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BiBTeX citation export for MOPA89: RHIC Electron Beam Cooling Analysis Using Principle Component and Autoencoder Analysis

@inproceedings{tran:napac2022-mopa89,
  author       = {A.D. Tran and X. Gu and Y. Hao},
  title        = {{RHIC Electron Beam Cooling Analysis Using Principle Component and Autoencoder Analysis}},
& booktitle    = {Proc. NAPAC'22},
  booktitle    = {Proc. 5th Int. Particle Accel. Conf. (NAPAC'22)},
  pages        = {260--262},
  eid          = {MOPA89},
  language     = {english},
  keywords     = {luminosity, electron, ECR, network, beam-cooling},
  venue        = {Albuquerque, NM, USA},
  series       = {International Particle Accelerator Conference},
  number       = {5},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {10},
  year         = {2022},
  issn         = {2673-7000},
  isbn         = {978-3-95450-232-5},
  doi          = {10.18429/JACoW-NAPAC2022-MOPA89},
  url          = {https://jacow.org/napac2022/papers/mopa89.pdf},
  abstract     = {{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.}},
}