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Numerical experiments to "High-frequency wave-propagation: error analysis for analytical and numerical approximations"

Baumstark, Julian 1,2
1 Institut für Angewandte und Numerische Mathematik (IANM), Karlsruher Institut für Technologie (KIT)
2 Sonderforschungsbereich 1173 (SFB 1173), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

This code has been used for the numerical experiments in the thesis "High-frequency wave-propagation: error analysis for analytical and numerical approximations" by Julian Baumstark, see https://www.doi.org/10.5445/IR/1000149719.


Zugehörige Institution(en) am KIT Institut für Angewandte und Numerische Mathematik (IANM)
Sonderforschungsbereich 1173 (SFB 1173)
Publikationstyp Forschungsdaten
Publikationsdatum 19.08.2022
Erstellungsdatum 16.08.2022
Identifikator DOI: 10.5445/IR/1000149721
KITopen-ID: 1000149721
Lizenz Creative Commons Namensnennung – Weitergabe unter gleichen Bedingungen 4.0 International
Liesmich

The scripts are intended to reproduce the figures from the thesis

"High-frequency wave-propagation: error analysis for analytical and numerical approximations"

by Julian Baumstark

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Requirements

The codes are tested on

Ubuntu 18.04 LTS

with

Matlab R2020a 

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Generation of figures

With this code Figures
3.1, 3.2, 4.1, 4.2, 4.3, 5.1, and 5.2
can be generated.

The calculation of the data for Figure 4.1, 4.2, 4.3, 5.1 and 5.2 takes a few days and requires a storage space of about 140 GB.

Figure 3.1 and 3.2

In order to obtain Figure 3.X (X=1 or 2) run the command

visualize_Fig3X.m

in Matlab.

Figure 4.1, 4.2 and 4.3

Open folder "Chapter_4" in Matlab.
In order to obtain Figure 4.X (X=1 or 2 or 3) first run the command

kleingordon_analytical_approx.m 

to compute the data. Then, run

visualize_Fig4X.m

in Matlab.

Figure 5.1 and 5.2

Open folder "Chapter_5" in Matlab.
In order to obtain Figure 5.X (X=1 or 2) first run the command

kleingordon_numerical_approx.m 

to compute the data. Then, run

visualize_Fig5X.m

in Matlab.

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