JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
TY - CONF AU - Soubelet, F. AU - Apsimon, Ö. AU - Persson, T.H.B. AU - Tomás García, R. AU - Welsch, C.P. 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 - Supervised Machine Learning for Local Coupling Sources Detection in 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 - Local interaction region (IR) linear coupling in the LHC has been shown to have a negative impact on beam size and luminosity, making its accurate correction for Run 3 and beyond a necessity. In view of determining corrections, supervised machine learning has been applied to the detection of linear coupling sources, showing promising results in simulations. An evaluation of different applied models is given, followed by the presentation of further possible application concepts for linear coupling corrections using machine learning. PB - JACoW Publishing CP - Geneva, Switzerland SP - 1842 EP - 1845 KW - coupling KW - quadrupole KW - network KW - optics KW - simulation DA - 2022/07 PY - 2022 SN - 2673-5490 SN - 978-3-95450-227-1 DO - doi:10.18429/JACoW-IPAC2022-WEPOPT008 UR - https://jacow.org/ipac2022/papers/wepopt008.pdf ER -