Quantum Macrostatistical Theory of Nonequilibrium Steady States

TL;DR

This paper develops a macrostatistical framework for quantum systems in nonequilibrium steady states, revealing long-range correlations and generalized Onsager relations through a Gaussian Markov process model.

Contribution

It introduces a novel quantum macrostatistical approach based on hydrodynamical observables, extending classical concepts to nonequilibrium quantum steady states.

Findings

Hydrodynamical fluctuations follow a Gaussian Markov process.

Transport coefficients satisfy generalized Onsager reciprocity.

Long-range spatial correlations are a generic feature of nonequilibrium states.

Abstract

We provide a general macrostatistical formulation of nonequilibrium steady states of reservoir driven quantum systems. This formulation is centred on the large scale properties of the locally conserved hydrodynamical observables, and our basic assumptions comprise (a) a chaoticity hypothesis for the nonconserved currents carried by these observables, (b) an extension of Onsager's regression hypothesis to the fluctuations about nonequilibrium states, and (c) a certain mesoscopic local equilibrium hypothesis. On this basis we obtain a picture wherein the fluctuations of the hydrodynamical observables about a nonequilibrium steady state execute a Gaussian Markov process of a generalized Onsager-Machlup type, which is completely determined by the position dependent transport coefficients and the equilibrium entropy function of the system. This picture reveals that the transport coefficients satisfy a generalized form of the Onsager reciprocity relations in the nonequilibrium situation and that the spatial correlations of the hydrodynamical observables are generically of long range. This last result constitutes a model-independent generalization of that obtained for special classical stochastic systems and marks a striking difference between the steady nonequilibrium and equilibrium states, since it is only at critical points that the latter carry long range correlations.