Controllability and Observability
Analysis of how edge removal impacts controllability and observability in complex networks using maximum matching theory.
Problem
How does structural damage affect the controllability and observability of complex networks? In particular, how does progressively removing edges change the number of driver nodes required to control the system?
Approach
The project analyzes structural controllability using maximum matching theory. Networks are progressively degraded via edge pruning, and the resulting changes in required driver nodes are tracked across different removal strategies.
Core Components
- Structural controllability via maximum matching
- Edge pruning strategies and vulnerability analysis
- Driver node identification
- Controllability degradation curves
- Network robustness interpretation
Impact
The analysis reveals that many networks are initially robust to edge removal but exhibit sharp transitions where controllability rapidly degrades. Targeted removal can break controllability much more efficiently than diffuse random damage.
Technical Note
The interactive pruning demo and the more detailed technical discussion now live in the writing section, alongside the other project notes.
Tools and Methods
- Network Science
- Graph Theory
- Structural Controllability
- Maximum Matching
- Complex Systems