GFA Accelerator Seminars

Comprehensive Analysis of Micro-Bunching Instabilities using Machine Learning

by Mr Tobias Boltz (KIT)

Europe/Zurich
Description
The operation with short electron bunches at synchrotron light sources leads to the formation of micro-structures within the bunches, which increase the emitted coherent synchrotron radiation power. The dynamic changes of these micro-structures can indirectly be studied by measuring the resulting fluctuations of the emitted radiation power. Such fluctuations have been observed at various synchrotron light sources including ANKA, KIT. Although several techniques exist to measure the electron distribution within the bunch, the small scale of the micro-structures makes their direct observation quite challenging. Therefore, the longitudinal dynamics have been simulated using the newly developed simulation code Inovesa. As this quickly accumulates to large data sets, machine learning techniques are employed in order to identify the dominant micro-structures in the longitudinal bunch profiles. Subsequently, these findings are used to extensively study the characteristics and dynamics of the micro-structures, and to investigate their correlation to the emitted coherent synchrotron radiation. Contact: Rasmus Ischebeck, 5535
Slides