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RIS citation export for TUIXGD1: Accurate and Confident Prediction of Electron Beam Longitudinal Properties Using Spectral Virtual Diagnostics

TY  - UNPB
AU  - Hanuka, A.
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  - Accurate and Confident Prediction of Electron Beam Longitudinal Properties Using Spectral Virtual Diagnostics
J2  - Proc. of IPAC2022, Bangkok, Thailand, 12-17 June 2022
CY  - Bangkok, Thailand
T2  - International Particle Accelerator Conference
T3  - 13
LA  - english
AB  - Longitudinal phase space measurement is one of the key diagnostics in FEL machines. In this work it is shown as the application of machine learning based virtual diagnostics can provide undirect information on the longitudinal phase space of the beam in a non intercepting way and, in combination with standard longitudinal diagnostics methods, helps overcoming resolution limitations and increasing the accuracy of the measured data.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
ER  -