Speaker
Sergei Kladov
(University of Chicago)
Description
Microbunching damping in relativistic electron beams is strongly influenced by
the inverse dispersion terms of the transport map, which couple the transverse
phase-space coordinates to the longitudinal displacement. In this work, we use
microbunching damping as an optimization objective for
lattice tuning in linear accelerators: the residual dispersion is minimized by maximizing the observed microbunching signal. Optimizer behavior is experimentally compared with analytical predictions and simulations.
Microbunching-based dispersion optimization is a faster, non-intercepting alternative to conventional dispersion measurements and requires no additional hardware or dedicated lattice configuration.
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Author
Sergei Kladov
(University of Chicago)
Co-authors
Claudio Emma
(SLAC National Accelerator Laboratory)
Zhirong Huang
(SLAC National Accelerator Laboratory)