Turbulence measurements in magnetized plasma with Short Pulse Reflectometry

This internship was devoted to investigation of turbulence characteristics in the TCV tokamak
using Short Pulse Reflectometry diagnostic and Machine Learning approach, focusing on
Trapped Electron Mode (TEM) instabilities and their impact on radial transport. A 1D model
initially provided insights, but a 2D model was developed to better account for curvature,
incidence angle, and scattering effects. Using extensive CUWA code simulations, datasets were
generated for both Gaussian and power spectrum turbulence structures accounting for various
simulation parameters like the position of the cut-off the structures of turbulences. The 2D
model achieved R2 scores of 0.92 for Gaussian and 0.89 for power spectrum tests, outperforming
deeper neural networks. It effectively managed non-linear effects, delay characteristics, and
cut-off layer shifts.

I wish to thank Dr. Oleg Krutkin for his supervision, the instructive discussions for
building the final model, and for the careful reading of the manuscript. Many thanks to
CINECA clusters and their support during the course of this work, one of the top five world
supercomputers.

This project was carried out within the framework of a master internship under the
supervision of the Ecole Normale Supérieure through Pr. Jean-François Allemand, who showed
great interest in this project. This project was supported by The EUROfusion Consortium and
received funding from the FUSEnet organization, the EPFL exchange program, and the Swiss
Plasma Center. Finally, I need to thank the SPC community for their kindness in listening to
my issues and considerations and for the positive atmosphere that prevails in the center