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RIS citation export for TUEC4: Test of Machine Learning at the CERN LINAC4

TY  - CONF
AU  - Kain, V.
AU  - Bruchon, N.
AU  - Hirlaender, S.
AU  - Madysa, N.
AU  - Skowroński, P.K.
AU  - Valentino, G.
AU  - Vojskovic, I.
ED  - Gianfelice, Eliana
ED  - Nagaitsev, Sergei
ED  - Kim, Dong Eon
ED  - Marx, Michaela
ED  - Schaa, Volker R. W.
TI  - Test of Machine Learning at the CERN LINAC4
J2  - Proc. of HB2021, Batavia, IL, USA, 04-08 October 2021
CY  - Batavia, IL, USA
T2  - ICFA ABDW on High-Intensity and High-Brightness Hadron Beams
T3  - 64
LA  - english
AB  - 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 beforehand 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.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 181
EP  - 185
KW  - controls
KW  - linac
KW  - electron
KW  - target
KW  - network
DA  - 2022/04
PY  - 2022
SN  - 2673-5571
SN  - 978-3-95450-225-7
DO  - doi:10.18429/JACoW-HB2021-TUEC4
UR  - https://jacow.org/hb2021/papers/tuec4.pdf
ER  -