Exact Coupling Threshold for Structural Transition in Interconnected Networks

Abstract

Interconnected networks are mathematical representation of systems where two or more simple networks are coupled to each other. Depending on the coupling weight between the two components, the interconnected network can function in two regimes: one where the two networks are structurally distinguishable, and one where they are not. The coupling threshold--denoting this structural transition--is one of the most crucial concepts in interconnected networks. Yet, current information about the coupling threshold is limited. This letter presents an analytical expression for the exact value of the coupling threshold and outlines network interrelation implications.

References in corpus (7)

• Cooperative Game Theory Approaches for Network Partitioning
• Synchronization in complex networks
• The structure and dynamics of multilayer networks
• Diffusion dynamics on multiplex networks
• Synchronization of interconnected networks: the role of connector nodes
• Laplacian spectra of complex networks and random walks on them: Are scale-free architectures really important?
• Multiplexity versus correlation: the role of local constraints in real multiplexes

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