Two-dimensional Bayesian Approach for Centrality Determination in Nucleus-Nucleus Collisions

TL;DR

This paper introduces a Bayesian two-dimensional method for accurately determining the centrality of nucleus-nucleus collisions by analyzing track hits and spectator energy, validated with simulated data.

Contribution

It presents a novel Bayesian framework that improves centrality estimation by modeling fluctuations of key observables in nuclear collision experiments.

Findings

Superior description of observable fluctuations in all collision centralities

Effective verification using simulated Xe+CsI collision data

Enhanced accuracy in impact parameter estimation

Abstract

The determination of centrality in nucleus-nucleus collisions is a crucial task as it enables the estimation of the impact parameter and hence allows for the comparison of experimental results with data from theoretical models and other experiments. In this work, we present a two-dimensional approach for centrality determination based on a Bayesian framework. The observables used were the number of track hits and the deposited energy of spectators in the forward hadronic calorimeter. A distribution is proposed to describe the fluctuations of these two observables at a fixed impact parameter value, which provides a significantly superior description of the observable distributions in both central and peripheral regions. The effectiveness of the proposed method was verified for the BM@N experiment using simulated data for Xe+CsI collisions at a beam energy of 3.8 AGeV.