2009
DOI: 10.1016/j.physa.2009.07.038
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Generalized superstatistics of nonequilibrium Markovian systems

Abstract: a b s t r a c tThe paper is devoted to the construction of the superstatistical description for nonequilibrium Markovian systems. It is based on Kirchhoff's diagram technique and the assumption on the system under consideration to possess a wide variety of cycles with vanishing probability fluxes. The latter feature enables us to introduce equivalence classes called channels within which detailed balance holds individually. Then stationary probability as well as flux distributions are represented as some sums … Show more

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Cited by 5 publications
(2 citation statements)
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References 75 publications
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“…Formal solutions have been formulated for general dimensions, which so far could only be evaluated for the 1D case 25 . For electron hopping transport in disordered semiconductors the population of states can be characterized by a field-dependent effective temperature 26,27 .…”
Section: Introductionmentioning
confidence: 99%
“…Formal solutions have been formulated for general dimensions, which so far could only be evaluated for the 1D case 25 . For electron hopping transport in disordered semiconductors the population of states can be characterized by a field-dependent effective temperature 26,27 .…”
Section: Introductionmentioning
confidence: 99%
“…Superstatistics is applicable to various complex systems. Its applications include, among others, cosmicray energy spectra and electron-positron pair annihilation [6,7], the world line representations of Feynman propagators for spin-0 and spin-1/2 particles [8], an extension of the random matrix theory covering systems with mixed regular-chaotic dynamics [9][10][11], nonstationary dynamical processes with time-varying multiplicative noise exponents [12], Markovian systems without detailed balance [13], a mesoscopic approach to the problem of Brownian motion [14], models of the metastatic cascade in cancerous systems [15], complex networks [16], ecosystems driven by hydroclimatic fluctuations [17], patternforming systems [18], solar flares [19], share price fluctuations [20][21][22][23], the statistics of train departure delays [24], wind velocity fluctuations [25], and many interesting applications in hydrodynamic turbulence [23,[26][27][28][29][30].…”
Section: Introductionmentioning
confidence: 99%