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RIS citation export for TUPOTK061: Prospects to Apply Machine Learning to Optimize the Operation of the Crystal Collimation System at the LHC

TY  - CONF
AU  - D’Andrea, M.
AU  - Azzopardi, G.
AU  - Di Castro, M.
AU  - Matheson, E.
AU  - Mirarchi, D.
AU  - Redaelli, S.
AU  - Ricci, G.
AU  - Valentino, G.
ED  - Zimmermann, Frank
ED  - Tanaka, Hitoshi
ED  - Sudmuang, Porntip
ED  - Klysubun, Prapong
ED  - Sunwong, Prapaiwan
ED  - Chanwattana, Thakonwat
ED  - Petit-Jean-Genaz, Christine
ED  - Schaa, Volker R.W.
TI  - Prospects to Apply Machine Learning to Optimize the Operation of the Crystal Collimation System at the LHC
J2  - Proc. of IPAC2022, Bangkok, Thailand, 12-17 June 2022
CY  - Bangkok, Thailand
T2  - International Particle Accelerator Conference
T3  - 13
LA  - english
AB  - Crystal collimation relies on the use of bent crystals to coherently deflect halo particles onto dedicated collimator absorbers. This scheme is planned to be used at the LHC to improve the betatron cleaning efficiency with high-intensity ion beams. Only particles with impinging angles below 2.5 urad relative to the crystalline planes can be efficiently channeled at the LHC nominal top energy of 7 Z TeV. For this reason, crystals must be kept in optimal alignment with respect to the circulating beam envelope to maximize the efficiency of the channeling process. Given the small angular acceptance, achieving optimal channeling conditions is particularly challenging. Furthermore, the different phases of the LHC operational cycle involve important dynamic changes of the local orbit and optics, requiring an optimized control of position and angle of the crystals relative to the beam. To this end, the possibility to apply machine learning to the alignment of the crystals, in a dedicated setup and in standard operation, is considered. In this paper, possible solutions for automatic adaptation to the changing beam parameters are highlighted and plans for the LHC ion runs starting in 2022 are discussed.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 1362
EP  - 1365
KW  - collimation
KW  - operation
KW  - collider
KW  - hadron
KW  - network
DA  - 2022/07
PY  - 2022
SN  - 2673-5490
SN  - 978-3-95450-227-1
DO  - doi:10.18429/JACoW-IPAC2022-TUPOTK061
UR  - https://jacow.org/ipac2022/papers/tupotk061.pdf
ER  -