| Issue |
EPJ Web Conf.
Volume 287, 2023
EOS Annual Meeting (EOSAM 2023)
|
|
|---|---|---|
| Article Number | 13014 | |
| Number of page(s) | 2 | |
| Section | Focused Sessions (FS) 4- Machine Learning and Photonic Artificial Intelligence / Optical Neural Networks and Neuromorphic Computing | |
| DOI | https://doi.org/10.1051/epjconf/202328713014 | |
| Published online | 18 October 2023 | |
https://doi.org/10.1051/epjconf/202328713014
Machine Learning for automatic pointing alignment and spatial beam filtering
1 Institute of Product and Production Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Klosterzelgstrasse 2, CH-5210 Windisch, Switzerland
2 Inspire AG, Physikstrasse 3, CH-8092 Zürich, Switzerland
* Corresponding author: bojan.resan@fhnw.ch
Published online: 18 October 2023
Constraint Bayesian optimization approach is used to optimize the beam pointing and spatial filtering of a laser beam using the capillary transmission and the output beam profile, as the optimization criteria. We have demonstrated that the developed method was able to robustly find the optimal laser parameters and it will be implemented in the SwissFEL UV photocathode laser in the future.
© The Authors, published by EDP Sciences, 2023
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