Proton Beam

Proton beams are charged particle beams used in diverse applications, from cancer therapy to fundamental physics research, with primary objectives focused on precise control and optimization of beam properties. Current research emphasizes the development of advanced machine learning models, including deep reinforcement learning, Bayesian optimization, and recurrent neural networks (like LSTMs), to automate beam control, predict faults, and optimize treatment planning, particularly in proton therapy. These advancements promise significant improvements in accelerator efficiency, treatment accuracy, and the ability to study complex beam dynamics, ultimately impacting fields ranging from medicine to materials science.