Using Artificial Intelligence in Cyclotron Design

Abstract

In cyclotron development, a large number of calculations are required for both individual accelerator systems and particle motion dynamics. Artificial intelligence (AI) can contribute to increasing the speed of calculations, optimizing the codes, and improving the quality of the results. The initial results of using machine learning (ML) for magnetic field formation are presented, and the potential applications of computer vision and AI prospects for optimizing beam motion are analyzed.