Stochastic line integrals and stream functions as metrics of irreversibility and heat transfer

TL;DR

This paper develops a general framework for stochastic line integrals, especially the stochastic area, to quantify irreversibility and heat transfer in noise-driven dynamical systems, supported by theoretical and numerical analysis.

Contribution

It introduces a comprehensive approach to understanding stochastic line integrals and stream functions, clarifying their experimental and simulation implementation for two-dimensional systems.

Findings

Stream function determines steady-state current orientation.

Stochastic area scales with noise strength in nonlinear and linear springs.

Numerical validation with a driven overdamped mass-spring system.

Abstract

Stochastic line integrals provide a useful tool for quantitatively characterizing irreversibility and detailed balance violation in noise-driven dynamical systems. A particular realization is the stochastic area, recently studied in coupled electrical circuits. Here, we provide a general framework for understanding properties of stochastic line integrals and clarify their implementation for experiments and simulations. For two-dimensional systems, stochastic line integrals can be expressed in terms of a stream function, the sign of which determines the orientation of steady-state probability currents. Additionally, the stream function permits analytical understanding of the scaling dependence of stochastic area on key parameters such as the noise strength for both nonlinear and linear springs. Theoretical results are supported by numerical studies of an overdamped, two-dimensional mass-spring system driven out of equilibrium.