Error Formulas for Block Rational Krylov Approximations of Matrix Functions

Abstract. This paper investigates explicit expressions for the error associated with the block rational Krylov approximation of matrix functions. Two formulas are proposed, both derived from characterizations of the residual of the block full orthogonal method. The first formula employs a block generalization of the residual polynomial, while the second leverages the block collinearity of the residuals. A posteriori error bounds based on the knowledge of spectral information of the argument are derived and tested on a set of examples. Notably, both error formulas and their corresponding upper bounds do not require the use of quadratures for their practical evaluation.

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Publication Details

Journal
SIAM Journal on Numerical Analysis
Published
2026-08-20
DOI
https://doi.org/10.1137/25m1751815
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Error Formulas for Block Rational Krylov Approximations of Matrix Functions

Stefano Massei, Leonardo Robol
SIAM Journal on Numerical Analysis
Matrix Theory and Algorithms
article

Error Formulas for Block Rational Krylov Approximations of Matrix Functions

Stefano Massei, Leonardo Robol
article en

Abstract

Abstract. This paper investigates explicit expressions for the error associated with the block rational Krylov approximation of matrix functions. Two formulas are proposed, both derived from characterizations of the residual of the block full orthogonal method. The first formula employs a block generalization of the residual polynomial, while the second leverages the block collinearity of the residuals. A posteriori error bounds based on the knowledge of spectral information of the argument are derived and tested on a set of examples. Notably, both error formulas and their corresponding upper bounds do not require the use of quadratures for their practical evaluation.

SIAM Journal on Numerical AnalysisVol. 64(4)
University of Pisa (IT)
Istituto Nazionale di Alta Matematica "Francesco Severi", Ministero dell’Istruzione, dell’Università e della Ricerca, Università di Pisa, Gruppo Nazionale per il Calcolo Scientifico
Openalex Percentile: Top 96%
Matrix Theory and Algorithms
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