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

Mali, Provash; Manna, Sounik; Mukhopadhyay, A.; Haldar, Pallab Kanti; Singh, G.

doi:10.1016/j.physa.2017.10.015

Cited by 35 publications

(32 citation statements)

References 44 publications

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“…The first studied topological property is the degree centrality, one of the most widely used in several articles due to the simplicity of its computation and the information which provides about the nonlinear properties of time series [ 12 , 18 , 19 , 26 ]. This measure is defined as the number of edges,

, that each node

has in the network, i.e., the number of other nodes which node

sees.…”

Section: Methodsmentioning

confidence: 99%

Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs

Gómez-Gómez

Carmona-Cabezas

Sánchez‐López

et al. 2021

Entropy

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The last decades have been successively warmer at the Earth’s surface. An increasing interest in climate variability is appearing, and many research works have investigated the main effects on different climate variables. Some of them apply complex networks approaches to explore the spatial relation between distinct grid points or stations. In this work, the authors investigate whether topological properties change over several years. To this aim, we explore the application of the horizontal visibility graph (HVG) approach which maps a time series into a complex network. Data used in this study include a 60-year period of daily mean temperature anomalies in several stations over the Iberian Peninsula (Spain). Average degree, degree distribution exponent, and global clustering coefficient were analyzed. Interestingly, results show that they agree on a lack of significant trends, unlike annual mean values of anomalies, which present a characteristic upward trend. The main conclusions obtained are that complex networks structures and nonlinear features, such as weak correlations, appear not to be affected by rising temperatures derived from global climate conditions. Furthermore, different locations present a similar behavior and the intrinsic nature of these signals seems to be well described by network parameters.

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, that each node

has in the network, i.e., the number of other nodes which node

sees.…”

Section: Methodsmentioning

confidence: 99%

Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs

Gómez-Gómez

Carmona-Cabezas

Sánchez‐López

et al. 2021

Entropy

View full text Add to dashboard Cite

show abstract

“…Both the G q and the T q techniques have been applied extensively to analyze several high-energy nucleus-nucleus collision data [27][28][29][30][31][32][33][34][35]. Very recently some sophisticated methods have also been applied to study the fractal nature of multiparticle production process [36][37][38][39][40][41][42][43][44][45][46][47].…”

Section: Fractals-multifractals and Monofractalsmentioning

confidence: 99%

Multifractal Analysis of Charged Particle Multiplicity Distribution in the Framework of Renyi Entropy

Bhattacharyya

Neagu

Firu

2018

Advances in High Energy Physics

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A study of multifractality and multifractal specific heat has been carried out for the produced shower particles in nuclear emulsion detector for 16 O-AgBr, 28 Si-AgBr, and 32 S-AgBr interactions at 4.5AGeV/c in the framework of Renyi entropy. Experimental results have been compared with the prediction of Ultra-Relativistic Quantum Molecular Dynamics (UrQMD) model. Our analysis reveals the presence of multifractality in the multiparticle production process in high energy nucleus-nucleus interactions. Degree of multifractality is found to be higher for the experimental data and it increases with the increase of projectile mass. The investigation of quark-hadron phase transition in the multiparticle production in 16 O-AgBr, 28 Si-AgBr, and 32 S-AgBr interactions at 4.5 AGeV/c in the framework of Ginzburg-Landau theory from the concept of multifractality has also been presented. Evidence of constant multifractal specific heat has been obtained for both experimental and UrQMD simulated data.

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“…Recently, complex network based visibility graph method has been applied over data collected from π − -AgBr interaction at 350 GeV and 32 S-AgBr interaction at 200A GeV, and then by analysing the Power of Scale-freeness of Visibility Graph (PSVG) [28,29,37] parameter extracted from the graphs, the scale-freeness and fractal properties of the process of particle production have been established [30,31]. Mali et al have applied visibility, horizontal visibility graphs and the sandbox algorithm to analyse multiparticle emission data in high-energy nucleus-nucleus collisions in [38,39]. The topological parameters of the visibility graphs have their usual significance with respect to the complex network systems.…”

Section: Introductionmentioning

confidence: 99%

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

Bhaduri

Ghosh

2018

Advances in High Energy Physics

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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 nucleusnucleus 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.

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

Cited by 35 publications

References 44 publications

Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs

Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs

Multifractal Analysis of Charged Particle Multiplicity Distribution in the Framework of Renyi Entropy

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

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