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DY: Fachverband Dynamik und Statistische Physik

DY 30: Networks IV (with SOE)

DY 30.6: Vortrag

Freitag, 30. März 2012, 11:15–11:30, MA 001

Self-organized critical adaptive networks — •Matthias Rybarsch and Stefan Bornholdt — Institut für Theoretische Physik, Universität Bremen, Otto-Hahn-Allee, 28359 Bremen

Dynamical systems of spins on a network can exhibit self-regulated evolution towards a critical state and are used as toy models for self-tuning in biological neural networks [1]. If, however, the model is changed from spin type to a network composed of Boolean state nodes which are more plausible in the biological context [2], this rewiring algorithm will no longer evolve the system to criticality and cannot be directly transferred in a simple way. Also, the function of such self-organized networks is often limited to a certain network topology like a regular lattice in case of ref. [1]. Here, we discuss a correlation-dependent mechanism for self-organized connectivity evolution which adresses these difficulties and evolves a biologically motivated, yet minimalistic network model to an average connectivity close to criticality in terms of damage spreading, both on lattice or random network topology.

[1] S. Bornholdt and T. Roehl: Self-organized critical neural networks, Phys. Rev. E 67, 066118 (2003)

[2] M. Rybarsch and S. Bornholdt: On the dangers of Boolean networks: Activity dependent criticality and threshold networks not faithful to biology, arXiv:1012.3287 (2010)