Unfolding of event-by-event net-charge distributions in heavy-ion collision

Abstract

We discuss a method to obtain the true event-by-event net-charge multiplicity distributions from a corresponding measured distribution which is subjected to detector effects such as finite particle counting efficiency. The approach is based on the Bayes method for the unfolding of distributions. We are able to faithfully unfold back the measured distributions to match their corresponding true distributions obtained for a widely varying underlying particle production mechanism, beam energy and collision centrality. Particularly the mean, variance, skewness, kurtosis and their products and ratios of net-charge distributions from the event generators are shown to be successfully unfolded from the measured distributions constructed to mimic a real experimental distribution. We demonstrate the necessity to account for detector effects before associating the higher moments of net-charge distributions with physical quantities or phenomena. The advantage of this approach is that one need not construct new observables to cancel out detector effects which lose their ability to be connected to physical quantities calculable in standard theories.