Mutual Linearity in and out of Stationarity for Markov Jump Processes: A Trajectory-Based Approach

TL;DR

This paper introduces a trajectory-based derivation of mutual linearity in Markov jump processes, extending it to non-stationary dynamics and broader systems like diffusion and quantum processes.

Contribution

It provides a novel trajectory-level derivation of mutual linearity, generalizing it to non-stationary relaxation and broader classes of systems.

Findings

Mutual linearity holds in non-stationary relaxation dynamics.

Trajectory approach generalizes mutual linearity to diffusion and quantum systems.

The work offers fundamental insights into system responses far from equilibrium.

Abstract

Nonequilibrium response theory is a fundamental framework for understanding how physical systems respond to perturbations. Recently, a mutual linearity has been discovered for Markov jump processes using linear algebra analysis. This mutual linearity states that two observables are linearly dependent on each other in the long-time limit when the transition rate of a single edge is altered. It has also been extended to non-stationary cases for current observables. In this work, we provide a trajectory-based derivation of mutual linearity utilizing the trajectory-level linear response theory. The trajectory approach allows us to generalize the mutual linearity to non-stationary relaxation dynamics for state observables and counting observables. Our results shed light on the fundamental response properties far from equilibrium and the trajectory-level origin of mutual linearity. Our trajectory-based approach makes it possible to generalize the mutual linearity to a broader class of systems, including diffusion processes and open quantum systems.