Analysis of Trajectory Entropy for Continuous Stochastic Processes at Equilibrium

ABSTRACT: The analytical expression for the trajectory entropy of the overdamped Langevin equation is derived via two approaches. The first route goes through the Fokker−Planck equation that governs the propagation of the conditional probability density, while the second method goes through the path integral of the Onsager− Machlup action. The agreement of these two approaches in the continuum limit underscores the equivalence between the partial differential equation and the path integral formulations for stochastic processes in the context of trajectory entropy. The values obtained using the analytical expression are also compared with those calculated with numerical solutions for arbitrary time resolutions of the trajectory. Quantitative agreement is clearly observed consistently across different models as the time interval between snapshots in the trajectories decreases. Furthermore, analysis of different scenarios illustrates how the deterministic and stochastic forces in the Langevin equation contribute to the variation in dynamics measured by the trajectory entropy. Consider very generally a system that interacts with its environment and evolves over time. Let x be some continuou