Characterizing Full Nonequilibrium Dynamics of Simple Exclusion Processes

Abstract

The simple exclusion process (SEP) is a paradigmatic model for nonequilibrium transport, yet the rich dynamics of its time-dependent joint distribution over an exponentially large configuration space remain notoriously intractable. Here, we leverage variational autoregressive networks to systematically characterize the nonequilibrium dynamics of symmetric (SSEP), asymmetric (ASEP), and totally asymmetric (TASEP) cases from one to three dimensions. We first validate the approach by reproducing the previous finite-time results for the 1D SSEP and long-time tensor-network results for the 2D SSEP, and then provide richer finite-time dynamics of the SSEP, ASEP, and TASEP in 1D and 2D, and a new finite-time analysis in 3D. Specifically, in 1D, we reveal that finite-time dynamical-activity maps directly correspond to the classical three-phase TASEP steady-state organization, and, in the long-time limit, boundary and bulk effects separately govern the dynamical susceptibility during the crossover from diffusive to ballistic transport. In 2D, we establish a mean-field directional-density criterion, supported by our neural-network calculations, and show that long-time boundary and bulk effects mirror their 1D counterparts. In 3D, we uncover new finite-time scaling relations for the active-inactive phase transition of the SSEP, and reveal a broadly consistent scaling exponent of the phase-transition point versus system size, implying that the phase-transition point is asymptotically controlled by the characteristic length scale ($s_c\sim L^{-2}$) regardless of dimension. This work thus establishes a unified framework for characterizing the nonequilibrium dynamics of representative transport systems.