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URLhttps://doi.org/10.18429/JACoW-LINAC2024-THPB066
TitleAutonomous beam alignment through quadrupole triplets using Bayesian Algorithm Execution
Authors
  • R. Roussel, D. Kennedy, A. Edelen
    SLAC National Accelerator Laboratory
  • E. Wisniewski
    Illinois Institute of Technology
  • A. Ody
    Argonne National Laboratory
AbstractA common challenge in online accelerator operations is aligning beams through a series of quadrupole magnets, especially when in situ beam position monitors are not present. Accelerator operators generally use a trial-and-error approach to solve this problem by sequentially measuring the centroid deflection of the beam as a function of quadrupole strengths. This is a challenging process that necessitates dedicated effort by operational experts, requiring significant beam time and personnel resources to configure basic accelerator operations. In this work, we use Bayesian Algorithm Execution (BAX) with virtual objectives to autonomously control steering magnets at the Argonne Wakefield Accelerator to center the beam through a quadrupole triplet. This technique uses virtual objectives to reduce the number of measurements needed to converge to an optimal solution, resulting in a turn-key algorithm for finding the optimal steering configuration for a set of accelerator magnets from scratch.
Paperdownload: THPB066.pdf
CiteBibTeX, LaTeX, Text/Word, RIS, EndNote
Conference32nd Linear Accelerator Conference (LINAC2024)
Series
LocationChicago, IL, USA
Date25-30 Aug 2024
PublisherJACoW Publishing, Geneva, Switzerland
Editorial BoardKelly Jaje (ANL), Kip Bishofberger (LANL), Ryan Brody (ANL), Gustavo Bruno (ANL), Jan Chrin (PSI), Cathy Eyberger (ANL), Maggie Montes (SLAC), Denise Skiadopoulos (ANL), Ling Wang (MSU/FRIB), Kent Wootton (ANL)
Online ISBN978-3-95450-219-6
Online ISSN2226-0366
Received20 August 2024
Revised29 August 2024
Accepted30 August 2024
Issued23 October 2024
DOI10.18429/JACoW-LINAC2024-THPB066
Pages765-767