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Methods for Quantitative Interpretation of Retarding Field Analyzer Data

Abstract

Over the course of the CesrTA program at Cornell, over 30 Retarding Field Analyzers (RFAs) have been installed in the CESR storage ring, and a great deal of data has been taken with them. These devices measure the local electron cloud density and energy distribution, and can be used to evaluate the efficacy of different cloud mitigation techniques. Obtaining a quantitative understanding of RFA data requires use of cloud simulation programs, as well as a detailed model of the detector itself. In a drift region, the RFA can be modeled by postprocessing the output of a simulation code, and one can obtain best fit values for important simulation parameters with a chi-square minimization method.

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