title: Critical slowing down in networks generating temporal complexity.
abstract: We study a nonlinear Langevin equation describing the dynamic variable X(t), the mean field (order parameter) of a finite size complex network at criticality. The conditions under which the autocorrelation function of X shows any direct connection with criticality are discussed. We find that if the network is prepared in a state far from equilibrium, X(0)=1, the autocorrelation function is characterized by evident signs of critical slowing down as well as by significant aging effects, while the preparation X(0)=0 does not generate evident signs of criticality on X(t), in spite of the fact that the same initial state makes the fluctuating variable η(t)≡sgn(X(t)) yield significant aging effects. These latter effects arise because the dynamics of η(t) are directly dependent on crucial events, namely the re-crossings of the origin, which undergo a significant aging process with the preparation X(0)=0. The time scale dominated by temporal complexity, aging, and ergodicity breakdown of η(t) is properly evaluated by adopting the method of stochastic linearization which is used to explain the exponential-like behavior of the equilibrium autocorrelation function of X(t).
authors: Center for Nonlinear Science, University of North Texas, Denton, Texas 76203, USA.
authors: M T
authors: MT
authors: Beig
authors: Army Research Laboratory, 2800 Powder Mill Road, Adelphi, Maryland 20883, USA.
authors: A
authors: A
authors: Svenkeson
authors: Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 6-D, Arica, Chile.
authors: M
authors: M
authors: Bologna
authors: Information Sciences Directorate, Army Research Office, Research Triangle Park, North Carolina 27709, USA.
authors: B J
authors: BJ
authors: West
authors: Center for Nonlinear Science, University of North Texas, Denton, Texas 76203, USA.
authors: P
authors: P
authors: Grigolini