Fig. 2: Behaviors of MR model.
From: Non-Markovian recovery makes complex networks more resilient against large-scale failures
a Probability Et([I]) in the mean-field theory [Eq. (4)] as a function of [I]. b Dependence of [I] on β1 in the steady state for β2 = 2.0, μ1 = 0.01, and μ2 = 1. The high-failure (solid curve) and low-failure (dashed curve) branches are calculated by the mean-field theory. The simulation data are obtained by swabbing β1 up and down in step of 0.002, starting with [I]0 = 0 for β1 = 0. The final state of a value of β1 is used as the initial state of the simulations for the next value of β1. The arrows indicate the simulation results when the value of β1 moves up and down. c Phase diagram on the β2/μ2-β1/μ1 plane as predicted by the mean-field theory. Systems in the bistable phase will evolve either to a high-failure or a low-failure phase depending on the initial conditions. Beyond the critical point, there is no distinction between the low-failure and high-failure phases.
