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

TL;DR

This paper introduces a Bayesian unfolding method to correct measured net-charge distributions in heavy-ion collisions for detector effects, enabling more accurate comparisons with theoretical models across various energies and centralities.

Contribution

The paper presents a novel Bayesian unfolding technique that effectively removes detector artifacts from net-charge distributions in heavy-ion collision experiments.

Findings

Unfolding method successfully recovers true distributions across different energies and centralities.

Emphasizes importance of accounting for detector effects in higher moment analyses.

Method simplifies comparison between experimental data and theoretical predictions.

Abstract

An unfolding method, based on Bayes theorem is presented to obtain true event-by-event net-charge multiplicity distribution from a corresponding measured distribution, which is subjected to detector artifacts. The unfolding is demonstrated to work for widely varying particle production mechanism, beam energy and collision centrality. Further the necessity of taking into account the detector effects is emphasized before comparing the experimental measurements to the theoretical calculations, particularly in case of higher moments. The advantage of this approach being that one need not construct new observable to cancel out detector effects which loose their ability to be connected to physical quantities calculable in standard theories.