Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/104912
Title: Test of machine learning at the CERN LINAC4
Authors: Kain, Verena
Bruchon, Niky
Hirlander, Simon
Madysa, Nico
Vojskovic, Isabella
Skowronski, Piotr
Valentino, Gianluca
Keywords: Machine Learning
Large Hadron Collider (France and Switzerland)
Linear accelerators
Issue Date: 2021
Publisher: JACoW Publishing
Citation: Kain, V., Madysa, N., Skowronski, P. K., Vojskovic, I., Bruchon, N., Hirlaender, S. & Valentino, G. (2021). Test of machine learning at the CERN LINAC4. 64th ICFA ABDW on High-Intensity and High-Brightness Hadron Beams, Batavia. 181-185.
Abstract: The CERN H− linear accelerator, LINAC4, served as a test bed for advanced algorithms during the CERN Long Shutdown 2 in the years 2019/20. One of the main goals was to show that reinforcement learning with all its benefits can be used as a replacement for numerical optimization and as a complement to classical control in the accelerator control context. Many of the algorithms used were prepared before- hand at the electron line of the AWAKE facility to make the best use of the limited time available at LINAC4. An overview of the algorithms and concepts tested at LINAC4 and AWAKE will be given and the results discussed.
URI: https://www.um.edu.mt/library/oar/handle/123456789/104912
Appears in Collections:Scholarly Works - FacICTCCE

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