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Research PaperResearchia:202601.29152

A reduced basis method for parabolic PDEs based on a space-time least squares formulation

Michael Hinze

Abstract

In this work, we present a POD-greedy reduced basis method for parabolic partial differential equations (PDEs), based on the least squares space-time formulation proposed in [Hinze, Kahle, Stahl, A least-squares space-time approach for parabolic equations, 2023, arXiv:2305.03402] that assumes only minimal regularity. We extend this approach to the parameter-dependent case. The corresponding variational formulation then is based on a parameter-dependent, symmetric, uniformly coercive, and continu...

Submitted: January 29, 2026Subjects: Mathematics; Numerical Analysis

Description / Details

In this work, we present a POD-greedy reduced basis method for parabolic partial differential equations (PDEs), based on the least squares space-time formulation proposed in [Hinze, Kahle, Stahl, A least-squares space-time approach for parabolic equations, 2023, arXiv:2305.03402] that assumes only minimal regularity. We extend this approach to the parameter-dependent case. The corresponding variational formulation then is based on a parameter-dependent, symmetric, uniformly coercive, and continuous bilinear form. We apply the reduced basis method to this formulation, following the well-developed techniques for parameterized coercive problems, as seen e.g. in reduced basis methods for parameterized elliptic PDEs. We present an offline-online decomposition and provide certification with absolute and relative error bounds. The performance of the method is demonstrated using selected numerical examples.


Source: arXiv:2601.21736v1 - http://arxiv.org/abs/2601.21736v1 PDF: https://arxiv.org/pdf/2601.21736v1 Original Link: http://arxiv.org/abs/2601.21736v1

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Date:
Jan 29, 2026
Topic:
Numerical Analysis
Area:
Mathematics
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