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RIS citation export for TUPOST046: Machine Learning Applied for the Calibration of the Hard X-Ray Single-Shot Spectrometer at the European XFEL

TY  - CONF
AU  - Grech, C.
AU  - Geloni, G.
AU  - Guetg, M.W.
ED  - Zimmermann, Frank
ED  - Tanaka, Hitoshi
ED  - Sudmuang, Porntip
ED  - Klysubun, Prapong
ED  - Sunwong, Prapaiwan
ED  - Chanwattana, Thakonwat
ED  - Petit-Jean-Genaz, Christine
ED  - Schaa, Volker R.W.
TI  - Machine Learning Applied for the Calibration of the Hard X-Ray Single-Shot Spectrometer at the European XFEL
J2  - Proc. of IPAC2022, Bangkok, Thailand, 12-17 June 2022
CY  - Bangkok, Thailand
T2  - International Particle Accelerator Conference
T3  - 13
LA  - english
AB  - Single-crystal monochromators are used in free electron lasers for hard x-ray self-seeding, selecting a very narrow spectral range of the original SASE signal for further amplification. When rotating the crystal around the roll and pitch axes, one can exploit several symmetric and asymmetric reflections as established by Bragg’s law. This work describes the implementation of a machine learning classifier to identify the crystal indices corresponding to a given reflection, and eventually calculate the difference between the photon energy as measured by a single-shot spectrometer and the actual one. The image processing techniques to extract the properties of the crystal reflection are described, as well as how this information is used to calibrate two spectrometer parameters.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 965
EP  - 968
KW  - FEL
KW  - photon
KW  - controls
KW  - laser
KW  - operation
DA  - 2022/07
PY  - 2022
SN  - 2673-5490
SN  - 978-3-95450-227-1
DO  - doi:10.18429/JACoW-IPAC2022-TUPOST046
UR  - https://jacow.org/ipac2022/papers/tupost046.pdf
ER  -