Attractor period distribution for critical Boolean networks
classification
❄️ cond-mat.dis-nn
keywords
argumentsattractornetworksanalyticattractorsbooleancomponentscritical
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Using analytic arguments, we show that dynamical attractor periods in large critical Boolean networks are power-law distributed. Our arguments are based on the method of relevant components, which focuses on the behavior of the nodes that control the dynamics of the entire network and thus determine the attractors. Assuming that the attractor period is equal to the least common multiple of the size of all relevant components, we show that the distribution in large networks is well approximated by a power-law with an exponent of -1. Numerical evidence based on sampling of attractors supports the conclusions of our analytic arguments.
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