Author: Hudson, S. T. P.
Paper Title Page
SAPAF03 Comparison of Model-Based and Heuristic Optimization Algorithms Applied to Photoinjectors Using Libensemble 22
 
  • N.R. Neveu
    IIT, Chicago, Illinois, USA
  • S. T. P. Hudson, J.M. Larson
    ANL, Argonne, Illinois, USA
  • L.K. Spentzouris
    Illinois Institute of Technology, Chicago, Illinois, USA
 
  Funding: U.S. DOE, OS, contract DE-AC02-06CH11357 and grant DE-SC0015479.
Genetic algorithms are common and often used in the accelerator community. They require large amounts of computational resources and empirical adjustment of hyperparameters. Model based methods are significantly more efficient, but often labeled as unreliable for the nonlinear or unsmooth problems that can be found in accelerator physics. We investigate the behavior of both approaches using a photoinjector operated in the space charge dominated regime. All optimization runs are coordinated and managed by the Python library libEnsemble, which is developed at Argonne National Laboratory.
 
slides icon Slides SAPAF03 [0.653 MB]  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-ICAP2018-SAPAF03  
About • paper received ※ 11 November 2018       paper accepted ※ 19 November 2018       issue date ※ 26 January 2019  
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