Extreme variability in convergence to structural balance in frustrated dynamical systems

Abstract

In many complex systems, the dynamical evolution of the different components can result in adaptation of the connections between them. We consider the problem of how a fully connected network of discrete-state dynamical elements which can interact via positive or negative links, approaches structural balance by evolving its links to be consistent with the states of its components. The adaptation process, inspired by Hebb's principle, involves the interaction strengths evolving in accordance with the dynamical states of the elements. We observe that in the presence of stochastic fluctuations in the dynamics of the components, the system can exhibit large dispersion in the time required for converging to the balanced state. This variability is characterized by a bimodal distribution, which points to an intriguing non-trivial problem in the study of evolving energy landscapes.

6 pages, 4 figures

References in corpus (7)

• Critical phenomena in complex networks
• Structure and tie strengths in mobile communication networks
• Adaptive Coevolutionary Networks: A Review
• Community detection in networks with positive and negative links
• Dynamics of Social Balance on Networks
• Active influence in dynamical models of structural balance in social networks
• Phase of Ising spins on modular networks analogous to social polarization

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