| Title |
Experimental Demonstration of Machine Learning Application in LHC Optics Commissioning |
| Authors |
- E. Fol, F.S. Carlier, J. Dilly, M. Hofer, J. Keintzel, M. Le Garrec, E.H. Maclean, T.H.B. Persson, F. Soubelet, R. Tomás García, A. Wegscheider
CERN, Meyrin, Switzerland
- J.F. Cardona
UNAL, Bogota D.C, Colombia
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| Abstract |
Recently, we conducted successful studies on the suitability of machine learning (ML) methods for optics measurements and corrections, incorporating novel ML-based methods for local optics corrections and reconstruction of optics functions. After performing extensive verifications on simulations and past measurement data, the newly developed techniques became operational in the LHC commissioning 2022. We present the experimental results obtained with the ML-based methods and discuss future improvements. Besides, we also report on improving the Beam Position Monitor (BPM) diagnostics with the help of the anomaly detection technique capable to identify malfunctioning BPMs along with their possible fault causes.
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| Paper |
download MOPOPT047.PDF [0.256 MB / 4 pages] |
| Cite |
download ※ BibTeX
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※ EndNote |
| Conference |
IPAC2022 |
| Series |
International Particle Accelerator Conference (13th) |
| Location |
Bangkok, Thailand |
| Date |
12-17 June 2022 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Frank Zimmermann (CERN, Meyrin, Switzerland); Hitoshi Tanaka (RIKEN, Hyogo, Japan); Porntip Sudmuang (SRLI, Nakhon, Thailand); Prapong Klysubun (SRLI, Nakhon, Thailand); Prapaiwan Sunwong (SRLI, Nakhon, Thailand); Thakonwat Chanwattana (SRLI, Nakhon, Thailand); Christine Petit-Jean-Genaz (CERN, Meyrin, Switzerland); Volker R.W. Schaa (GSI, Darmstadt, Germany) |
| Online ISBN |
978-3-95450-227-1 |
| Online ISSN |
2673-5490 |
| Received |
07 June 2022 |
| Accepted |
16 June 2022 |
| Issue Date |
06 July 2022 |
| DOI |
doi:10.18429/JACoW-IPAC2022-MOPOPT047 |
| Pages |
359-362 |
| Copyright |
 Published by JACoW Publishing under the terms of the Creative Commons Attribution 3.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |
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