Bayesian approach to long-range correlations and multiplicity fluctuations in nucleus-nucleus collisions

TL;DR

This paper introduces a Bayesian method to accurately reconstruct particle multiplicity fluctuations and correlations at fixed impact parameters in nucleus-nucleus collisions, improving understanding of collision dynamics.

Contribution

A novel Bayesian inference approach is developed to disentangle impact parameter fluctuations from intrinsic particle correlations in collision data.

Findings

Multiplicity fluctuations are smaller at large rapidity.

The method effectively isolates impact parameter effects.

Proposed analyses can confirm rapidity-dependent fluctuation patterns.

Abstract

The number of particles detected in a nucleus-nucleus collision strongly depends on the impact parameter of the collision. Therefore, multiplicity fluctuations, as well as rapidity correlations of multiplicities, are dominated by impact parameter fluctuations. We present a method based on Bayesian inference which allows for a robust reconstruction of fluctuations and correlations at fixed impact parameter. We apply the method to ATLAS data on the distribution of charged multiplicity and transverse energy. We argue that multiplicity fluctuations are smaller at large rapidity than around central rapidity. We suggest simple, new analyses, in order to confirm this effect.