Machine-learning-assisted beam tuning at FRIB

Facility for Rare Isotope Beams (FRIB) requires diverse primary ion species beams to produce rare isotopes. The beam tuning time can be reduced by employing Machine Learning (ML) techniques. In this presentation, we aim to explore practical perspectives on shortening beam tuning time. Specifically, we discuss customization of Bayesian Optimization for maximum beam time utilization, and virtual diagnostics that are currently under development.