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{gao:ipac2022-tupost054,
author = {Y. Gao and K.A. Brown and J.A. Crittenden and X. Gu and G.H. Hoffstaetter and W. Lin and J. Morris and S. Seletskiy},
% author = {Y. Gao and K.A. Brown and J.A. Crittenden and X. Gu and G.H. Hoffstaetter and W. Lin and others},
% author = {Y. Gao and others},
title = {{Experiment of Bayesian Optimization for Trajectory Alignment at Low Energy RHIC Electron Cooler}},
booktitle = {Proc. IPAC'22},
% booktitle = {Proc. 13th International Particle Accelerator Conference (IPAC'22)},
pages = {987--990},
eid = {TUPOST054},
language = {english},
keywords = {electron, experiment, alignment, collider, controls},
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-TUPOST054},
url = {https://jacow.org/ipac2022/papers/tupost054.pdf},
abstract = {{As the world’s first electron cooler that uses radio frequency (rf) accelerated electron bunches, the low energy RHIC electron cooling (LEReC) system is a nonmagnetized cooler of ion beams in RHIC at Brookhaven National Laboratory. Beam dynamics in LEReC are different from the more conventional electron coolers due to the bunching of the electron beam. To ensure an efficient cooling performance at LEReC, many parameters need to be monitored and fine-tuned. The alignment of the electron and ion trajectories in the LEReC cooling sections is one of the most critical parameters. This work explores using a machine learning (ML) method - Bayesian Optimization (BO) to optimize the trajectories’ alignment. Experimental results demonstrate that ML methods such as BO can perform control tasks efficiently in the RHIC controls system.}},
}