Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds

For projection-based linear-subspace model order reduction (MOR), it is well known that the Kolmogorov $n$-width describes the best-possible error for a reduced order model (ROM) of size $n$. In this paper, we provide approximation bounds for ROMs on polynomially mapped manifolds. In particular, we...

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Main Authors: Buchfink, Patrick, Glas, Silke, Haasdonk, Bernard
Format: Article
Language:English
Published: Académie des sciences 2024-12-01
Series:Comptes Rendus. Mathématique
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Online Access:https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.632/
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author Buchfink, Patrick
Glas, Silke
Haasdonk, Bernard
author_facet Buchfink, Patrick
Glas, Silke
Haasdonk, Bernard
author_sort Buchfink, Patrick
collection DOAJ
description For projection-based linear-subspace model order reduction (MOR), it is well known that the Kolmogorov $n$-width describes the best-possible error for a reduced order model (ROM) of size $n$. In this paper, we provide approximation bounds for ROMs on polynomially mapped manifolds. In particular, we show that the approximation bounds depend on the polynomial degree $p$ of the mapping function as well as on the linear Kolmogorov $n$-width for the underlying problem. This results in a Kolmogorov $(n,p)$-width, which describes a lower bound for the best-possible error for a ROM on polynomially mapped manifolds of polynomial degree $p$ and reduced size $n$.
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spelling doaj-art-f09aa9efd6ea49c6a9e07db702060c8f2025-02-07T11:27:00ZengAcadémie des sciencesComptes Rendus. Mathématique1778-35692024-12-01362G131881189110.5802/crmath.63210.5802/crmath.632Approximation Bounds for Model Reduction on Polynomially Mapped ManifoldsBuchfink, Patrick0Glas, Silke1https://orcid.org/0000-0003-3274-1615Haasdonk, Bernard2Institute of Applied Analysis and Numerical Simulation, University of Stuttgart, Pfaffenwaldring 57, 70569 Stuttgart, Germany; University of Twente, Department of Applied Mathematics, P.O. Box 217, 7500 AE Enschede, The NetherlandsUniversity of Twente, Department of Applied Mathematics, P.O. Box 217, 7500 AE Enschede, The NetherlandsInstitute of Applied Analysis and Numerical Simulation, University of Stuttgart, Pfaffenwaldring 57, 70569 Stuttgart, GermanyFor projection-based linear-subspace model order reduction (MOR), it is well known that the Kolmogorov $n$-width describes the best-possible error for a reduced order model (ROM) of size $n$. In this paper, we provide approximation bounds for ROMs on polynomially mapped manifolds. In particular, we show that the approximation bounds depend on the polynomial degree $p$ of the mapping function as well as on the linear Kolmogorov $n$-width for the underlying problem. This results in a Kolmogorov $(n,p)$-width, which describes a lower bound for the best-possible error for a ROM on polynomially mapped manifolds of polynomial degree $p$ and reduced size $n$.https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.632/Model Order Reductionnonlinear manifoldspolynomial mappingspolynomial $(n,p)$-widths
spellingShingle Buchfink, Patrick
Glas, Silke
Haasdonk, Bernard
Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
Comptes Rendus. Mathématique
Model Order Reduction
nonlinear manifolds
polynomial mappings
polynomial $(n,p)$-widths
title Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
title_full Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
title_fullStr Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
title_full_unstemmed Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
title_short Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
title_sort approximation bounds for model reduction on polynomially mapped manifolds
topic Model Order Reduction
nonlinear manifolds
polynomial mappings
polynomial $(n,p)$-widths
url https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.632/
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