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Preprints, Working Papers, ... Year : 2017

Relating centrality to impact parameter in nucleus-nucleus collisions

Abstract

In ultrarelativistic heavy-ion experiments, one estimates the centrality of a collision using a single observable, say $n$, typically given by the transverse energy or the number of tracks observed in a dedicated detector. The correlation between $n$ and the impact parameter, $b$, of the collision is then inferred by fitting a specific model of the collision dynamics, such as the Glauber model, to experimental data. The goal of this paper is to assess precisely which information about $b$ can be extracted from data without any specific model of the collision. Under the sole assumption that the probability distribution of $n$ is Gaussian for a fixed $b$, we show that the probability distribution of impact parameter in a narrow centrality bin can be accurately reconstructed up to $5\%$ centrality. We apply our methodology to Relativistic Heavy Ion Collider (RHIC) and Large Hadron Collider (LHC) data. We propose a simple measure of the precision of the centrality determination, which can be used to compare different experiments.
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Dates and versions

cea-01583430 , version 1 (07-09-2017)

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Sruthy Jyothi Das, Giuliano Giacalone, Pierre-Amaury Monard, Jean-Yves Ollitrault. Relating centrality to impact parameter in nucleus-nucleus collisions. 2017. ⟨cea-01583430⟩
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