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Complex networks derived from cellular automata
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.Comment: 10 pages, 8 figure
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