DOE OSTI · 3377202
Customized Bayesian optimization for efficient beam tuning at the facility for rare isotope beams
Abstract
Bayesian optimization (BO) has recently emerged as a powerful approach for on-line beam tuning, and it is rapidly gaining adoption across accelerator facilities due to its flexibility and efficiency in handling complex optimization tasks. At the Facility for Rare Isotope Beams, rapid and reliable tuning is essential to support the delivery of diverse ion species. To improve the practicality of BO in this setting, we implemented several enhancements, including scalarized composite objective construction for multicriteria optimization, asynchronous evaluation for better resource utilization, prior-mean-assisted optimization to accelerate convergence, and a local search strategy for rapid completion of the task. We present the details of these methods, discuss challenges-encountered, and share our experience applying them to specific beam-tuning tasks.
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Hwang, Kilean [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000270154318), Zhao, Qiang [Michigan State University, East Lansing, MI (United States)], Zhang, Tong [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000164347386), Maruta, Tomofumi [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000161714339), Plastun, Alexander [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000253511969), Fukushima, Kei [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000271247591), Ostroumov, Peter [Michigan State University, East Lansing, MI (United States)] (ORCID:0000000207193947). 2026-02-17. Customized Bayesian optimization for efficient beam tuning at the facility for rare isotope beams. https://doi.org/10.1103/5hyd-bhpx
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