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Universal framework for edge controllability of complex networks.

Shao-Peng Pang1,2, Wen-Xu Wang3,4, Fei Hao5,6

  • 1The Seventh Research Division, School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China.

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|June 28, 2017
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Summary
This summary is machine-generated.

This study introduces a universal framework for edge controllability in complex networks. It reveals that interaction strength, not just network structure, significantly impacts control, with specific network types showing higher controllability.

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Area of Science:

  • Network Science
  • Control Theory
  • Systems Biology

Background:

  • Dynamical processes on network edges are crucial in many real-world systems.
  • Existing frameworks lack universality for arbitrary network structures and interaction strengths.
  • A comprehensive theory for edge controllability is needed.

Purpose of the Study:

  • To develop a universal framework for edge controllability in complex networks.
  • To identify critical nodes for control and derive controllability bounds.
  • To analyze the influence of network structure and interaction strength on controllability.

Main Methods:

  • Generalizing switchboard dynamics for edge processes.
  • Applying exact controllability theory to develop a universal framework.
  • Analyzing local weighted network structure for node controllability.

Main Results:

  • Node controllability is determined solely by local weighted structure.
  • Identified critical nodes and derived analytic formulas for controllability bounds.
  • Interaction strength plays a more significant role than network structure in edge controllability.

Conclusions:

  • The developed framework provides a universal approach to edge controllability.
  • Transcriptional regulatory networks and electronic circuits exhibit higher strong structural controllability (SSC).
  • Directed and sparse networks generally demonstrate greater SSC than undirected and dense networks.