Speaker
Description
Implementing automated tuning techniques has been a priority at TRIUMF, driven by the need to support the significant increase in RIB availability expected with the new Advanced Rare Isotope Laboratory (ARIEL). This efficiency boost will facilitate a broad spectrum of research in nuclear, particle, and astrophysics. This work outlines the shift from manual tuning to an automated approach for optimizing beamline transport. We utilize the predictive digital twin, Model Coupled Accelerator Tuning (MCAT), to compute transport and accelerated beam tunes, while Bayesian Optimization for Ion Steering (BOIS) handles beam orbit correction. BOIS treats steering as a black-box optimization problem, maximizing beam current based solely on direct measurement. By combining MCAT and BOIS, this method offers a more efficient, physics-grounded tuning process, with potential applications for facilities beyond TRIUMF.
Funding Agency
NSERC
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