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'Journal of Accelerator Conferences Website' (JACoW) is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.

https://doi.org/10.18429/JACoW-FLS2023-TH3D3
Title How Can Machine Learning Help Future Light Sources?
Authors
  • A. Santamaria Garcia, E. Bründermann, M. Caselle, A.-S. Müller, L. Scomparin, C. Xu
    KIT, Karlsruhe, Germany
  • G. De Carne
    Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen, Germany
Abstract Machine learning (ML) is one of the key technologies that can considerably extend and advance the capabilities of particle accelerators and needs to be included in their future design. Future light sources aim to reach unprecedented beam brightness and radiation coherence, which require challenging beam sizes and accelerating gradients. The sensitive designs and complex operation modes that arise from such demands will impact the beam availability and flexibility for the users, and can render future accelerators inefficient. ML brings a paradigm shift that can re-define how accelerators are operated. In this contribution we introduce the vision of ML-driven facilities for future accelerators, address some challenges of future light sources, and show an example of how such methods can be used to control beam instabilities.
Paper download TH3D3.PDF [0.402 MB / 8 pages]
Slides download TH3D3_TALK.PDF [5.398 MB]
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Conference FLS2023
Series ICFA Advanced Beam Dynamics Workshop (67th)
Location Luzern, Switzerland
Date 27 August-01 September 2023
Publisher JACoW Publishing, Geneva, Switzerland
Editorial Board Hans-Heinrich Braun (PSI, Villigen, Switzerland); Jan Chrin (PSI, Villigen, Switzerland); Romain Ganter (PSI, Villigen, Switzerland); Nicole Hiller (PSI, Villigen, Switzerland); Volker RW Schaa (GSI, Darmstadt, Germany)
Online ISBN 978-3-95450-224-0
Online ISSN 2673-7035
Received 23 August 2023
Revised 25 August 2023
Accepted 31 August 2023
Issued 02 December 2023
DOI doi:10.18429/JACoW-FLS2023-TH3D3
Pages 249-256
Copyright
Creative Commons CC logoPublished by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI.