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Multifractal detrended fluctuation analysis of particle density fluctuations in high-energy nuclear collisions

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  • Mali, P.
  • Sarkar, S.
  • Ghosh, S.
  • Mukhopadhyay, A.
  • Singh, G.

Abstract

The detrended fluctuation analysis (DFA) and the multifractal DFA (MF-DFA) techniques are employed to characterize the pseudorapidity (η) distribution of charged mesons produced in 28Si+Ag/Br interaction at 14.5 GeV/nucleon and 32S+Ag/Br interaction at 200 GeV/nucleon. Various multifractal parameters are calculated and compared with a Monte-Carlo simulation based on the ultra-relativistic quantum molecular dynamics (UrQMD) model. The results of this analysis show that the single particle distributions in both experiments and in their respective UrQMD simulations are multifractal in nature. The differences between the experiment and corresponding simulation however, are not always very significant. But the present results are significantly different from those obtained by using other conventional methods of multifractal analysis. The observations also indicate that the detrended multifractal analysis might be an efficient tool for characterizing the multiparticle emission data, but the method requires some improvement so that it can differentiate between the non-statistical signal and the statistical noise.

Suggested Citation

  • Mali, P. & Sarkar, S. & Ghosh, S. & Mukhopadhyay, A. & Singh, G., 2015. "Multifractal detrended fluctuation analysis of particle density fluctuations in high-energy nuclear collisions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 25-33.
    • Handle: RePEc:eee:phsmap:v:424:y:2015:i:c:p:25-33
    DOI: 10.1016/j.physa.2014.12.037
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    References listed on IDEAS

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    5. Wang, Yudong & Liu, Li & Gu, Rongbao, 2009. "Analysis of efficiency for Shenzhen stock market based on multifractal detrended fluctuation analysis," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 271-276, December.
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    Cited by:

    1. Lahmiri, Salim, 2017. "Multifractal analysis of Moroccan family business stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 183-191.
    2. Alvarez-Ramirez, J. & Rodriguez, E., 2018. "AR(p)-based detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 49-57.
    3. Mali, P. & Manna, S.K. & Haldar, P.K. & Mukhopadhyay, A. & Singh, G., 2017. "Detrended analysis of shower track distribution in nucleus-nucleus interactions at CERN SPS energy," Chaos, Solitons & Fractals, Elsevier, vol. 94(C), pages 86-94.
    4. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    5. Mali, Provash & Mukhopadhyay, Amitabha & Singh, Gurmukh, 2016. "Multifractal detrended moving average analysis of particle density functions in relativistic nuclear collisions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 323-332.

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