Low-dimensional dynamics in observables from complex and higher-dimensional systems

M S Baptista, I L Caldas, M S Baptista, C S Baptista, A A Ferreira, M V A P Heller

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8 Citations (Scopus)

Abstract

We analyze fluctuating observables of high-dimensional systems as the New York Stock Market S&P 500 index, the amino-acid sequence in the M. genitalium DNA, the maximum temperature of the San Francisco Bay area, and the toroidal magneto plasma potential. The probability measures of these fluctuations are obtained by the statistical analysis of a rescaling combination of the first Poincare return time of a low-dimensional chaotic system. This result indicates that it is possible to use a measure of a low-dimensional chaotic attractor to describe a measure of these complex systems. Moreover, within this description we determine scaling power laws for average measurements of the analyzed fluctuations. (C) 2000 Elsevier Science B.V. All rights reserved.

Original languageEnglish
Pages (from-to)91-99
Number of pages9
JournalPhysica. A, Statistical Mechanics and its Applications
Volume287
Issue number1-2
Early online date30 Oct 2000
DOIs
Publication statusPublished - 15 Nov 2000

Keywords

  • chaos
  • econophysics
  • stock market
  • DNA
  • turbulence
  • modeling
  • transport
  • weather

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