Automated beam tuning of the TRIUMF ISAC facility

Modern heavy ion accelerators have become more complex, with greater variability in energy, isotope selection, and A/q ratios. In response, TRIUMF has launched a program focused on automating beam tuning and delivery across its accelerator complex. This initiative includes high-level applications, model-based tuning of the accelerator, and the integration of machine learning tools. For example, Bayesian optimization is used to correct beam orbits within the TRIUMF accelerators. This presentation will provide an overview of the program's progress and highlight some exciting new results achieved over the past two years.