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Beam halo losses reduction with simulation constrained Bayesian Optimization

https://repo.qst.go.jp/records/2001994
https://repo.qst.go.jp/records/2001994
33664109-9404-489d-ae4a-b785526c60a6
アイテムタイプ 会議発表論文 / Conference Paper(1)
公開日 2025-11-04
タイトル
タイトル Beam halo losses reduction with simulation constrained Bayesian Optimization
言語 en
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_5794
資源タイプ conference paper
アクセス権
アクセス権 metadata only access
アクセス権URI http://purl.org/coar/access_right/c_14cb
著者 Hyun Jibong

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Hyun Jibong

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Andrea De Franco

× Andrea De Franco

Andrea De Franco

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Akagi Tomoya

× Akagi Tomoya

Akagi Tomoya

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Hirosawa Koki

× Hirosawa Koki

Hirosawa Koki

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Kondo Keitaro

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Kondo Keitaro

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Masuda Kai

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Masuda Kai

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Mizuno Akihiko

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Mizuno Akihiko

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Carin Yann

× Carin Yann

Carin Yann

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Fabio Cismondi

× Fabio Cismondi

Fabio Cismondi

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Francesco Scantamburlo

× Francesco Scantamburlo

Francesco Scantamburlo

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Gex Dominique

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Gex Dominique

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Herve Dzitko

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Herve Dzitko

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内容記述タイプ Abstract
内容記述 The Linear IFMIF Prototype Accelerator (LIPAc) is designedto demonstrate continuous wave (CW) accelerationof a 125 mA deuteron beam up to 9 MeV using a radiofrequencyquadrupole (RFQ) and a superconducting radiofrequency(SRF) linac. Prior to SRF linac installation, beamcommissioning was conducted with a 5 MeV deuteron beam.Attempts to increase the duty cycle revealed a significant risein vacuum pressure, as detected by sensors, thus limitingthe operational duty cycle to about 3%. Simulation studiesindicated that the pressure increase was likely attributable tobeam halo formation. To address this issue, Bayesian optimizationwas applied to the beam optics—specifically, fourquadrupole magnets and four steerers—with the objectiveof minimizing halo-induced losses by monitoring vacuumpressure while constraining core beam losses. This approachsuccessfully reduced the sector vacuum pressure by approximately67%. Further simulations verified that beam haloformation driven by nonlinear space-charge forces was effectivelymitigated by relaxing beam focusing in specificregions, consistent with theoretical predictions. As a result,the duty cycle was increased to 8.7%. These findings demonstratethat machine learning techniques, such as Bayesianoptimization, can effectively support beam optics tuningin high-current accelerator systems. This paper presents acomparative analysis of the beam optics before and afteroptimization, highlighting the improvements in halo suppression.
書誌情報 Proceedings of the 71st ICFA Adv. Beam Dyn. Workshop High-Intensity High-Bright. Hadron Beams

p. 110-115, 発行日 2025-11
ISSN
収録物識別子タイプ ISSN
収録物識別子 2673-5571
DOI
識別子タイプ DOI
関連識別子 10.18429/JACoW-HB2025-WEIBC01
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