SMuK 2023 – wissenschaftliches Programm
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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz
AKPIK 1: Poster
AKPIK 1.1: Poster
Montag, 20. März 2023, 16:00–18:00, HSZ OG2
Learning Electron Bunch Distribution along a Beamline by Normalising Flows — •Anna Willmann1, Jurjen Couperus Cabadağ1, Yen-Yu Chang1, Richard Pausch1, Amin Ghaith1, Alexander Debus1, Arie Irman1, Michael Bussmann2, Ulrich Schramm1,3, and Nico Hoffmann1 — 1Helmholtz Zentrum Dresden-Rossendorf, Dresden, Germany — 2Center for Advanced Systems Understanding, Görlitz, Germany — 3Technische Universität Dresden, Germany
Understanding and control of Laser-driven Free Electron Lasers remain to be difficult problems that require highly intensive experimental and theoretical research. The gap between simulated and experimentally collected data might complicate studies and interpretation of obtained results. In this work we developed a deep learning based surrogate that could help to fill in this gap. We introduce a surrogate model based on normalising flows for conditional phase-space representation of electron clouds in a FEL beamline. Achieved results let us discuss further benefits and limitations in exploitability of the models to gain deeper understanding of fundamental processes within a beamline.