Showing 1 - 10 of 14
We study the influence of the type of update functions on the evolution of Boolean networks under selection for dynamical robustness. The chosen types of functions are canalyzing functions and threshold functions. Starting from a random initial network, we evolve the network by an adaptive walk....
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We investigate Threshold Random Boolean Networks with K=2 inputs per node, which are equivalent to Kauffman networks, with only part of the canalyzing functions as update functions. According to the simplest consideration these networks should be critical but it turns out that they show a rich...
Persistent link: https://www.econbiz.de/10009280416
We evaluate the probability that a Boolean network returns to an attractor after perturbing h nodes. We find that the return probability as function of h can display a variety of different behaviours, which yields insights into the state-space structure. In addition to performing computer...
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A biologically motivated model for spatio-temporal coexistence of two competing species is studied by mean-field theory and numerical simulations. In d ≥2 dimensions the phase diagram displays an extended region where both species coexist, bounded by two second-order phase transition lines...
Persistent link: https://www.econbiz.de/10009281795
We study the interplay between surface roughening and phase separation during the growth of binary films. Renormalization group calculations are performed on a pair of equations coupling the interface height and order parameter fluctuations. We find a larger roughness exponent at the critical...
Persistent link: https://www.econbiz.de/10009282438
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A forest-fire model is introduced which contains a lightning probability f. This leads to a self-organized critical state in the limit f→0 provided that the time scales of free growth and burning down of forest clusters are separated. We derive scaling laws and calculate all critical...
Persistent link: https://www.econbiz.de/10011057653
We present a generalization of the forest-fire model of P. Bak et al. by including the immunity g which is the probability that a tree is not ignited although one of its neighbors is burning. When g reaches a critical value gc(p), which depends on the tree growth rate p, the fire cannot survive...
Persistent link: https://www.econbiz.de/10011063303