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Temporal correlations in the Vicsek model with vectorial noise

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  • Gulich, Damián
  • Baglietto, Gabriel
  • Rozenfeld, Alejandro F.

Abstract

We study the temporal correlations in the evolution of the order parameter ϕt for the Vicsek model with vectorial noise by estimating its Hurst exponent H with detrended fluctuation analysis (DFA). We present results on this parameter as a function of noise amplitude η introduced in simulations. We also compare with well known order–disorder phase transition for that same noise range. We find that – regardless of detrending degree – H spikes at the known coexistence noise for phase transition, and that this is due to nonstationarities introduced by the transit of the system between two well defined states with lower exponents. We statistically support this claim by successfully synthesizing equivalent cases derived from a transformed fractional Brownian motion (TfBm).

Suggested Citation

  • Gulich, Damián & Baglietto, Gabriel & Rozenfeld, Alejandro F., 2018. "Temporal correlations in the Vicsek model with vectorial noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 590-604.
    • Handle: RePEc:eee:phsmap:v:502:y:2018:i:c:p:590-604
    DOI: 10.1016/j.physa.2018.02.094
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    1. Longfeng Zhao & Wei Li & Chunbin Yang & Jihui Han & Zhu Su & Yijiang Zou, 2017. "Multifractality and Network Analysis of Phase Transition," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.
    2. Czarnecki, Łukasz & Grech, Dariusz & Pamuła, Grzegorz, 2008. "Comparison study of global and local approaches describing critical phenomena on the Polish stock exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6801-6811.
    3. Solé, Ricard V. & Valverde, Sergi, 2001. "Information transfer and phase transitions in a model of internet traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(3), pages 595-605.
    4. Bashan, Amir & Bartsch, Ronny & Kantelhardt, Jan W. & Havlin, Shlomo, 2008. "Comparison of detrending methods for fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5080-5090.
    5. Gulich, Damián & Zunino, Luciano, 2014. "A criterion for the determination of optimal scaling ranges in DFA and MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 17-30.
    6. V. Manías & J. Candia & E. V. Albano, 2005. "Corner wetting in a far-from-equilibrium magnetic growth model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 47(4), pages 563-570, October.
    7. Ludescher, Josef & Bogachev, Mikhail I. & Kantelhardt, Jan W. & Schumann, Aicko Y. & Bunde, Armin, 2011. "On spurious and corrupted multifractality: The effects of additive noise, short-term memory and periodic trends," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(13), pages 2480-2490.
    8. Amir Bashan & Ronny Bartsch & Jan W. Kantelhardt & Shlomo Havlin, 2008. "Comparison of detrending methods for fluctuation analysis," Papers 0804.4081, arXiv.org.
    9. Grech, Dariusz & Pamuła, Grzegorz, 2008. "The local Hurst exponent of the financial time series in the vicinity of crashes on the Polish stock exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4299-4308.
    10. Grech, Dariusz & Mazur, Zygmunt, 2013. "On the scaling ranges of detrended fluctuation analysis for long-term memory correlated short series of data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2384-2397.
    11. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    12. Kantelhardt, Jan W & Koscielny-Bunde, Eva & Rego, Henio H.A & Havlin, Shlomo & Bunde, Armin, 2001. "Detecting long-range correlations with detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 441-454.
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