Steady-state distributions of probability fluxes on complex networks
Przemyslaw Chelminiak, Michal Kurzynski

TL;DR
This paper analyzes the statistical properties of probability fluxes in complex networks driven out of equilibrium by external forces, showing that their steady-state distributions are normally distributed with a standard deviation related to the flux and external force.
Contribution
It introduces a model of Markovian dynamics with an external transition (gate) on complex networks and demonstrates that flux distributions converge to a normal distribution regardless of network topology.
Findings
Flux distributions are normally distributed under external forcing.
Standard deviation of flux depends on the square root of the average flux.
Network modifications affect flux distribution parameters as predicted theoretically.
Abstract
The methodology based on the random walk processes is adapted and applied to a comprehensive analysis of the statistical properties of the probability fluxes. To this aim we define a simple model of the Markovian stochastic dynamics on a complex network extended by the additional transition, called hereafter the gate. The random skips through the gate, driven by the external constant force, violate the detailed balance in the network. We argue, using a theoretical approach and numerical simulations, that the stationary distributions of the probability fluxes emergent under such conditions converge, regardless of the network topology, to the normal distribution. This result, combined with the stationary fluctuation theorem, permits to show that its standard deviation depends directly on the square root of the average flux. In turn, the central result of our paper relates this quantity to…
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Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence · Advanced Thermodynamics and Statistical Mechanics
