Emergence of Symmetry in Complex Networks

Abstract

Many real networks have been found to have a rich degree of symmetry, which is a very important structural property of complex network, yet has been rarely studied so far. And where does symmetry comes from has not been explained. To explore the mechanism underlying symmetry of the networks, we studied statistics of certain local symmetric motifs, such as symmetric bicliques and generalized symmetric bicliques, which contribute to local symmetry of networks. We found that symmetry of complex networks is a consequence of similar linkage pattern, which means that nodes with similar degree tend to share similar linkage targets. A improved version of BA model integrating similar linkage pattern successfully reproduces the symmetry of real networks, indicating that similar linkage pattern is the underlying ingredient that responsible for the emergence of the symmetry in complex networks.

7 pages, 7 figures

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• Does the brain behave like a (complex) network? I. Dynamics
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• Structural Inference of Networked Dynamical Systems with Universal Differential Equations
• The rigorous solution for the average distance of a Sierpinski network
• Approximate Network Symmetry
• Gene regulatory and signalling networks exhibit distinct topological distributions of motifs
• Graph Iso/Auto-morphism: A Divide-&-Conquer Approach