Machine learning applied to single-shot x-ray diagnostics in an XFEL

11 Oct 2016A. Sanchez-GonzalezP. MicaelliC. OlivierT. R. BarillotM. IlchenA. A. LutmanA. MarinelliT. MaxwellA. AchnerM. AgåkerN. BerrahC. BostedtJ. BuckP. H. BucksbaumS. Carron MonteroB. CooperJ. P. CryanM. DongR. FeifelL. J. FrasinskiH. FukuzawaA. GallerG. HartmannN. HartmannW. HelmlA. S. JohnsonA. KnieA. O. LindahlJ. LiuK. MotomuraM. MuckeC. O'GradyJ-E. RubenssonE. R. SimpsonR. J. SquibbC. SåtheK. UedaM. VacherD. J. WalkeV. ZhaunerchykR. N. CoffeeJ. P. Marangos

X-ray free-electron lasers (XFELs) are the only sources currently able to produce bright few-fs pulses with tunable photon energies from 100 eV to more than 10 keV. Due to the stochastic SASE operating principles and other technical issues the output pulses are subject to large fluctuations, making it necessary to characterize the x-ray pulses on every shot for data sorting purposes... (read more)

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