Azimuthal Anisotropy in High Energy Nuclear Collision - An Approach based on Complex Network Analysis

TL;DR

This paper introduces an extension of the Visibility Graph method to analyze azimuthal anisotropy in high-energy nuclear collisions, using complex network parameters to provide deterministic insights beyond traditional statistical fluctuation analysis.

Contribution

It presents a novel application of the Visibility Graph method to detect azimuthal anisotropy in nucleus-nucleus collision data by analyzing topological network parameters.

Findings

Average clustering coefficient varies with pseudorapidity regions.

Complex network analysis correlates with particle production phenomenology.

Method provides deterministic insights into azimuthal anisotropy.

Abstract

Recently, a complex network based method of Visibility Graph has been applied to confirm the scale-freeness and presence of fractal properties in the process of multiplicity fluctuation. Analysis of data obtained from experiments on hadron-nucleus and nucleus-nucleus interactions results in values of Power-of-Scale-freeness-of-Visibility-Graph-(PSVG) parameter extracted from the visibility graphs. Here, the relativistic nucleus-nucleus interaction data have been analysed to detect azimuthal-anisotropy by extending the Visibility Graph method and extracting the average clustering coefficient, one of the important topological parameters, from the graph. Azimuthal-distributions corresponding to different pseudorapidity-regions around the central-pseudorapidity value are analysed utilising the parameter. Here we attempt to correlate the conventional physical significance of this coefficient with respect to complex-network systems, with some basic notions of particle production phenomenology, like clustering and correlation. Earlier methods for detecting anisotropy in azimuthal distribution, were mostly based on the analysis of statistical fluctuation. In this work, we have attempted to find deterministic information on the anisotropy in azimuthal distribution by means of precise determination of topological parameter from a complex network perspective.