Author: Wu, D.
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TUPMF044 First Lasing of the CAEP THz FEL Facility Driven by a Superconducting Accelerator 1349
 
  • D. Wu, W. Bai, D.R. Deng, C.L. Lao, M. Li, S.F. Lin, X. Luo, L.J. Shan, X. Shen, H. Wang, J. Wang, Y. Xu, L.G. Yan, X. Yang, K. Zhou
    CAEP/IAE, Mianyang, Sichuan, People's Republic of China
  • Y.H. Dou, X.J. Shu
    Institute of Applied Physics and Computational Mathematics, People's Republic of China
  • W.-H. Huang
    TUB, Beijing, People's Republic of China
  • X.Y. Lu
    PKU, Beijing, People's Republic of China
  
  Funding: Work supported by China National Key Scientific Instrument and Equipment Development Project (2011YQ130018), National Natural Science Foundation of China (11475159, 11505173, 11575264 and 11605190)
The stimulated saturation of the terahertz free electron laser at China Academy of Engineering Physics was reached in August, 2017. This THz FEL facility consists of a GaAs photocathode high-voltage DC gun, a superconducting RF linac, a planar undulator and a quasi-concentric optical resonator. The terahertz wave frequency is continuous adjustable from 2 THz to 3 THz. The average power is more than 10 W and the micro-pulse power is more than 0.3 MW. 		 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-TUPMF044  
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TUPMF045 Performance Optimization of a Prototype Undulator U38 Using Multi-Objective Genetic Algorithm 1353
 
  • L.G. Yan, D.R. Deng, P. Li, D. Wu
    CAEP/IAE, Mianyang, Sichuan, People's Republic of China
  
  Funding: The project of the national large-scale instrument development: 2011YQ130018; National Natural Science Foundation of China: 11505174, 11505173 and 11605190.
Genetic Algorithm (GA) is one of the most excellent method to search the optimal solution of a problem, which has been applied to solve various problems. It is hard to estimate shim applied on raw undulator precisely. There are many methods have been developed to solve the problem. In this proceeding, we measured the magnetic field distribution of prototype undulator U38 and concluded the shim using multi-objective GA. The code was written with the language of Python and based on the package pyevolve. A multi-objective fitness function was setup to implement the multi-objective optimization. Experimentally，performances satisfied the requirements by shimming U38 three times. The trajectory center deviation, peak-to-peak error and phase error are reduced to 0.15 mm, 0.49% and 1°. 		 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-TUPMF045  
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