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RIS citation export for WEPCC06: Simulation Supported Profile Reconstruction With Machine Learning

TY - CONF
AU - Singh, R.
AU - Sapinski, M.
AU - Vilsmeier, D.M.
ED - Liu, Zhengzheng
ED - Lidia, Steven
ED - McCausey, Amy
ED - Schaa, Volker RW
TI - Simulation Supported Profile Reconstruction With Machine Learning
J2 - Proc. of IBIC2017, Grand Rapids, MI, USA, 20-24 August 2017
C1 - Grand Rapids, MI, USA
T2 - International Beam Instrumentation Conference
T3 - 6
LA - english
AB - Measured IPM profiles can be significantly distorted due to displacement of residual ions or electrons by interaction with beam fields for high intensity or high energy beams. It is thus difficult to deduce the characteristics of the actual beam profile from the measurements. Neural network with multilayer perceptron (MLP)architecture is applied to reconstruct the actual beam profile from the measurement data. The MLP is trained using the IPM simulation tool developed under the IPMSim collaboration. The first results are presented in this contribution.
PB - JACoW
CP - Geneva, Switzerland
SP - 350
EP - 354
KW - ion
KW - simulation
KW - space-charge
KW - network
KW - electron
DA - 2018/03
PY - 2018
SN - 978-3-95450-192-2
DO - 10.18429/JACoW-IBIC2017-WEPCC06
UR - http://jacow.org/ibic2017/papers/wepcc06.pdf
ER -