Fragmentation transitions in a coevolving nonlinear voter model.

Sci Rep

IFISC, Instituto de Física Interdisciplinar y Sistemas Complejos (CSIC-UIB), Campus Universitat Illes Balears, E-07122, Palma, Spain.

Published: October 2017

AI Article Synopsis

  • This study investigates a nonlinear voter model that looks at how individual states and network structure evolve together.
  • The analysis reveals three distinct phases in a p,q parameter space: an active coexistence phase, an absorbing consensus phase, and an absorbing fragmented phase.
  • For larger systems, the active phase lasts significantly longer compared to the linear voter model, with unique transition lines indicating different types of phase changes.

Article Abstract

We study a coevolving nonlinear voter model describing the coupled evolution of the states of the nodes and the network topology. Nonlinearity of the interaction is measured by a parameter q. The network topology changes by rewiring links at a rate p. By analytical and numerical analysis we obtain a phase diagram in p,q parameter space with three different phases: Dynamically active coexistence phase in a single component network, absorbing consensus phase in a single component network, and absorbing phase in a fragmented network. For finite systems the active phase has a lifetime that grows exponentially with system size, at variance with the similar phase for the linear voter model that has a lifetime proportional to system size. We find three transition lines that meet at the point of the fragmentation transition of the linear voter model. A first transition line corresponds to a continuous absorbing transition between the active and fragmented phases. The other two transition lines are discontinuous transitions fundamentally different from the transition of the linear voter model. One is a fragmentation transition between the consensus and fragmented phases, and the other is an absorbing transition in a single component network between the active and consensus phases.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5634441PMC
http://dx.doi.org/10.1038/s41598-017-13047-2DOI Listing

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