Generalized statistical mechanics for superstatistical systems

TL;DR

This paper introduces a generalized statistical mechanics framework for superstatistical systems, enabling better modeling of complex systems with fluctuating environments across various fields.

Contribution

It develops a formalism that maps superstatistical systems onto modified statistical mechanics, broadening the applicability of superstatistics.

Findings

Unified approach to superstatistics in different systems

Application to train delay, turbulence, and cancer survival data

Enhanced modeling of systems with environmental fluctuations

Abstract

Mesoscopic systems in a slowly fluctuating environment are often well described by superstatistical models. We develop a generalized statistical mechanics formalism for superstatistical systems, by mapping the superstatistical complex system onto a system of ordinary statistical mechanics with modified energy levels. We also briefly review recent examples of applications of the superstatistics concept for three very different subject areas, namely train delay statistics, turbulent tracer dynamics, and cancer survival statistics.