Critical slowing down in networks generating temporal complexity

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 n(t) = sgn(X(t)) yield significant aging effects. These latter effects arise because the dynamics of n(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 n(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).