Linear combination of Lanczos vectors: A storage-efficient algorithm for sparse matrix eigenvector computations
✍ Scribed by T. Koslowski; W. Von Niessen
- Publisher
- John Wiley and Sons
- Year
- 1993
- Tongue
- English
- Weight
- 634 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0192-8651
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✦ Synopsis
We present a storage-efficient and robust algorithm for the computation of eigenvectors of large sparse symmetrical matrices using a Lanczos scheme. The algorithm is based upon a linear combination of Lanczos vectors (LCLV) with a variable iteration depth. A simple method is given to determine the iteration depth before the eigenvector computation is performed. Test calculations are reported for tight-binding models of ordered and disordered 2-D systems. The algorithm turns out to be reliable if an eigenvector residual less than 10 -J is required. We report benchmarks for various computers. Possible fields of application are discussed.