JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
TY - CONF AU - Zhang, S. AU - Andonian, G. AU - Apsimon, Ö. AU - Hansel, C.E. AU - Manwani, P. AU - Naranjo, B. AU - Oruganti, M.H. AU - Rosenzweig, J.B. AU - Welsch, C.P. AU - Yadav, M. 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 - Reconstruction of Beam Parameters from Betatron Radiation Using Maximum Likelihood Estimation and Machine Learning J2 - Proc. of IPAC2022, Bangkok, Thailand, 12-17 June 2022 CY - Bangkok, Thailand T2 - International Particle Accelerator Conference T3 - 13 LA - english AB - Betatron radiation that arises during plasma wakefield acceleration can be measured by a UCLA-built Compton spectrometer, which records the energy and angular position of incoming photons. Because information about the properties of the beam is encoded in the betatron radiation, measurements of the radiation can be used to reconstruct beam parameters. One method of extracting information about beam parameters from measurements of radiation is maximum likelihood estimation (MLE), a statistical technique which is used to determine unknown parameters from a distribution of observed data. In addition, machine learning methods, which are increasingly being implemented for different fields of beam diagnostics, can also be applied. We assess the ability of both MLE and other machine learning methods to accurately extract beam parameters from measurements. PB - JACoW Publishing CP - Geneva, Switzerland SP - 407 EP - 409 KW - radiation KW - betatron KW - simulation KW - diagnostics KW - beam-diagnostic DA - 2022/07 PY - 2022 SN - 2673-5490 SN - 978-3-95450-227-1 DO - doi:10.18429/JACoW-IPAC2022-MOPOPT063 UR - https://jacow.org/ipac2022/papers/mopopt063.pdf ER -