Local Convergence Behavior of Extended Local Optimal Block Preconditioned Conjugate Gradient Method for Computing Eigenvalues of Hermitian Matrices

ABSTRACT This paper provides a comprehensive and detailed analysis of the local convergence behavior of an extended variation of the locally optimal preconditioned conjugate gradient method (LOBPCG) for computing the extreme eigenvalues of a Hermitian matrix. The convergence rates derived in this work are either obtained for the first time or sharper than those previously established, including those in Ovtchinnikov's work ( SIAM J. Numer. Anal. , 46(5):2567–2592, 2008). The study also extends to generalized problems, including Hermitian matrix polynomials that admit an extended form of the Rayleigh quotient. The new approach used to obtain these rates may also serve as a valuable tool for the convergence analysis of other gradient‐type optimization methods.

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Publication Details

Journal
Numerical Linear Algebra with Applications
Published
2026-04-01
DOI
https://doi.org/10.1002/nla.70075
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Local Convergence Behavior of Extended Local Optimal Block Preconditioned Conjugate Gradient Method for Computing Eigenvalues of Hermitian Matrices

Xin Liang
Numerical Linear Algebra with Applications
Matrix Theory and Algorithms
article

Local Convergence Behavior of Extended Local Optimal Block Preconditioned Conjugate Gradient Method for Computing Eigenvalues of Hermitian Matrices

Xin Liang
article en

Abstract

ABSTRACT This paper provides a comprehensive and detailed analysis of the local convergence behavior of an extended variation of the locally optimal preconditioned conjugate gradient method (LOBPCG) for computing the extreme eigenvalues of a Hermitian matrix. The convergence rates derived in this work are either obtained for the first time or sharper than those previously established, including those in Ovtchinnikov's work ( SIAM J. Numer. Anal. , 46(5):2567–2592, 2008). The study also extends to generalized problems, including Hermitian matrix polynomials that admit an extended form of the Rayleigh quotient. The new approach used to obtain these rates may also serve as a valuable tool for the convergence analysis of other gradient‐type optimization methods.

Numerical Linear Algebra with ApplicationsVol. 33(2)
Beijing Institute of Mathematical Sciences and Applications, Tsinghua University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 97%
Matrix Theory and Algorithms
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