Oct 9 – 13, 2022
FHNW Campus Brugg-Windisch
Europe/Zurich timezone

Applications of Machine Learning for RF Systems

Oct 10, 2022, 2:55 PM
Aula (Building 3)


Building 3

Oral Low Level RF Workshop 2022 Machine Learning


Jonathan Edelen (RadiaSoft)


The application of machine learning to accelerators has been a dinner table discussion amongst members of the community with an ever increasing list of application spaces. ML has successfully been applied to the improvement of diagnostics, on-line modeling, anomaly detection, and postmortem data analysis. When it comes to accelerator RF systems, machine learning has been of most interest for improving superconducting systems and quench detection / protection systems. Given modern hardware infrastructure, these only scratch the surface of potential applications. This talk will provide an overview of recent applications of machine learning technologies for both slow-controls and real-time systems and highlight some opportunities for the integration of machine learning techniques for the improvement of control systems for RF structures.

Primary authors


Dr Nathan Cook (RadiaSoft LLC) Dr Matthew Kilpatrick (RadiaSoft LLC)

Presentation materials