Title |
CERN Accelerators Beam Optimization Algorithm |
Authors |
- E. Piselli, A. Akroh, S. Rothe
CERN, Geneva, Switzerland
- K. Blaum, M. Door
MPI-K, Heidelberg, Germany
- D. Leimbach
IKP, Mainz, Germany
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Abstract |
In experimental physics, computer algorithms are used to make decisions to perform measurements and different types of operations. To create a useful algorithm, the optimization parameters should be based on real time data. However, parameter optimization is a time consuming task, due to the large search space. In order to cut down the runtime of optimization we propose an algorithm inspired by the numerical method Nelder-Mead. This paper presents details of our method and selected experimental results from high-energy (CERN accelerators) to low-energy (Penning-trap systems) experiments as to demonstrate its efficiency. We also show simulations performed on standard test functions for optimization.
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Paper |
download WEPHA124.PDF [1.652 MB / 6 pages] |
Poster |
download WEPHA124_POSTER.PDF [1.069 MB] |
Export |
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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 |
27 September 2019 |
Accepted |
09 October 2019 |
Issue Date |
30 August 2020 |
DOI |
doi:10.18429/JACoW-ICALEPCS2019-WEPHA124 |
Pages |
1379-1384 |
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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