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Giulia Bertagnolli1, Manlio De Domenico2

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Summary
This summary is machine-generated.

This study extends diffusion geometries to multilayer networks using diverse random walk dynamics. It reveals how different search strategies shape network geometry, offering new insights into complex system organization.

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Area of Science:

  • Network Science
  • Complex Systems
  • Mathematical Physics

Background:

  • Complex networks exhibit inherent geometries influenced by topology and dynamics.
  • Random walks, modeling various processes, define diffusion geometries to reveal network organization.
  • Existing methods struggle with real-world networks containing isolated or disconnected components.

Purpose of the Study:

  • To extend the concept of diffusion geometries to multilayer networks.
  • To incorporate diverse random walk dynamics, including local and nonlocal information.
  • To overcome limitations of existing methods in handling disconnected network components.

Main Methods:

  • Developing a framework for diffusion geometries on multilayer networks.
  • Implementing various random walk dynamics (local and nonlocal) on these networks.
  • Analyzing synthetic and empirical multilayer network data.

Main Results:

  • The study successfully extends diffusion geometries to multilayer networks.
  • Different random walk dynamics demonstrably shape distinct geometric features.
  • The approach effectively handles networks with isolated nodes and disconnected components.

Conclusions:

  • Diffusion geometries provide a powerful geometric perspective on multilayer network organization.
  • The choice of random walk dynamics significantly influences the emergent network geometry.
  • This framework offers a robust method for analyzing complex systems across various domains.