IPAC2022 - List of Authors (Shih, K.)

Paper	Title	Page
WEPOMS057	Simulation Studies and Machine Learning Applications at the Coherent electron Cooling experiment at RHIC	2387
	W. Lin, J.A. Crittenden, G.H. Hoffstaetter, M.A. Sampson Cornell University (CLASSE), Cornell Laboratory for Accelerator-Based Sciences and Education, Ithaca, New York, USA Y.C. Jing BNL, Upton, New York, USA K. Shih SBU, Stony Brook, New York, USA
	Funding: Work supported by the U.S. National Science Foundation under Award PHY-1549132, and by Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy. 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.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOMS057
About •	Received ※ 06 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 15 June 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Simulation Studies and Machine Learning Applications at the Coherent electron Cooling experiment at RHIC

2387

W. Lin, J.A. Crittenden, G.H. Hoffstaetter, M.A. Sampson
Cornell University (CLASSE), Cornell Laboratory for Accelerator-Based Sciences and Education, Ithaca, New York, USA
Y.C. Jing
BNL, Upton, New York, USA
K. Shih
SBU, Stony Brook, New York, USA

Funding: Work supported by the U.S. National Science Foundation under Award PHY-1549132, and by Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy.
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.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOMS057

About •

Received ※ 06 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 15 June 2022

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)