A block Chebyshev-Davidson method for linear response eigenvalue problems
From MaRDI portal
Publication:503482
DOI10.1007/s10444-016-9455-2zbMath1357.65046OpenAlexW2316170522MaRDI QIDQ503482
Yunkai Zhou, Ren-Cang Li, Zhongming Teng
Publication date: 12 January 2017
Published in: Advances in Computational Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10444-016-9455-2
numerical exampleeigenvalueeigenvectorconvergence rateRitz valuesChebyshev polynomiallinear responseDavidson-type methodupper bound estimator
Related Items (8)
A distributed block Chebyshev-Davidson algorithm for parallel spectral clustering ⋮ A projected preconditioned conjugate gradient method for the linear response eigenvalue problem ⋮ A block Lanczos method for the linear response eigenvalue problem ⋮ Rayleigh-Ritz majorization error bounds for the linear response eigenvalue problem ⋮ Error bounds for approximate deflating subspaces for linear response eigenvalue problems ⋮ Backward perturbation analysis and residual-based error bounds for the linear response eigenvalue problem ⋮ Thick restarting the weighted harmonic Golub-Kahan-Lanczos algorithm for the linear response eigenvalue problem ⋮ Trace minimization method via penalty for linear response eigenvalue problems
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Bounding the spectrum of large Hermitian matrices
- A block Chebyshev-Davidson method with inner-outer restart for large eigenvalue problems
- Chebyshev-filtered subspace iteration method free of sparse diagonalization for solving the Kohn-Sham equation
- A spectral scheme for Kohn-Sham density functional theory of clusters
- Backward perturbation analysis and residual-based error bounds for the linear response eigenvalue problem
- Self-consistent-field calculations using Chebyshev-filtered subspace iteration
- A sharp version of Kahan's theorem on clustered eigenvalues
- Convergence analysis of Lanczos-type methods for the linear response eigenvalue problem
- On the convergence rate of a preconditioned subspace eigensolver
- A Rayleigh-Chebyshev procedure for finding the smallest eigenvalues and associated eigenvectors of large sparse Hermitian matrices
- Matrix Algorithms
- Minimization Principles for the Linear Response Eigenvalue Problem II: Computation
- Reduction of the RPA eigenvalue problem and a generalized Cholesky decomposition for real-symmetric matrices
- Adaptive Projection Subspace Dimension for the Thick-Restart Lanczos Method
- The university of Florida sparse matrix collection
- Vibrational states of nuclei in the random phase approximation
- A Chebyshev–Davidson Algorithm for Large Symmetric Eigenproblems
- Canonical formulation of a generalized coupled dispersionless system
- Convergence Estimates for the Generalized Davidson Method for Symmetric Eigenvalue Problems I: The Preconditioning Aspect
- Convergence Estimates for the Generalized Davidson Method for Symmetric Eigenvalue Problems II: The Subspace Acceleration
- GMRES with Deflated Restarting
- Minimization Principles for the Linear Response Eigenvalue Problem I: Theory
This page was built for publication: A block Chebyshev-Davidson method for linear response eigenvalue problems
