Two algorithms for the calculation of extreme eigenvalues of large matrices recently presented are compared. The first one is a modification of the well-known power method with Chebyshev iterations to accelerate convergence and an auxiliary procedure capabable of automatically setting all the extern
A novel algorithm for calculation of the extreme eigenvalues of large Hermitian matrices
โ Scribed by Yuko Okamoto; Humphrey J. Maris
- Publisher
- Elsevier Science
- Year
- 1993
- Tongue
- English
- Weight
- 661 KB
- Volume
- 76
- Category
- Article
- ISSN
- 0010-4655
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โฆ Synopsis
A new fast algorithm for calculating a few maximum (or minimum) eigenvalues and the corresponding eigenvectors of large N x N Hermitian matrices is presented. The method is based on a molecular dynamics algorithm for N coupled harmonic oscillators. The time step for iteration is chosen so that only the normal mode with the maximum eigenvalue grows exponentially. Other eigenvalues and eigenvectors are obtained one by one from the largest eigenvalue by repeating the process in subspaces orthogonal to the previous modes. The characteristics of the algorithm lie in the simplicity, speed (CPU time cx N 2), and memory efficiency (~(N) besides the matrix). The effectiveness of the algorithm is illustrated by calculation of the groundstate and first-excited state energies of the Heisenberg model for an antiferromagnetic chain with N up to 16384.
๐ SIMILAR VOLUMES
Elementary Jacobi Rotations are used as the basic tools to obtain eigenvalues and eigenvectors of arbitrary real symmetric matrices. The proposed algorithm has a complete concurrent structure, that is: every eigenvalueeigenvector pair can be obtained in any order and in an independent way from the r