Critical dynamics of randomly assembled and diluted threshold networks
1Fakultät für Physik, Universität Wien, Austria and Department of Physics, Loughborough University, LE11 3TU, United Kingdom.
Summary
Randomly assembled networks with connection deletion exhibit stable dynamics when using power-law distributions. This finding is crucial for understanding complex network behavior and neural development.
Area of Science:
- Complex systems
- Network science
- Computational neuroscience
Background:
- Understanding the dynamics of randomly assembled networks is crucial.
- The impact of connection deletion on network stability is not fully understood.
- Previous models often assumed fixed network structures.
Purpose of the Study:
- To investigate the dynamical behavior of randomly assembled networks with random connection deletion.
- To construct a dynamical phase diagram for these networks.
- To explore the role of connection strength distributions in network stability.
Main Methods:
- Utilized the annealed approximation, suitable for the thermodynamic limit.
- Constructed dynamical phase diagrams.
- Analyzed various probability density distributions for connection strengths, focusing on power-law functions.
Main Results:
- Identified power-law distribution functions as key to expanding stable dynamics.
- Demonstrated that power-law distributions favor ordered dynamics over chaotic phases.
- Explored relationships with studies on networks featuring variable in-degree.
Conclusions:
- Power-law distributions enhance the stability of randomly assembled networks with connection pruning.
- The findings have implications for neural modeling and developmental neurobiology.
- Network pruning and connection strength distribution significantly influence dynamical behavior.
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