| Title |
Software Architecture for Automatic LHC Collimator Alignment Using Machine Learning |
| Authors |
- G. Azzopardi, S. Redaelli, B. Salvachua
CERN, Meyrin, Switzerland
- A. Muscat, G. Valentino
University of Malta, Information and Communication Technology, Msida, Malta
|
| Abstract |
The Large Hadron Collider at CERN relies on a collimation system to absorb unavoidable beam losses before they reach the superconducting magnets. The collimators are positioned close to the beam in a transverse setting hierarchy achieved by aligning each collimator with a precision of a few tens of micrometers. In previous years, collimator alignments were performed semi-automatically*, requiring collimation experts to be present to oversee and control the entire process. In 2018, manual, expert control of the alignment procedure was replaced by dedicated machine learning algorithms, and this new software was used for collimator alignments throughout the year. This paper gives an overview of the software re-design required to achieve fully automatic collimator alignments, describing in detail the software architecture and controls systems involved. Following this successful deployment, this software will be used in the future as the default alignment software for the LHC.
|
| Footnotes & References |
*G. Valentino et al., "Semi-automatic beam-based LHC collimator alignment", Physical Review Special Topics-Accelerators and Beams vol. 15, no. 5, 2012. |
| Paper |
download MOCPL04.PDF [6.274 MB / 8 pages] |
| Slides |
download MOCPL04_TALK.PDF [5.933 MB] |
| Export |
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※ EndNote |
| Conference |
ICALEPCS2019 |
| Series |
International Conference on Accelerator and Large Experimental Physics Control Systems (17th) |
| Location |
New York, NY, USA |
| Date |
05-11 October 2019 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Karen S. White (ORNL, Oak Ridge, TN, USA); Kevin A. Brown (BNL, Upton, NY, USA); Philip S. Dyer (BNL, Upton, NY, USA); Volker RW Schaa (GSI, Darmstadt, Germany) |
| Online ISBN |
978-3-95450-209-7 |
| Online ISSN |
2226-0358 |
| Received |
28 September 2019 |
| Accepted |
09 October 2019 |
| Issue Date |
30 August 2020 |
| DOI |
doi:10.18429/JACoW-ICALEPCS2019-MOCPL04 |
| Pages |
78-85 |
| 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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