The Joint Accelerator Conferences Website (JACoW) is an international collaboration that publishes the proceedings of accelerator conferences held around the world.
TY - CONF AU - Emma, C. AU - Alverson, M.D. AU - Edelen, A.L. AU - Hanuka, A. AU - Hogan, M.J. AU - O'Shea, B.D. AU - Storey, D.W. AU - White, G.R. AU - Yakimenko, V. ED - Schaa, Volker RW ED - Jansson, Andreas ED - Shea, Thomas ED - Olander, Johan TI - Machine Learning-Based Longitudinal Phase Space Prediction of Two-Bunch Operation at FACET-II J2 - Proc. of IBIC2019, Malmö, Sweden, 08-12 September 2019 CY - Malmö, Sweden T2 - International Beam Instrumentation Conferenc T3 - 8 LA - english AB - We report on the application of machine learning (ML) methods for predicting the longitudinal phase space (LPS) distribution of particle accelerators. Our approach consists of training a ML-based virtual diagnostic to predict the LPS using only nondestructive linac and e-beam measurements as inputs. We validate this approach with a simulation study for the FACET-II linac and with an experimental demonstration conducted at LCLS. At LCLS, the e-beam LPS images are obtained with a transverse deflecting cavity and used as training data for our ML model. In both the FACET-II and LCLS cases we find good agreement between the predicted and simulated/measured LPS profiles, an important step towards showing the feasibility of implementing such a virtual diagnostic on particle accelerators in the future. PB - JACoW Publishing CP - Geneva, Switzerland SP - 679 EP - 683 KW - diagnostics KW - simulation KW - operation KW - experiment KW - linac DA - 2019/11 PY - 2019 SN - 2673-5350 SN - 978-3-95450-204-2 DO - doi:10.18429/JACoW-IBIC2019-THBO01 UR - http://jacow.org/ibic2019/papers/thbo01.pdf ER -