Random walker's view of networks whose growth it shapes
Robert J H Ross1, Charlotte Strandkvist1, Walter Fontana1
1Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts 02115, USA.
Physical Review. E
|July 24, 2019
Summary
This study introduces a network growth model driven by random walkers. Walker movement influences network structure, revealing a relationship between walker motility and average node degree.
Area of Science:
- Network science
- Computational modeling
- Statistical physics
Background:
- Understanding network formation is crucial in various scientific domains.
- Existing models often simplify the dynamics of growth and node attachment.
- The role of mobile agents in shaping network topology requires further investigation.
Purpose of the Study:
- To develop a simple model for network growth driven by random walkers.
- To explore how walker motility influences the resulting network structures.
- To investigate the relationship between walker behavior and network properties like average degree.
Main Methods:
- Simulating a network growth model with one or more random walkers.
- Varying the motility rate of the walkers.
- Analyzing the emergent network structures and calculating the average degree experienced by walkers.
Main Results:
- The model generates a spectrum of network structures based on walker motility.
- The average degree observed by a walker is directly dependent on its motility rate.
- Modulating walker influence on node attachment creates new limiting behaviors.
Conclusions:
- Walker motility is a key parameter controlling network growth and topology.
- The model provides a framework for understanding emergent network complexity.
- Further research is needed to explore the energetic and computational costs of such models in physical systems.
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