A priori error analysis for one-parameter Lagrange and POD reduced order methods
Abstract
This work deals with the numerical solution of parametric linear elliptic partial differential equations using the finite element method for spatial discretization and a proper orthogonal decomposition or Lagrange subspace method based ROM for treating the parameter dependency. We study a simple one-parameter model problem and prove an error estimate for these ROMs as a function of the snapshot point set. Sub-exponential convergence with respect to the number of snapshot points is established under very mild assumptions on the point set. Exponential convergence is proven for structured point sets. In contrast to existing error analysis of Lagrange subspace methods, our estimates are not based on interpolation or perturbation arguments. Rather, we define a new approximation operator from the snapshot subspace and prove error and stability estimates for it.
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BibTeX
@misc{hannukainen2026priori,
title = {{A priori error analysis for one-parameter Lagrange and POD reduced order methods}},
author = {Antti Hannukainen and Vigdis Toresen},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.34865},
eprint = {2609.34865},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.34865},
}
RIS
TY - UNPB
TI - A priori error analysis for one-parameter Lagrange and POD reduced order methods
AU - Antti Hannukainen
AU - Vigdis Toresen
PY - 2026
DA - 2026/09/28
PB - arXiv
DO - 10.48550/arxiv.2609.34865
UR - https://arxiv.org/abs/2609.34865
AB - This work deals with the numerical solution of parametric linear elliptic partial differential equations using the finite element method for spatial discretization and a proper orthogonal decomposition or Lagrange subspace method based ROM for treating the parameter dependency. We study a simple one-parameter model problem and prove an error estimate for these ROMs as a function of the snapshot point set. Sub-exponential convergence with respect to the number of snapshot points is established under very mild assumptions on the point set. Exponential convergence is proven for structured point sets. In contrast to existing error analysis of Lagrange subspace methods, our estimates are not based on interpolation or perturbation arguments. Rather, we define a new approximation operator from the snapshot subspace and prove error and stability estimates for it.
ER -