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Related Experiment Video

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Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
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Reentrant phase transitions in threshold driven contagion on multiplex networks.

Samuel Unicomb1, Gerardo Iñiguez2,3,4, János Kertész2

  • 1Université de Lyon, ENS de Lyon, INRIA, CNRS, UMR 5668, IXXI, F-69364 Lyon, France.

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Threshold contagion models on complex networks can remain susceptible to global cascades, even with high connectivity. Heterogeneous multiplex networks exhibit reentrant phase transitions, explaining large-scale contagion in connected, complex systems.

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Area of Science:

  • Complex Systems Science
  • Network Science
  • Epidemiology
  • Sociology
  • Finance

Background:

  • Threshold driven contagion models explain cascading phenomena across various networks (social, financial, biological).
  • Existing models predict network resistance to global cascades at high connectivity in single-layer, unweighted networks.
  • This prediction contradicts empirical observations of widespread contagion in highly connected, complex networks.

Purpose of the Study:

  • To investigate threshold driven contagion dynamics on weight-heterogeneous multiplex networks.
  • To determine if such networks can remain susceptible to global cascades irrespective of connectivity levels.
  • To explain the occurrence of large-scale contagion in highly connected yet heterogeneous network structures.

Main Methods:

  • Theoretical modeling of threshold driven contagion.
  • Analysis of contagion spread on multiplex networks with heterogeneous edge weights.
  • Examination of network susceptibility to global cascades as a function of connectivity and edge density.

Main Results:

  • Weight-heterogeneous multiplex networks remain susceptible to global cascades at all connectivity levels.
  • Increasing edge density leads to alternating phases of stability and instability.
  • Reentrant phase transitions of contagion are observed, characterized by cycles of stability and instability.

Conclusions:

  • Multiplexity and weight heterogeneity are critical factors in contagion dynamics.
  • These network properties provide a theoretical basis for observing large-scale cascades in highly connected, complex systems.
  • The findings challenge previous assumptions about network resistance to contagion based solely on connectivity.