TY  - JOUR
AU  - Ferreira de Lima, Danilo Enoque
AU  - Davtyan, Arman
AU  - Laksman, Joakim
AU  - Gerasimova, Natalia
AU  - Maltezopoulos, Theophilos
AU  - Liu, Jia
AU  - Schmidt, Philipp
AU  - Michelat, Thomas
AU  - Mazza, Tommaso
AU  - Meyer, Michael
AU  - Grünert, Jan
AU  - Gelisio, Luca
TI  - Machine-learning-enhanced automatic spectral characterization of x-ray pulses from a free-electron laser
JO  - Communications Physics
VL  - 7
IS  - 1
SN  - 2399-3650
CY  - London
PB  - Springer Nature
M1  - PUBDB-2025-00522
SP  - 400
PY  - 2024
AB  - A reliable characterization of x-ray pulses is critical to optimally exploit advanced photon sources, such as free-electron lasers. In this paper, we present a method based on machine learning, the virtual spectrometer, that improves the resolution of non-invasive spectral diagnostics at the European XFEL by up to 40
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:001380084800001
DO  - DOI:10.1038/s42005-024-01900-6
UR  - https://bib-pubdb1.desy.de/record/622842
ER  -