Generalizations of Davidson's method for computing eigenvalues of sparse symmetric matrices
SIAM Journal on Scientific and Statistical Computing
A Jacobi--Davidson Iteration Method for Linear EigenvalueProblems
SIAM Journal on Matrix Analysis and Applications
The symmetric eigenvalue problem
The symmetric eigenvalue problem
A parallel Davidson-type algorithm for several eigenvalues
Journal of Computational Physics
LAPACK Users' guide (third ed.)
LAPACK Users' guide (third ed.)
Thick-Restart Lanczos Method for Large Symmetric Eigenvalue Problems
SIAM Journal on Matrix Analysis and Applications
Lanczos Algorithms for Large Symmetric Eigenvalue Computations, Vol. 1
Lanczos Algorithms for Large Symmetric Eigenvalue Computations, Vol. 1
A Chebyshev-Davidson Algorithm for Large Symmetric Eigenproblems
SIAM Journal on Matrix Analysis and Applications
Efficient solution of the Schroedinger-Poisson equations in layered semiconductor devices
Journal of Computational Physics
Inexact Inverse Subspace Iteration with Preconditioning Applied to Non-Hermitian Eigenvalue Problems
SIAM Journal on Matrix Analysis and Applications
| Hi-index | 31.45 |
A procedure is presented for finding a number of the smallest eigenvalues and their associated eigenvectors of large sparse Hermitian matrices. The procedure, a modification of an inverse subspace iteration procedure, uses adaptively determined Chebyshev polynomials to approximate the required application of the inverse operator on the subspace. The method is robust, converges with acceptable rapidity, and can easily handle operators with eigenvalues of multiplicity greater than one. Numerical results are shown that demonstrate the utility of the procedure.