Boolean dynamics of Kauffman models with a scale-free network

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 〈k〉 of nodes increase. In the relatively small network (N∼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 〈k〉=2, where the function forms of the distributions are given as an almost exponential. We have found that for the relatively large N∼103 the growth of the median of the distribution over the attractor lengths asymptotically changes from algebraic type to exponential one as the average degree 〈k〉 goes to 〈k〉=2. The result supports the existence of the transition at 〈k〉c=2 derived in the annealed model.