Sharp Convergence Estimates for the Preconditioned Steepest Descent Method for Hermitian Eigenvalue Problems

DOI10.1137/040620643zbMath1113.65033OpenAlexW2076995010MaRDI QIDQ5470942

Evgueni E. Ovtchinnikov

Publication date: 2 June 2006

Published in: SIAM Journal on Numerical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/040620643

zbMATH Keywords

preconditioningEuclidean spacesteepest descenteigenvalue computationsharp convergence estimatesHermitian linear operator

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical computation of matrix norms, conditioning, scaling (65F35)

Related Items (10)

Convergence theory for preconditioned eigenvalue solvers in a nutshell ⋮ Hybrid preconditioning for iterative diagonalization of ill-conditioned generalized eigenvalue problems in electronic structure calculations ⋮ THE HYPERBOLIC QUADRATIC EIGENVALUE PROBLEM ⋮ Convergence rates of individual Ritz values in block preconditioned gradient-type eigensolvers ⋮ A Filtered-Davidson Method for Large Symmetric Eigenvalue Problems ⋮ A block preconditioned steepest descent method for symmetric eigenvalue problems ⋮ On relaxed filtered Krylov subspace method for non-symmetric eigenvalue problems ⋮ Mesh independence of the generalized Davidson algorithm ⋮ Rayleigh quotient minimization method for symmetric eigenvalue problems ⋮ Approximation of positive semidefinite nonlinear eigenvalue problems

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