Abstract

Particle accelerators are essential for scientific research across many fields, including physics, material science, and medical applications and have enabled many significant scientific discoveries, such as the discovery of the Higgs boson and the development of advanced cancer therapies. However, the challenges for commissioning and operating these highly complex machines, and the ever increasing demands on experimental requirements, calls for new methods for analysis, comparison and optimization as they're given by artificial intelligence. The lecture will begin with a brief overview of particle accelerators, followed by an introduction to specific machine learning methods relevant to the operation of particle accelerators. Finally, there will be application examples that demonstrate successful uses of machine learning.