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On Linear Models for Discrete Operator Inference in Time Dependent Problems

Yannis Schumann, Philipp Neumann: Chair for High Performance Computing, Helmut-Schmidt University Hamburg, Germany

This repository contains all source code associated with our manuscript On Linear Models for Discrete Operator Inference in Time Dependent Problems, submitted to the conference proceedings of the 8th European Seminar on Computing (ESCO 2022) in JCAM.

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All code is provided to the reader as notebook file (.ipynb). The following table describes the respective contents of each of the files.

File Name Content
MostStableStencilESCO.ipynb All Code associated with section 4.1.1:
- Table 1
- Analysis of the importance of parameters $\Delta x$, $\Delta t$
- Analysis of the cardinality of the set of initial variables
- Analysis of the order of the selected schemes
MinimalStencilESCO.ipynb All Code associated with section 4.1.2:
- Table 2
VariableCoefficientsESCO.ipynb All Code associated with section 4.2:
- Table 3
-Figure 3
-Analysis of the choice for the windows size $\Delta x$