Time-Scale and Noise Optimality in Self-Organized Critical Adaptive Networks

Christian Kuehn

doi:10.1103/physreve.85.026103

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arXiv · 1110.5433

Time-Scale and Noise Optimality in Self-Organized Critical Adaptive Networks

Christian Kuehn

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Abstract

Recent studies have shown that adaptive networks driven by simple local rules can organize into "critical" global steady states, providing another framework for self-organized criticality (SOC). We focus on the important convergence to criticality and show that noise and time-scale optimality are reached at finite values. This is in sharp contrast to the previously believed optimal zero noise and infinite time scale separation case. Furthermore, we discover a noise induced phase transition for the breakdown of SOC. We also investigate each of the three new effects separately by developing models. These models reveal three generically low-dimensional dynamical behaviors: time-scale resonance (TR), a new simplified version of stochastic resonance - which we call steady state stochastic resonance (SSR) - as well as noise-induced phase transitions.

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BibTeX RIS

Christian Kuehn. 2011-12-23. Time-Scale and Noise Optimality in Self-Organized Critical Adaptive Networks. https://doi.org/10.1103/physreve.85.026103

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