White-noise fluctuation theorem for Langevin dynamics

Abstract

Fluctuation theorems (FTs) based on time-reversal have provided remarkable insight into the non-equilibrium statistics of thermodynamic quantities like heat, work, and entropy production. These types of laws impose constraints on the distributions of certain trajectory functionals that reflect underlying dynamical symmetries. In this work, we introduce a detailed FT for Langevin dynamics that follows from the statistics of Gaussian white noise rather than from time-reversal. The theorem, which originates from a point-wise symmetry in phase space, holds individually for each degree of freedom coupled to additive or multiplicative noise. The relation is independent of the phase space distribution generated by the dynamics and can be used to derive a versatile parameter inference algorithm applicable to the a wide range of systems, including non-conservative and non-Markovian ones.

Keywords

• fluctuation theorems
• stochastic thermodynamics
• stochastic processes
• parameter inference