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Cascading failures in scale-free interdependent networks.

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Understanding network cascades is crucial for system resilience. This study reveals that specific network structures, including scale-free degree distribution and assortativity, are essential for minimizing large cascade sizes in complex systems.

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Area of Science:

  • Complex Systems Science
  • Network Science
  • Statistical Physics

Background:

  • Large cascades are prevalent in natural and engineered complex systems.
  • Understanding cascade propagation is vital for system robustness.

Purpose of the Study:

  • To investigate cascade propagation across realistic multilayer network topologies.
  • To identify key network properties that mitigate large cascade sizes.

Main Methods:

  • Utilized the Bak-Tang-Wiesenfeld sandpile model.
  • Employed realistic network topologies with heterogeneous degree distributions.
  • Analyzed intra- and interlayer degree correlations.

Main Results:

  • Scale-free degree distribution, internal network assortativity, and cross-network hub-to-hub connections are necessary to reduce large cascade sizes.
  • Network structure correlations significantly influence dynamical cascading processes.
  • Correlations can prevent failure propagation across connected network layers.

Conclusions:

  • Multilayer network topology plays a critical role in cascade dynamics.
  • Optimizing internal and cross-network structures enhances the robustness of interconnected systems.