Estimating the condition number of Chebyshev filtered vectors with application to the ChASE library

Fuente: arXiv
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Main Authors: Di Napoli, Edoardo, Wu, Xinzhe
Format: Preprint
Published: 2026
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author Di Napoli, Edoardo
Wu, Xinzhe
author_facet Di Napoli, Edoardo
Wu, Xinzhe
contents Chebyshev filtered subspace iteration is a well-known algorithm for the solution of (symmetric/Hermitian) algebraic eigenproblems which has been implemented in several application codes~\cite{Kronik:2006ff, abinit:2020} or in stand alone libraries~\cite{ChASE}. An essential part of the algorithm is the QR-factorization of the array of vectors spanning the active subspace that have been filtered by the Chebyshev filter. Typically such an array has an a-priori unknown high condition number that directly influences the choice of QR-factorization algorithm. In this work we show how such condition number can be bound from above with precise and inexpensive estimates. We then proceed to use these estimates to implement a mechanism for the choice of QR-factorization in the ChASE library. We show how such mechanism enhance the performance of the library without compromising on its accuracy.
format Preprint
id arxiv_https___arxiv_org_abs_2603_10514
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Estimating the condition number of Chebyshev filtered vectors with application to the ChASE library
Di Napoli, Edoardo
Wu, Xinzhe
Numerical Analysis
Computational Engineering, Finance, and Science
Distributed, Parallel, and Cluster Computing
65f35
Chebyshev filtered subspace iteration is a well-known algorithm for the solution of (symmetric/Hermitian) algebraic eigenproblems which has been implemented in several application codes~\cite{Kronik:2006ff, abinit:2020} or in stand alone libraries~\cite{ChASE}. An essential part of the algorithm is the QR-factorization of the array of vectors spanning the active subspace that have been filtered by the Chebyshev filter. Typically such an array has an a-priori unknown high condition number that directly influences the choice of QR-factorization algorithm. In this work we show how such condition number can be bound from above with precise and inexpensive estimates. We then proceed to use these estimates to implement a mechanism for the choice of QR-factorization in the ChASE library. We show how such mechanism enhance the performance of the library without compromising on its accuracy.
title Estimating the condition number of Chebyshev filtered vectors with application to the ChASE library
topic Numerical Analysis
Computational Engineering, Finance, and Science
Distributed, Parallel, and Cluster Computing
65f35
url https://arxiv.org/abs/2603.10514