Efficient Computation of Dominant Eigenvalues Using Adaptive Block Lanczos with Chebyshev Filtering

Fuente: arXiv
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Main Authors: Guide, M. El, Jbilou, K., Lachhab, K.
Format: Preprint
Published: 2025
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author Guide, M. El
Jbilou, K.
Lachhab, K.
author_facet Guide, M. El
Jbilou, K.
Lachhab, K.
contents We present an efficient method for computing dominant eigenvalues of large, nonsymmetric, diagonalizable matrices based on an adaptive block Lanczos algorithm combined with Chebyshev polynomial filtering. The proposed approach improves numerical stability through two key components: (i) the Adaptive Block Lanczos (ABLE) method, which maintains biorthogonality using SVD based stabilization, and (ii) Chebyshev filtering, which enhances spectral separation via iterative polynomial filtering. Numerical experiments on dense and sparse test problems confirm the effectiveness of the ABLE Chebyshev algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2508_08495
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Efficient Computation of Dominant Eigenvalues Using Adaptive Block Lanczos with Chebyshev Filtering
Guide, M. El
Jbilou, K.
Lachhab, K.
Numerical Analysis
F65
We present an efficient method for computing dominant eigenvalues of large, nonsymmetric, diagonalizable matrices based on an adaptive block Lanczos algorithm combined with Chebyshev polynomial filtering. The proposed approach improves numerical stability through two key components: (i) the Adaptive Block Lanczos (ABLE) method, which maintains biorthogonality using SVD based stabilization, and (ii) Chebyshev filtering, which enhances spectral separation via iterative polynomial filtering. Numerical experiments on dense and sparse test problems confirm the effectiveness of the ABLE Chebyshev algorithm.
title Efficient Computation of Dominant Eigenvalues Using Adaptive Block Lanczos with Chebyshev Filtering
topic Numerical Analysis
F65
url https://arxiv.org/abs/2508.08495