Autocorrelation is applied to analyze sets of finite-sampling data such as the turn-by-turn beam position monitor (BPM) data in an accelerator.  This method of data analysis, called the independent component analysis (ICA), is shown to be a powerful beam diagnosis tool for being able to decompose sampled signals into its underlying source signals.  We find that the ICA has an advantage over the principle component analysis (PCA) used in the model-independent analysis (MIA) in isolating independent modes.  Applications of ICA to beam measurements and accelerator modeling and correction will be discussed.

Wednesday, January 21, 2009

2:30 – 3:30 p.m.
CEBAF Center, Room F113

Talk Slides: (Slides)


For more information, please contact Dr. Alex Bogacz or Anne-Marie Valente.