|MOPA89||RHIC Electron Beam Cooling Analysis Using Principle Component and Autoencoder Analysis||luminosity, electron, ECR, network||260|
Funding: Work supported by the US Department of Energy under contract No. DE-AC02-98CH10886.
Principal component analysis and autoencoder analysis were used to analyze the experimental data of RHIC operation with low energy RHIC electron cooling (LEReC). This is unsupervised learning which includes electron beam settings and observable during operation. Both analyses were used to gauge the dimensional reducibility of the data and to understand which features are important to beam cooling.
|DOI •||reference for this paper ※ doi:10.18429/JACoW-NAPAC2022-MOPA89|
|About •||Received ※ 02 August 2022 — Revised ※ 05 August 2022 — Accepted ※ 06 August 2022 — Issue date ※ 12 August 2022|
|Cite •||reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)|