Keyword: FEL
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WEVIR03 Microbunch Rotation as an Outcoupling Mechanism for Cavity-based X-Ray Free Electron Lasers electron, quadrupole, cavity, undulator 35
 
  • R.A. Margraf, Z. Huang
    Stanford University, Stanford, California, USA
  • Z. Huang, J.P. MacArthur, G. Marcus
    SLAC, Menlo Park, California, USA
 
  Funding: This work was supported by the Department of Energy, Laboratory Directed Research and Development program at SLAC National Accelerator Laboratory, under contract DE-AC02-76SF00515.
Electron bunches in an undulator develop periodic density fluctuations, or microbunches, which enable the exponential gain of power in an X-ray free-electron laser (XFEL). For certain applications, one would like to preserve this microbunching structure of the electron bunch as it experiences a dipole kick which bends its trajectory. This process, called microbunch rotation, rotates the microbunches and aligns them perpendicular to the new direction of electron travel. Microbunch rotation was demonstrated experimentally by MacArthur et al. with soft x-rays* and additional unpublished data demonstrated microbunch rotation with hard x-rays. Further investigations into the magnetic lattice used to rotate these microbunches showed that microbunches can be rotated using an achromatic lattice with a small R56, connecting this technique to earlier studies of achromatic bends. Here, we propose and study a practical way to rotate Angstrom-level microbunching as an out-coupling mechanism for the Optical Cavity-Based X-ray FEL (CBXFEL) project at SLAC.
*J. P. MacArthur, A. A. Lutman, J. Krzywinski, and Z. Huang, "Microbunch Rotation and Coherent Undulator Radiation from a Kicked Electron Beam", Physical Review X, vol. 8, no. 4, Nov. 2018.
 
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DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2020-WEVIR03  
About • paper received ※ 01 June 2020       paper accepted ※ 12 June 2020       issue date ※ 11 August 2020  
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WEVIR10 Adaptive Feedback Control and Machine Learning for Particle Accelerators electron, controls, diagnostics, feedback 53
 
  • A. Scheinker
    LANL, Los Alamos, New Mexico, USA
 
  The precise control of charged particle beams, such as an electron beam’s longitudinal phase space as well as the maximization of the output power of a free electron laser (FEL), or the minimization of beam loss in accelerators, are challenging tasks. For example, even when all FEL parameter set points are held constant both the beam phase space and the output power have high variance because of the uncertainty and time-variation of thousands of coupled parameters and of the electron distribution coming off of the photo cathode. Similarly, all large accelerators face challenges due to time variation, leading to beam losses and changing behavior even when all accelerator parameters are held fixed. We present recent efforts towards developing machine learning methods along with automatic, model-independent feedback for automatic tuning of charge particle beams in particle accelerators. We present experimental results from the LANSCE linear accelerator at LANL, the EuXFEL, AWAKE at CERN, FACET-II and the LCLS.  
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DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2020-WEVIR10  
About • paper received ※ 27 May 2020       paper accepted ※ 12 June 2020       issue date ※ 14 June 2020  
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