| Title |
Machine Learning Based Tuning and Diagnostics for the ATR Line at BNL |
| Authors |
- J.P. Edelen, K. Bruhwiler, E.G. Carlin, C.C. Hall
RadiaSoft LLC, Boulder, Colorado, USA
- K.A. Brown, V. Schoefer
BNL, Upton, New York, USA
|
| Abstract |
Over the past several years machine learning has increased in popularity for accelerator applications. We have been exploring the use of machine learning as a diagnostic and tuning tool for transfer line from the AGS to RHIC at Brookhaven National Laboratory. In our work, inverse models are used to either provide feed-forward corrections for beam steering or as a diagnostic to illuminate quadrupole magnets that have excitation errors. In this talk we present results on using machine learning for beam steering optimization for a range of different operating energies. We also demonstrate the use of inverse models for optical error diagnostics. Our results are from studies that use combine simulation and measurement data.
|
| Funding |
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Award Number DE-SC0019682. |
| Paper |
download THAL04.PDF [3.131 MB / 6 pages] |
| Slides |
download THAL04_TALK.PDF [4.845 MB] |
| Cite |
download ※ BibTeX
※ LaTeX
※ Text/Word
※ RIS
※ EndNote |
| Conference |
ICALEPCS2021 |
| Series |
International Conference on Accelerator and Large Experimental Physics Control Systems (18th) |
| Location |
Shanghai, China |
| Date |
14-22 October 2021 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Kazuro Furukawa (KEK, Tsukuba, Japan); Yingbing Yan (SARI,Shanghai, China); Yongbin Leng (SARI,Shanghai, China); Zhichu Chen (SARI,Shanghai, China); Volker RW Schaa (GSI, Darmstadt, Germany) |
| Online ISBN |
978-3-95450-221-9 |
| Online ISSN |
2226-0358 |
| Received |
10 October 2021 |
| Revised |
22 October 2021 |
| Accepted |
14 December 2021 |
| Issue Date |
01 March 2022 |
| DOI |
doi:10.18429/JACoW-ICALEPCS2021-THAL04 |
| Pages |
803-808 |
| 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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