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BiBTeX citation export for TUPOST056: Multi-Objective Bayesian Optimization at SLAC MeV-UED

@inproceedings{ji:ipac2022-tupost056,
  author       = {F. Ji and A.L. Edelen and R.J. England and P.L. Kramer and D. Luo and C.E. Mayes and M.P. Minitti and S.A. Miskovich and M. Mo and A.H. Reid and R.J. Roussel and X. Shen and X.J. Wang and S.P. Weathersby},
% author       = {F. Ji and A.L. Edelen and R.J. England and P.L. Kramer and D. Luo and C.E. Mayes and others},
% author       = {F. Ji and others},
  title        = {{Multi-Objective Bayesian Optimization at SLAC MeV-UED}},
  booktitle    = {Proc. IPAC'22},
% booktitle    = {Proc. 13th International Particle Accelerator Conference (IPAC'22)},
  pages        = {995--998},
  eid          = {TUPOST056},
  language     = {english},
  keywords     = {electron, gun, controls, detector, timing},
  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-TUPOST056},
  url          = {https://jacow.org/ipac2022/papers/tupost056.pdf},
  abstract     = {{SLAC MeV-UED, part of the LCLS user facility, is a powerful ’electron camera’ for the study of ultrafast molecular structural dynamics and the coupling of electronic and atomic motions in a variety of material and chemical systems. The growing demand of scientific applications calls for rapid switching between different beamline configurations for delivering electron beams meeting specific user run requirements, necessitating fast online tuning strategies to reduce set up time. Here, we utilize multi-objective Bayesian optimization(MOBO) for fast searching the parameter space efficiently in a serialized manner, and mapping out the Pareto Front which gives the trade-offs between key beam parameters, i.e., spot size, q-resolution, pulse length, pulse charge, etc. Algorithm, model deployment and first test results will be presented.}},
}