Connecting core percolation and controllability of complex networks
11] Social Cognitive Networks Academic Research Center, Rensselaer Polytechnic Institute, Troy, NY, 12180 USA [2] Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, 12180 USA [3] Center for Complex Network Research and Department of Physics, Northeastern University, Boston, Massachusetts 02115, USA.
Scientific Reports
|June 21, 2014
Summary
Core percolation, a network transition, reveals how a network's core structure dictates its controllability. This study links core formation to control modes and robustness in complex networks.
Area of Science:
- Network science
- Statistical physics
- Control theory
Background:
- Core percolation is a critical structural transition in complex networks.
- Recent advances offer an analytical framework for core percolation in uncorrelated random networks with diverse degree distributions.
Purpose of the Study:
- To apply core percolation analytical tools to network controllability analysis.
- To investigate the relationship between core structure and network control modes.
- To derive analytical expressions for controllability robustness.
Main Methods:
- Utilizing the analytical framework of core percolation.
- Applying network controllability analysis techniques.
- Extending core percolation deductions to controllability robustness.
Main Results:
- Confirmed that the emergence of control bifurcation aligns with core formation.
- Demonstrated that the core structure determines the network's control mode.
- Derived analytical expressions for controllability robustness.
Conclusions:
- The study elucidates the interplay between complex network structure and dynamics.
- Findings provide insights into how core percolation influences network controllability and robustness.
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