2010/09/23 by Yoshihiko Kayama, Kayama, Yoshihiko
Computer Science · Physics and Astronomy · #Cellular Automata and Applications #Cellular Automata and Lattice Gases (nlin.CG) #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Physical sciences #Mathematical Physics (math-ph) #Opinion Dynamics and Social Influence #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1009.4509
openalex publication_date 2010/09/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose a method for deriving networks from one-dimensional binary cellular automata. The derived networks are usually directed and have structural properties corresponding to the dynamical behaviors of their cellular automata. Network parameters, particularly the efficiency and the degree distribution, show that the dependence of efficiency on the grid size is characteristic and can be used to classify cellular automata and that derived networks exhibit various degree distributions. In particular, a class IV rule of Wolfram's classification produces a network having a scale-free distribution.