JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@inproceedings{soubelet:ipac2022-wepopt008,
author = {F. Soubelet and Ö. Apsimon and T.H.B. Persson and R. Tomás García and C.P. Welsch},
title = {{Supervised Machine Learning for Local Coupling Sources Detection in the LHC}},
booktitle = {Proc. IPAC'22},
% booktitle = {Proc. 13th International Particle Accelerator Conference (IPAC'22)},
pages = {1842--1845},
eid = {WEPOPT008},
language = {english},
keywords = {coupling, quadrupole, network, optics, simulation},
venue = {Bangkok, Thailand},
series = {International Particle Accelerator Conference},
number = {13},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {07},
year = {2022},
issn = {2673-5490},
isbn = {978-3-95450-227-1},
doi = {10.18429/JACoW-IPAC2022-WEPOPT008},
url = {https://jacow.org/ipac2022/papers/wepopt008.pdf},
abstract = {{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.}},
}