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{lin:ipac2022-wepoms057,
author = {W. Lin and J.A. Crittenden and G.H. Hoffstaetter and Y.C. Jing and M.A. Sampson and K. Shih},
title = {{Simulation Studies and Machine Learning Applications at the Coherent electron Cooling experiment at RHIC}},
booktitle = {Proc. IPAC'22},
% booktitle = {Proc. 13th International Particle Accelerator Conference (IPAC'22)},
pages = {2387--2390},
eid = {WEPOMS057},
language = {english},
keywords = {LEBT, electron, emittance, quadrupole, solenoid},
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-WEPOMS057},
url = {https://jacow.org/ipac2022/papers/wepoms057.pdf},
abstract = {{Coherent electron cooling is a novel cooling technique which cools high-energy hadron beams rapidly by amplifying the modulation induced by hadrons in electron bunches. The Coherent electron cooling (CeC) experiment at Brookhaven National Laboratory (BNL) is a proof-of-principle test facility to demonstrate this technique. To achieve efficient cooling performance, electron beams generated in the CeC need to meet strict quality standards. In this work, we first present sensitivity studies of the low energy beam transport (LEBT) section, in preparation for building a surrogate model of the LEBT line in the future. We also present preliminary test results of a machine learning (ML) algorithm developed to improve the efficiency of slice-emittance measurements in the CeC diagnostic line.}},
}