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Workshop: Machine Learning and the Physical Sciences

Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows

Anna Willmann · Jurjen Pieter Couperus Cabada─č · Yen-Yu Chang · Richard Pausch · Amin Ghaith · Alexander Debus · Arie Irman · Michael Bussmann · Ulrich Schramm · Nico Hoffmann


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.

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