@article{DOM+21,
  abstract = {X-ray free-electron lasers (XFELs) as the world`s most brilliant light sources provide ultrashort X-ray pulses with durations typically on the order of femtoseconds. Recently, they have approached and entered the attosecond regime, which holds new promises for single-molecule imaging and studying nonlinear and ultrafast phenomena like localized electron dynamics. The technological evolution of XFELs toward well-controllable light sources for precise metrology of ultrafast processes was, however, hampered by the diagnostic capabilities for characterizing X-ray pulses at the attosecond frontier. In this regard, the spectroscopic technique of photoelectron angular streaking has successfully proven how to non-destructively retrieve the exact time-energy structure of XFEL pulses on a single-shot basis. By using artificial intelligence algorithms, in particular convolutional neural networks, we here show how this technique can be leveraged from its proof-of-principle stage toward routine diagnostics at XFELs, thus enhancing and refining their scientific access in all related disciplines.},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System},
  adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv210813979D},
  archiveprefix = {arXiv},
  author = {{Dingel}, Kristina and {Otto}, Thorsten and {Marder}, Lutz and {Funke}, Lars and {Held}, Arne and {Savio}, Sara and {Hans}, Andreas and {Hartmann}, Gregor and {Meier}, David and {Viefhaus}, Jens and {Sick}, Bernhard and {Ehresmann}, Arno and {Ilchen}, Markus and {Helml}, Wolfram},
  eid = {arXiv:2108.13979},
  eprint = {2108.13979},
  interhash = {c803192ee609104c0af8500c632d5d01},
  intrahash = {3904c6bd556676ba2223dbe50000ecbf},
  journal = {arXiv e-prints},
  month = aug,
  pages = {arXiv:2108.13979},
  primaryclass = {physics.data-an},
  title = {{Toward AI-enhanced online-characterization and shaping of ultrashort X-ray free-electron laser pulses}},
  year = 2021
}