Nonextensive statistical mechanics: A brief introduction

TL;DR

This paper introduces nonextensive statistical mechanics, a generalization of Boltzmann-Gibbs theory, suitable for complex systems with non-ergodic or fractal phase space structures, and discusses its foundations and applications.

Contribution

It provides a concise overview of the formalism, dynamical basis, and applications of nonextensive statistical mechanics, highlighting its stability and robustness.

Findings

Generalized entropy $S_q$ extends traditional thermodynamics.

Applicable to systems with fractal or hierarchical phase space.

Demonstrates stability of the nonextensive entropy concept.

Abstract

Boltzmann-Gibbs statistical mechanics is based on the entropy $S_{BG}=-k \sum_{i=1}^W p_i \ln p_i$. It enables a successful thermal approach of ubiquitous systems, such as those involving short-range interactions, markovian processes, and, generally speaking, those systems whose dynamical occupancy of phase space tends to be ergodic. For systems whose microscopic dynamics is more complex, it is natural to expect that the dynamical occupancy of phase space will have a less trivial structure, for example a (multi)fractal or hierarchical geometry. The question naturally arises whether it is possible to study such systems with concepts and methods similar to those of standard statistical mechanics. The answer appears to be {\it yes} for ubiquitous systems, but the concept of entropy needs to be adequately generalized. Some classes of such systems can be satisfactorily approached with the entropy $S_q=k\frac{1-\sum_{i=1}^W p_i^q}{q-1}$ (with $q \in \cal R$, and $S_1 =S_{BG}$). This theory is sometimes referred in the literature as {\it nonextensive statistical mechanics}. We provide here a brief introduction to the formalism, its dynamical foundations, and some illustrative applications. In addition to these, we illustrate with a few examples the concept of {\it stability} (or {\it experimental robustness}) introduced by B. Lesche in 1982 and recently revisited by S. Abe.