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Abstract
In this work, a subspace method is proposed for efficient solution of parametric linear systems with a symmetric and positive definite coefficient matrix of the form I−A(σ). The motivation is to use the method for solution of linear systems appearing when solving parameter dependent elliptic PDEs using the finite element method (FEM). In the proposed method, one first computes a method subspace and then uses it to approximately solve the linear system for any parameter vector. The method subspace is designed in such a way that it contains the j+1-term truncated Neumann series approximation of the solution to desired accuracy for any admissible parameter vector. This allows us to use the best approximation property of subspace methods to show that the subspace solution is at least as accurate as the truncated Neumann series approximation. The performance of the method is demonstrated by numerical examples with the parametric diffusion equation. In these examples, the method yields much smaller errors than anticipated by the Neumann series based error analysis. We study this phenomenon in some special cases.
Original language | English |
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Pages (from-to) | 1-18 |
Number of pages | 18 |
Journal | Computers and Mathematics with Applications |
Volume | 178 |
Early online date | 22 Nov 2024 |
DOIs | |
Publication status | Published - 15 Jan 2025 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Model order reduction
- Neumann series
- Subspace method
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FAME: Flagship of Advanced Mathematics for Sensing, Imaging and Modelling
Hyvönen, N. (Principal investigator)
01/01/2024 → 30/04/2028
Project: Academy of Finland: Other research funding
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-: Centre of Excellence of Inverse Modelling and Imaging
Hannukainen, A. (Principal investigator)
01/05/2020 → 31/12/2022
Project: Academy of Finland: Other research funding