Strategy for Bayesian Optimized Beam Steering at TRIUMF-ISAC's MEBT and HEBT Beamlines

2025/05/13 by Hassan, O., Shelbaya, O., Fedorko, W. +2 · 1 citation
#Accelerator Physics (physics.acc-ph) #Applied Physics (physics.app-ph) #FOS: Physical sciences

paper · doi:10.48550/arxiv.2505.08767

Abstract

In preparation for operation of multiple Rare Isotope Beams (RIBs) when the Advanced Rare Isotope Laboratory (ARIEL) becomes operational, TRIUMF embarked on a program of advanced beam tuning applications and machine learning tools. The strategy for operationalizing Bayesian Optimization for beam steering purposes is being developed. A previously reported centroid correction algorithm is used to tune accelerated charged particle beams at TRIUMF's ISAC postaccelerator facility. We present findings and results from multiple machine development experiments conducted between October and November 2024, as part of a pivot toward semi-automated machine tuning methods. These findings were instrumental in shaping the tuning strategy for the medium and high energy beam transport (MEBT, HEBT) lines at ISAC, by sequentially optimizing sub-sections of the beamlines.

Citations

• A Tutorial on Bayesian Optimization

Cited by

• Matching Optimization for TRIUMF's Rare Isotope Linac

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