Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
Numerical Analysis
2023-12-04 v1 Numerical Analysis
Abstract
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.
Cite
@article{arxiv.2312.00724,
title = {Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds},
author = {Patrick Buchfink and Silke Glas and Bernard Haasdonk},
journal= {arXiv preprint arXiv:2312.00724},
year = {2023}
}
Comments
11 pages, 1 figure