Iterative unfolding with the Richardson-Lucy algorithm
Abstract
The Richardson-Lucy unfolding approach is simple and excellently performing. It efficiently suppresses artificial high frequency contributions and permits to introduce known features of the true distribution. An algorithm to fix the number of iterations to an optimal value has been developed and tested with five different types of distributions, with different event numbers and with different binnings. The influence of the starting distribution has been studied. A simple way to document the unfolding result such that it can be compared to theoretical predictions is proposed.
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