What should a statistical mechanics satisfy to reflect nature?

TL;DR

This paper explores the criteria that statistical mechanics should meet to accurately describe complex, non-ergodic systems, proposing extensions beyond traditional Boltzmann-Gibbs frameworks through nonextensive approaches.

Contribution

It reviews nonextensive statistical mechanics and its recent developments, suggesting broader conditions under which statistical methods can effectively model complex systems.

Findings

Non-ergodic systems can be modeled using generalized thermostatistics.

Traditional Boltzmann-Gibbs methods are not universally applicable.

Nonextensive frameworks provide a promising approach for complex systems.

Abstract

There is no compelling reason imposing that the methods of statistical mechanics should be restricted to the dynamical systems which follow the usual Boltzmann-Gibbs prescriptions. More specifically, ubiquitous natural and artificial systems exhibit complex dynamics, for instance, generic stationary states which are {\it not} ergodic nor close to it, in any geometrically simple subset of the {\it a priori} allowed phase space, in any (even extended) trivial sense. A vast class of such systems appears, nevertheless, to be tractable within thermostatistical methods completely analogous to the usual ones. The question posed in the title arises then naturally. Some answer to this complex question is advanced in the present review of nonextensive statistical mechanics and its recent connections.