Volume 41, pp. 93-108, 2014.
The block preconditioned steepest descent iteration for elliptic operator eigenvalue problems
Klaus Neymeyr and Ming Zhou
Abstract
The block preconditioned steepest descent iteration is an iterative eigensolver for
subspace eigenvalue and eigenvector computations.
An important area of application of the method is the approximate solution of mesh eigenproblems
for self-adjoint elliptic partial differential operators. The subspace iteration allows to compute some of
the smallest eigenvalues together with the associated invariant subspaces simultaneously. The building
blocks of the iteration are the computation of the preconditioned
residual subspace for the current iteration subspace and the application of the Rayleigh-Ritz method
in order to extract an improved subspace iterate.
The convergence analysis of this iteration provides new sharp estimates for the
Ritz values. It is based on the analysis of the vectorial
preconditioned steepest descent iteration which appeared in
[SIAM J. Numer. Anal., 50 (2012), pp. 3188–3207].
Numerical experiments using a finite element discretization of the Laplacian
with up to
Full Text (PDF) [800 KB], BibTeX
Key words
subspace iteration, steepest descent/ascent, Rayleigh-Ritz procedure, elliptic eigenvalue problem, multigrid, preconditioning
AMS subject classifications
65N12, 65N22, 65N25, 65N30
Links to the cited ETNA articles
| [9] | Vol. 7 (1998), pp. 104-123 Andrew V. Knyazev: Preconditioned eigensolvers - an oxymoron? |
ETNA articles which cite this article
| Vol. 46 (2017), pp. 424-446 Ming Zhou and Klaus Neymeyr: Sharp Ritz value estimates for restarted Krylov subspace iterations |
| Vol. 51 (2019), pp. 331-362 Marija Miloloža Pandur: Preconditioned gradient iterations for the eigenproblem of definite matrix pairs |
| Vol. 58 (2023), pp. 597-620 Ming Zhou and Klaus Neymeyr: Convergence rates of individual Ritz values in block preconditioned gradient-type eigensolvers |