Nonlinear Sciences – Adaptation and Self-Organizing Systems
Scientific paper
2002-07-09
Nonlinear Sciences
Adaptation and Self-Organizing Systems
24 pages, 9 figures, Submitted to the Journal of Statistical Physics
Scientific paper
In this work we analyze the stochastic dynamics of the Kauffman model evolving under the influence of noise. By considering the average crossing time between two distinct trajectories, we show that different Kauffman models exhibit a similar kind of behavior, even when the structure of their basins of attraction is quite different. This can be considered as a robust property of these models. We present numerical results for the full range of noise level and obtain approximate analytic expressions for the above crossing time as a function of the noise in the limit cases of small and large noise levels.
Aldana Maximino
Kadanoff Leo P.
Qu Xiaofei
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