On the rational approximation of Markov ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
On the rational approximation of Markov functions,with applications to the computation of Markovfunctions of Toeplitz matrices
Auteur(s) :
Beckermann, Bernhard [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Bisch, Joanna [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Luce, Robert [Auteur]
Gurobi Optimization
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Bisch, Joanna [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Luce, Robert [Auteur]
Gurobi Optimization
Titre de la revue :
Numerical Algorithms
Pagination :
109-144
Éditeur :
Springer Verlag
Date de publication :
2022
ISSN :
1017-1398
Mot(s)-clé(s) en anglais :
positive Thiele continued fractions
rational interpolation
Markov function
Toeplitz matrices
matrix function
rational interpolation
Markov function
Toeplitz matrices
matrix function
Discipline(s) HAL :
Mathématiques [math]/Analyse numérique [math.NA]
Résumé en anglais : [en]
We investigate the problem of approximating the matrix function $f(A)$ by $r(A)$, with $f$ a Markov function, $r$ a rational interpolant of $f$, and $A$ a symmetric Toeplitz matrix. In a first step, we obtain a new upper ...
Lire la suite >We investigate the problem of approximating the matrix function $f(A)$ by $r(A)$, with $f$ a Markov function, $r$ a rational interpolant of $f$, and $A$ a symmetric Toeplitz matrix. In a first step, we obtain a new upper bound for the relative interpolation error $1-r/f$ on the spectral interval of $A$. By minimizing this upper bound over all interpolation points, we obtain a new, simple and sharp a priori bound for the relative interpolation error. We then consider three different approaches of representing and computing the rational interpolant $r$. Theoretical and numerical evidence is given that any of these methods for a scalar argument allows to achieve high precision, even in the presence of finite precision arithmetic. We finally investigate the problem of efficiently evaluating $r(A)$, where it turns out that the relative error for a matrix argument is only small if we use a partial fraction decomposition for $r$ following Antoulas and Mayo. An important role is played by a new stopping criterion which ensures to automatically find the degree of $r$ leading to a small error, even in presence of finite precision arithmetic.Lire moins >
Lire la suite >We investigate the problem of approximating the matrix function $f(A)$ by $r(A)$, with $f$ a Markov function, $r$ a rational interpolant of $f$, and $A$ a symmetric Toeplitz matrix. In a first step, we obtain a new upper bound for the relative interpolation error $1-r/f$ on the spectral interval of $A$. By minimizing this upper bound over all interpolation points, we obtain a new, simple and sharp a priori bound for the relative interpolation error. We then consider three different approaches of representing and computing the rational interpolant $r$. Theoretical and numerical evidence is given that any of these methods for a scalar argument allows to achieve high precision, even in the presence of finite precision arithmetic. We finally investigate the problem of efficiently evaluating $r(A)$, where it turns out that the relative error for a matrix argument is only small if we use a partial fraction decomposition for $r$ following Antoulas and Mayo. An important role is played by a new stopping criterion which ensures to automatically find the degree of $r$ leading to a small error, even in presence of finite precision arithmetic.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
Fichiers
- document
- Accès libre
- Accéder au document
- BBL_revised.pdf
- Accès libre
- Accéder au document
- 2106.05098
- Accès libre
- Accéder au document