TY - UNPB
T1 - Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
AU - Buchfink, Patrick
AU - Glas, Silke
AU - Haasdonk, Bernard
PY - 2023/12/4
Y1 - 2023/12/4
N2 - 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. Inparticular, we showt hat 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.
AB - 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. Inparticular, we showt hat 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.
U2 - 10.48550/arXiv.2312.00724
DO - 10.48550/arXiv.2312.00724
M3 - Preprint
SP - 1
EP - 11
BT - Approximation Bounds for Model Reduction on Polynomially Mapped Manifolds
PB - ArXiv.org
ER -