Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning

Sanchez-Gonzalez, A.; Micaelli, P.; Olivier, C.; R. Barillot, T.; Ilchen, M.; A. Lutman, A.; Marinelli, A.; Maxwell, T.; Achner, A.; Agåker, M.; Berrah, N.; Bostedt, C.; D. Bozek, J.; Buck, J.; H. Bucksbaum, P.; Carron Montero, S.; Cooper, B.; P. Cryan, J.; Dong, M.; Feifel, R.; J. Frasinski, L.; Fukuzawa, H.; Galler, A.; Hartmann, G.; Hartmann, N.; Helml, W.; S. Johnson, A.; Knie, A.; O. Lindahl, A.; Liu, J.; Motomura, K.; Mucke, M.; O’Grady, C.; Rubensson, J-E; R. Simpson, E.; J. Squibb, R.; Såthe, C.; Ueda, K.; Vacher, M.; J. Walke, D.; Zhaunerchyk, V.; N. Coffee, R.; P. Marangos, J.

doi:10.1038/ncomms15461

Public

Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning

Shared by NobleBlocks on Jun 5, 2017 • 12:00 AM UTC

Authors:

A. Sanchez-Gonzalez

P. Micaelli

C. Olivier

Abstract

Abstract Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have great potential for a wide impact on science, and are a critical element for unravelling the structural dynamics of matter. To fully harness this potential, we must accurately know the X-ray properties...

Discussions