Methods for Quantitative Interpretation of Retarding Field Analyzer Data∗
نویسندگان
چکیده
A great deal of Retarding Field Analyzer (RFA) data has been taken as part of the CesrTA program at Cornell. Obtaining a quantitative understanding of this data requires use of cloud simulation programs, as well as a detailed model of the RFA 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 using a systematic method to improve agreement between data and simulation.
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