application of this method for standard, generalized, and quadratic eigenproblems will be discussed.