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Stochastic dynamical systems always undergo trending mechanisms of transition to criticality

Denis M. Filatov and Alexey A. Lyubushin

Physica A: Statistical Mechanics and its Applications, 2019, vol. 527, issue C

Abstract: We study diverse mechanisms of the transition of stochastic dynamical systems to critical states. We begin from employing two independent quantitative methods of time series analysis, first-order detrended fluctuation analysis and multivariate canonical coherence analysis, and investigate GPS data of land surface displacements. We find out that there are two different mechanisms of the transition to criticality: the first mechanism is consistent with that observed in some biological dynamical systems and associated with a growth of the energies at low frequencies in the power spectrum, whereas the second mechanism is new and governed by a decay of the energies at high frequencies. Despite this difference, we show that both mechanisms lead to a loss of chaoticity in the system’s behavior and result in a more deterministic evolution of the system as a whole. Basing on these findings, we develop a multivariate stochastic model that qualitatively explains both empirically observed mechanisms. The obtained results allow to pose a hypothesis that, in spite of the spread understanding, in stochastic dynamical systems of any nature the transition to a critical state is always realized through a trending nonlinear process that has nothing to do with purely random dynamics.

Keywords: Stochastic dynamical systems; Fractal analysis of time series; Coherence analysis; Collective behavior; Critical states; Mechanisms of transition to criticality; Loss of complexity/chaoticity (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119307745

DOI: 10.1016/j.physa.2019.121309

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