Multifractal analysis of multiparticle emission data in the framework of visibility graph and sandbox algorithm

P. Mali, S.K. Manna, A. Mukhopadhyay, P.K. Haldar and G. Singh

Physica A: Statistical Mechanics and its Applications, 2018, vol. 493, issue C, 253-266

Abstract: Multiparticle emission data in nucleus–nucleus collisions are studied in a graph theoretical approach. The sandbox algorithm used to analyze complex networks is employed to characterize the multifractal properties of the visibility graphs associated with the pseudorapidity distribution of charged particles produced in high-energy heavy-ion collisions. Experimental data on 28Si+Ag/Br interaction at laboratory energy Elab=14.5A GeV, and 16O+Ag/Br and 32S+Ag/Br interactions both at Elab=200A GeV, are used in this analysis. We observe a scale free nature of the degree distributions of the visibility and horizontal visibility graphs associated with the event-wise pseudorapidity distributions. Equivalent event samples simulated by ultra-relativistic quantum molecular dynamics, produce degree distributions that are almost identical to the respective experiment. However, the multifractal variables obtained by using sandbox algorithm for the experiment to some extent differ from the respective simulated results.

Keywords: High-energy heavy-ion collisions; Visibility graph and sandbox methods; Degree distribution of visibility graph; Multifractality and long-range correlation (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:493:y:2018:i:c:p:253-266

DOI: 10.1016/j.physa.2017.10.015

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