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

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Hauptverfasser: Hassan, O., Shelbaya, O., Fedorko, W., Planche, T., Kester, O.
Format: Preprint
Veröffentlicht: 2025
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author Hassan, O.
Shelbaya, O.
Fedorko, W.
Planche, T.
Kester, O.
author_facet Hassan, O.
Shelbaya, O.
Fedorko, W.
Planche, T.
Kester, O.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2505_08767
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Strategy for Bayesian Optimized Beam Steering at TRIUMF-ISAC's MEBT and HEBT Beamlines
Hassan, O.
Shelbaya, O.
Fedorko, W.
Planche, T.
Kester, O.
Accelerator Physics
Applied Physics
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.
title Strategy for Bayesian Optimized Beam Steering at TRIUMF-ISAC's MEBT and HEBT Beamlines
topic Accelerator Physics
Applied Physics
url https://arxiv.org/abs/2505.08767