Iterative unfolding with the Richardson–Lucy algorithm

The Richardson–Lucy unfolding approach is reviewed. It is extremely simple and excellently performing. It efficiently suppresses artificial high frequency contributions and permits to introduce known features of the true distribution. An algorithm to optimize the number of iterations has been developed and tested with five different types of distributions. The corresponding unfolding results were independent of the number of events, the number of bins in the observed and the unfolded distribution, and the experimental resolution.