Complexity, information transfer and collective behavior in chaotic dynamical networks (1010.4810v1)

Abstract: We investigate the relationship between complexity, information transfer and the emergence of collective behaviors, such as synchronization and nontrivial collective behavior, in a network of globally coupled chaotic maps as a simple model of a complex system. We calculate various quantities for this system: the mean field, a measure of statistical complexity, the information transfer, as well as the information shared, between the macroscopic and local levels as functions of the strength of a coupling parameter in the system. Our results show that the emergence of nontrivial collective behavior is associated to higher values of complexity. Little transference of information from the global to the local level occurs when the system settles into nontrivial collective behavior while no information at all flows between these two scales in a synchronized collective state. As the parameter values for the onset of nontrivial collective behavior or chaos synchronization are approached, the information transfer from the macroscopic level to the local level is higher, in comparison to the situation where those collective states are already established in the system. Our results add support to the view of complexity as an emergent collective property that is absent at the local level in systems of interacting elements.