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Predicting the stationary behavior of observables in isolated many-body quantum systems is a central challenge in quantum statistical mechanics. While one can often use the Gibbs ensemble, which is simple to compute, there are many…

Quantum Physics · Physics 2025-07-30 Lodovico Scarpa , Abdulla Alhajri , Vlatko Vedral , Fabio Anza

The statistical mechanics of Gibbs is a juxtaposition of subjective, probabilistic ideas on the one hand and objective, mechanical ideas on the other. In this paper, we follow the path set out by Jaynes, including elements added…

Statistical Mechanics · Physics 2015-11-24 David M. Rogers , Thomas L. Beck , Susan B. Rempe

We study Gibbs partition models, also known as composition schemes. Our main results comprehensively describe their phase diagram, including a phase transition from the convergent case described in Stufler (2018, Random Structures \&…

Probability · Mathematics 2022-11-22 Benedikt Stufler

Statistical mechanics relies on the complete though probabilistic description of a system in terms of all the microscopic variables. Its object is to derive therefrom static and dynamic properties involving some reduced set of variables.…

Statistical Mechanics · Physics 2009-10-31 R. Balian

The foundations of the Boltzmann-Gibbs (BG) distributions for describing equilibrium statistical mechanics of systems are examined. Broadly, they fall into: (i) probabilistic paaroaches based on the principle of equal a priori probability…

Statistical Mechanics · Physics 2009-11-10 A. K. Rajagopal , Sumiyoshi Abe

We investigate multiscale Gibbs measures from a variational and probabilistic viewpoint, focusing on the structural asymmetry among conditional entropies that characterizes their construction. We show how this asymmetry emerges both from…

Mathematical Physics · Physics 2025-12-23 Francesco Camilli , Pierluigi Contucci , Emanuele Mingione

The fundamentals of Statistical Mechanics require a fresh definition in the context of the developments in Classical Mechanics of integrable and chaotic systems. This is done with the introduction of Micro Partitions ; a union of disjoint…

Statistical Mechanics · Physics 2007-05-23 Ajay Patwardhan

Predictive statistical mechanics is a form of inference from available data, without additional assumptions, for predicting reproducible phenomena. By applying it to systems with Hamiltonian dynamics, a problem of predicting the macroscopic…

Statistical Mechanics · Physics 2015-09-22 Domagoj Kuic

We discuss here the use of generalized forms of entropy, taken as information measures, to characterize phase transitions and critical behavior in thermodynamic systems. Our study is based on geometric considerations pertaining to the space…

Statistical Mechanics · Physics 2009-04-14 M. Portesi , F. Pennini , A. Plastino

We study the thermodynamic formalism for generalized Gibbs measures, such as renormalization group transformations of Gibbs measures or joint measures of disordered spin systems. We first show existence of the relative entropy density and…

Probability · Mathematics 2007-05-23 Christof Kuelske , Arnaud Le Ny , Frank Redig

We give an introductory account of the recently identified gauge invariance of the equilibrium statistical mechanics of classical many-body systems [J. M\"uller et al., Phys. Rev. Lett. Phys. Rev. Lett. 133, 217101 (2024)]. The gauge…

Statistical Mechanics · Physics 2025-03-26 Johanna Müller , Florian Sammüller , Matthias Schmidt

Our goal is to present the basic results on one-dimensional Gibbs and equilibrium states viewed as special invariant measures on symbolic dynamical systems, and then to describe without technicalities a sample of results they allowed to…

Dynamical Systems · Mathematics 2020-07-16 J. -R. Chazottes , G. Keller

We study a class of dynamical systems generated by random substitutions, which contains both intrinsically ergodic systems and instances with several measures of maximal entropy. In this class, we show that the measures of maximal entropy…

Dynamical Systems · Mathematics 2026-03-26 Philipp Gohlke , Andrew Mitchell

We are concerned with sets of generic points for shift-invariant measures in the countable symbolic space. We measure the sizes of the sets by the Billingsley-Hausdorff dimensions defined by Gibbs measures. It is shown that the dimension of…

Dynamical Systems · Mathematics 2016-02-01 Ai-hua Fan , Ming-tian Li , Ji-hua Ma

On the basis of a model system of pillars built of unit cubes, a two-component entropic measure for the multiscale analysis of spatio-compositional inhomogeneity is proposed. It quantifies the statistical dissimilarity per cell of the…

Statistical Mechanics · Physics 2015-05-13 Ryszard Piasecki

Entropic dynamics is a framework in which the laws of dynamics are derived as an application of entropic methods of inference. Its successes include the derivation of quantum mechanics and quantum field theory from probabilistic principles.…

Statistical Mechanics · Physics 2021-04-29 Pedro Pessoa , Felipe Xavier Costa , Ariel Caticha

We introduce a new compositional framework for generalized variational inference, clarifying the different parts of a model, how they interact, and how they compose. We explain that both exact Bayesian inference and the loss functions…

Machine Learning · Statistics 2025-03-26 Toby St Clere Smithe , Marco Perin

Statistical equilibrium configurations are important in the physics of macroscopic systems with a large number of constituent degrees of freedom. They are expected to be crucial also in discrete quantum gravity, where dynamical spacetime…

General Relativity and Quantum Cosmology · Physics 2021-09-14 Isha Kotecha

We discuss the relationship between discrete-time processes (chains) and one-dimensional Gibbs measures. We consider finite-alphabet (finite-spin) systems, possibly with a grammar (exclusion rule). We establish conditions for a stochastic…

Probability · Mathematics 2007-05-23 Roberto Fernandez , Gregory Maillard

Many problems of interest in computer science and information theory can be phrased in terms of a probability distribution over discrete variables associated to the vertices of a large (but finite) sparse graph. In recent years,…

Probability · Mathematics 2009-11-11 Amir Dembo , Andrea Montanari
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