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We propose a new class of phenomenological models for dynamic glass transitions. The system consists of an ensemble of mesoscopic regions to which local energies are allocated. At each time step, a region is randomly chosen and a new local…

Disordered Systems and Neural Networks · Physics 2009-11-11 Ivan Junier

In this paper, we study the mechanics of statistically non-uniform two-phase elastic discrete structures. In particular, following the methodology proposed in (Luciano and Willis, Journal of the Mechanics and Physics of Solids 53,…

Materials Science · Physics 2011-05-03 Jan Zeman , Ron H. J. Peerlings , Marc G. D. Geers

We discuss a spin glass reminiscent of the Random Energy Model, which allows in particular to recast the Parisi minimization into a more classical Gibbs variational principle, thereby shedding some light on the physical meaning of the order…

Probability · Mathematics 2009-11-13 Erwin Bolthausen , Nicola Kistler

A new phenomenological dark energy model, originally associated to the large-scale structure formation and considered as a solution to the fine-tuning and coincidence problems related to the cosmological constant, was analyzed within the…

General Relativity and Quantum Cosmology · Physics 2026-03-05 A. Kazım Çamlıbel

The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. We show for the first time…

Statistical Mechanics · Physics 2011-10-11 Valerio Lucarini , Stefania Sarno

In the context of models where the dark energy density $\rD$ is a random variable, anthropic selection effects may explain both the "old" cosmological constant problem and the "time coincidence". We argue that this type of solution to both…

Astrophysics · Physics 2009-11-07 J. Garriga , A. Vilenkin

Energy-based models (EBMs) are powerful probabilistic models, but suffer from intractable sampling and density evaluation due to the partition function. As a result, inference in EBMs relies on approximate sampling algorithms, leading to a…

Machine Learning · Computer Science 2020-01-10 Dieterich Lawson , George Tucker , Bo Dai , Rajesh Ranganath

We introduce a stability criterion for quantum statistical ensembles describing macroscopic systems. An ensemble is called "stable" when a small number of local measurements cannot significantly modify the probability distribution of the…

Quantum Physics · Physics 2016-12-20 Walter Hahn , Boris V. Fine

We discuss the metastate, a probability measure on thermodynamic states, and its usefulness in addressing difficult questions pertaining to the statistical mechanics of systems with quenched disorder, in particular short-range spin glasses.…

Disordered Systems and Neural Networks · Physics 2007-05-23 C. M. Newman , D. L. Stein

In this paper the Random Energy Model(REM) under exponential type environment is considered which includes double exponential and Gaussian cases. Limiting Free Energy is evaluated in these models. Limiting Gibbs' distribution is evaluated…

Probability · Mathematics 2007-05-23 Nabin Kumar Jana

We examined energy spectrums of some particular systems of binary spins. It is shown that the configuration space can be divided into classes, and in the limit the energy distributions in these classes can be approximated by the normal…

Disordered Systems and Neural Networks · Physics 2015-05-14 Boris Kryzhanovsky , Leonid Litinskii

The limit of small entropy production is reached in relaxing systems long after preparation, and in stationary driven systems in the limit of small driving power. Surprisingly, for extended systems this limit is not in general the…

Condensed Matter · Physics 2009-10-31 Leticia F. Cugliandolo , Jorge Kurchan

This thesis presents original results in two domains of disordered statistical physics: logarithmic correlated Random Energy Models (logREMs), and localization transitions in long-range random matrices. In the first part devoted to logREMs,…

Disordered Systems and Neural Networks · Physics 2017-05-22 Xiangyu Cao

Marginal stability is the notion that stability is achieved, but only barely so. This property constrains the ensemble of configurations explored at low temperature in a variety of systems, including spin, electron and structural glasses. A…

Statistical Mechanics · Physics 2016-04-12 Le Yan , Marco Baity-Jesi , M. Mueller , Matthieu Wyart

When describing the effective dynamics of an observable in a many-body system, the repeated randomness assumption, which states that the system returns in a short time to a maximum entropy state, is a crucial hypothesis to guarantee that…

Quantum Physics · Physics 2024-09-25 Philipp Strasberg , Andreas Winter , Jochen Gemmer , Jiaozi Wang

We derive a rigorous lower bound on the average local energy for the Ising model with quenched randomness. The result is that the lower bound is given by the average local energy calculated in the absence of all interactions other than the…

Disordered Systems and Neural Networks · Physics 2009-11-13 Hidetsugu Kitatani , Hidetoshi Nishimori , Akira Aoki

We investigate the spectral properties of all-to-all interacting spin Hamiltonians acting on exactly $k$ spins, whose coupling coefficients are drawn from a normal distribution with mean $\mu$ and variance $\sigma^2$. For $\mu = 0$, we…

Quantum Physics · Physics 2026-01-09 Sasanka Dowarah

Stability against perturbation is a highly nontrivial property of quantum systems and is often a requirement to define new phases. In most systems where stability can be rigorously established, only static perturbations are considered;…

Quantum Physics · Physics 2025-10-17 Hongye Yu , Tzu-Chieh Wei

We analyze the properties of a Lennard-Jones system at the level of the potential energy landscape. After an exhaustive investigation of the topological features of the landscape of the systems, obtained studying small size sample, we…

Disordered Systems and Neural Networks · Physics 2016-08-31 L. Angelani , G. Parisi , G. Ruocco , G. Viliani

The article reviews recent developments in the theory of fluctuations and correlations of energy levels and eigenfunction amplitudes in diffusive mesoscopic samples. Various spatial geometries are considered, with emphasis on…

Disordered Systems and Neural Networks · Physics 2009-10-31 Alexander D. Mirlin