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 - Edelen, J.P. AU - Einstein-Curtis, J.A. AU - Hall, C.C. AU - Henderson, M.J. AU - Romanov, A.L. ED - Forck, Peter ED - Wawrzyniak, Adriana ED - Schaa, Volker R.W. ED - Kowalski, Grzegorz W. ED - Cudek, Agnieszka (SOLARIS, Kraków TI - Removing Noise in BPM Measurements with Variational Autoencoders J2 - Proc. of IBIC2022, Kraków, Poland, 11-15 September 2022 CY - Kraków, Poland T2 - International Beam Instrumentation Conference T3 - 11 LA - english AB - Noise in beam measurements is an ever-present challenge in accelerator operations. In addition to the challenges presented by hardware and signal processing, new operational regimes, such as ultra-short bunches, create additional difficulties in routine beam measurements. Techniques in machine learning have been successfully applied in other domains to overcome challenges inherent in noisy data. Variational autoencoders (VAEs) are shown to be capable of removing significant leevels of noise. A VAE can be used as a pre-processing tool for noise removal before the de-noised data is analyzed via other methods, or the VAE can be directly used to make beam dynamics measurements. Here we present the use of VAEs as a tool for addressing noise in BPM measurements. PB - JACoW Publishing CP - Geneva, Switzerland SP - 43 EP - 46 KW - operation KW - network KW - optics KW - coupling KW - controls DA - 2022/12 PY - 2022 SN - 2673-5350 SN - 978-3-95450-241-7 DO - doi:10.18429/JACoW-IBIC2022-MOP10 UR - https://jacow.org/ibic2022/papers/mop10.pdf ER -