Non-Linear Generalization of the DLR Equations: $q$-Specifications and $q$-Equilibrium Measures

TL;DR

This paper extends the classical DLR framework to a non-linear setting by introducing $q$-specifications and $q$-equilibrium measures, providing new tools to analyze complex physical systems and their equilibrium states.

Contribution

It develops the concept of $q$-specifications and $q$-equilibrium measures, establishing existence, uniqueness, and examples within a non-linear generalization of DLR theory.

Findings

Existence and uniqueness conditions for $q$-equilibrium measures

Examples of $q$-specifications with no $q$-equilibrium measures

Multiple $q$-equilibrium measures in low-temperature Ising models

Abstract

We introduce a {\it non-linear} generalization of the classical Dobrushin-Lanford-Ruelle (DLR) framework by developing the concept of a $q$-specification and the associated $q$-equilibrium measures. These objects arise naturally from a family of non-linear $q$-stochastic operators acting on the space of probability measures. A $q$-equilibrium measure is characterized as a fixed point of such operators, providing a non-linear analogue of the Gibbs equilibrium in the sense of DLR. We establish general conditions ensuring the existence and uniqueness of $q$-equilibrium measures and demonstrate how quasilocality plays a decisive role in their construction. Moreover, we exhibit examples of $q$-specifications with an empty set of $q$-equilibrium measures. We characterize the set of $q$-equilibrium measures by studying the dynamical systems generated by a class of $q$-stochastic operators. As a concrete application, we show that for the one-dimensional Ising model at sufficiently low temperatures, multiple $q$-equilibrium measures may exist, even though the classical Gibbs measure remains unique. Our results reveal that the $q$-specification formalism extends the DLR theory from linear to non-linear settings and opens a new direction in the study of Gibbs measures and equilibrium states of physical systems.