Dimension reduction of noisy interacting systems

We consider a class of models describing an ensemble of identical interacting agents subject to multiplicative noise. In the thermodynamic limit, these systems exhibit continuous and discontinuous phase transitions in a, generally, nonequilibrium setting. We provide a systematic dimension reduction methodology for constructing low dimensional, reduced-order dynamics based on the cumulants of the probability distribution of the infinite system. We show that the stationary properties of the reduced dynamics yield a quantitatively accurate representation of the stationary phase diagram of the system by comparing it with exact analytical results and numerical simulations. Moreover, we test the accuracy of the reduced dynamics in representing the response of the system to perturbations and show that phase transitions are associated with the breakdown of linear response operators and the emergence of poles in the susceptibility for real values of the frequency