A maximum entropy thermodynamics of small systems

TL;DR

This paper introduces a maximum entropy and superstatistical framework to analyze the internal dynamics of small systems in contact with large baths, accounting for fluctuations and finite-size effects.

Contribution

It develops a novel superstatistical maximum entropy approach to model small system dynamics and calculates first-order size corrections to canonical ensemble descriptions.

Findings

Method accurately captures the state space of a harmonic oscillator with different baths.

The approach accounts for fluctuations in inverse temperature and finite-size effects.

Results demonstrate improved modeling of small systems beyond traditional ensembles.

Abstract

We present a maximum entropy approach to analyze the internal dynamics of a small system in contact with a large bath e.g. a solute-solvent system. For the small solute, the fluctuations around the mean values of observables are not negligible and the probability distribution P(r) of the state space depends on the intricate details of the interaction of the solute with the solvent. Here, we employ a superstatistical approach: P(r) is expressed as a marginal distribution summed over the variation in {\beta}, the inverse temperature of the solute. The joint distribution P({\beta},r) is estimated by maximizing its entropy. We also calculate the first order system-size corrections to the canonical ensemble description of the state space. We test the development on a simple harmonic oscillator interacting with two baths with very different chemical identities viz. a) Lennard-Jones particles and b) water molecules. In both cases, our method captures the state space of the oscillator sufficiently well. Future directions and connections with traditional statistical mechanics are discussed.