Boolean Dynamics of Kauffman Models with a Scale-Free Network

Details Boolean Dynamics of Kauffman Models with a Scale-Free Network Boolean Dynamics of Kauffman Models with a Scale-Free Network

2005-10-17

arxiv.org/abs/cond-mat/0510430v3

Physics

Condensed Matter

Disordered Systems and Neural Networks

10 pages, 8 figures

Scientific paper

We study the Boolean dynamics of the "quenched" Kauffman models with a directed scale-free network, comparing with that of the original directed random Kauffman networks and that of the directed exponential-fluctuation networks. We have numerically investigated the distributions of the state cycle lengths and its changes as the network size $N$ and the average degree $$ of nodes increase. In the relatively small network ($N \sim 150$), the median, the mean value and the standard deviation grow exponentially with $N$ in the directed scale-free and the directed exponential-fluctuation networks with $ =2 $, where the function forms of the distributions are given as an almost exponential. We have found that for the relatively large $N \sim 10^3$ the growth of the median of the distribution over the attractor lengths asymptotically changes from algebraic type to exponential one as the average degree $$ goes to $ =2$. The result supports an existence of the transition at $_c =2$ derived in the annealed model.

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