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

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.

13 pages, 11 figures; v2: published version with some added explanations and rephrasing of our presentation, especially in Part II. Code for 2D Bayesian reconstruction of ATLAS data is included as ancillary file

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Cited by in corpus (9)

• Machine Learning in Nuclear Physics
• Evidence of the triaxial structure of ${}^{129}$Xe at the Large Hadron Collider
• Correlations between flow and transverse momentum in Xe+Xe and Pb+Pb collisions at the LHC with the ATLAS detector: a probe of the heavy-ion initial state and nuclear deformation
• Measures of azimuthal anisotropy in high-energy collisions
• Non-Gaussian transverse momentum fluctuations from impact parameter fluctuations
• Multiplicity fluctuations and correlations in 5.02 TeV p+Pb collisions at zero impact parameter
• Impact parameter dependence of anisotropic flow: Bayesian reconstruction in ultracentral nucleus-nucleus collisions
• The size of the quark-gluon plasma in ultracentral collisions: impact of initial density fluctuations on the average transverse momentum
• Bayesian reconstruction of anisotropic flow fluctuations at fixed impact parameter