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In this paper, we extend the concept of generalized entropy to uniform spaces, allowing computations beyond metrizable settings. We apply this to parabolic dynamics - systems with a unique fixed point uniformly attracting all compact…

Dynamical Systems · Mathematics 2025-07-02 Frederico A. C. L. Marinho , Hellen de Paula , Lucas H. R. de Souza

Configurational entropy has been revealed as a reliable method for constraining some parameters of a given model [Phys. Rev. D \textbf{92} (2015) 126005, Eur. Phys. J. C \textbf{76} (2016) 100]. In this letter we calculate the…

High Energy Physics - Theory · Physics 2016-10-12 R. A. C. Correa , P. H. R. S. Moraes , A. de Souza Dutra , W. de Paula , T. Frederico

The ability to continuously learn remains elusive for deep learning models. Unlike humans, models cannot accumulate knowledge in their weights when learning new tasks, mainly due to an excess of plasticity and the low incentive to reuse…

Machine Learning · Computer Science 2022-04-21 Vladimir Araujo , Julio Hurtado , Alvaro Soto , Marie-Francine Moens

We give a notion of entropy for general gemetric structures, which generalizes well-known notions of topological entropy of vector fields and geometric entropy of foliations, and which can also be applied to singular objects, e.g. singular…

Differential Geometry · Mathematics 2011-09-27 Nguyen Tien Zung

Topological constraint theory has become an increasingly popular tool to predict the compositional dependence of glass properties or pinpoint promising compositions with tailored functionalities. This approach reduces complex disordered…

Disordered Systems and Neural Networks · Physics 2020-06-16 Mathieu Bauchy

This paper is concerned with reconstruction issue of inverse obstacle problems governed by partial differential equations and consists of two parts. (i) The first part considers the foundation of the probe and enclosure methods for an…

Analysis of PDEs · Mathematics 2022-07-11 Masaru Ikehata

We present new results reflecting the analogies between the Kob-Andersen model and other glassy systems. Studying the stability of the blocked configurations above and below the transition we also give arguments that supports their…

Statistical Mechanics · Physics 2016-08-31 S. Franz , R. Mulet , G. Parisi

We introduce a class of dissipative quantum spin models with local interactions and without quenched disorder that show glassy behaviour. These models are the quantum analogs of the classical facilitated spin models. Just like their…

Statistical Mechanics · Physics 2012-07-31 Beatriz Olmos , Igor Lesanovsky , Juan P. Garrahan

We review the main methods used to study spin glasses. In the first part, we focus on methods for fully connected models and systems defined on a tree, such as the replica method, the Thouless-Anderson-Palmer formalism, the cavity method,…

Disordered Systems and Neural Networks · Physics 2023-12-01 Ada Altieri , Marco Baity-Jesi

The short- and long-time dynamics of model systems undergoing a glass transition with apparent inversion of Kauzmann and dynamical arrest glass transition lines is investigated. These models belong to the class of the spherical mean-field…

Disordered Systems and Neural Networks · Physics 2016-01-06 Corrado Rainone , Ulisse Ferrari , Matteo Paoluzzi , Luca Leuzzi

We explore several potential issues that have been raised over the years regarding the "entropic droplet" scenario of activated transport in liquids, due to Wolynes and coworkers, with the aim of clarifying the status of various…

Disordered Systems and Neural Networks · Physics 2014-12-05 Vassiliy Lubchenko , Pyotr Rabochiy

We derive a mode-coupling theory for the slow dynamics of fluids confined in disordered porous media represented by spherical particles randomly placed in space. Its equations display the usual nonlinear structure met in this theoretical…

Soft Condensed Matter · Physics 2007-05-23 V. Krakoviack

The random first order transition theory of the dynamics of supercooled liquids is extended to treat aging phenomena in nonequilibrium structural glasses. A reformulation of the idea of ``entropic droplets'' in terms of libraries of local…

Soft Condensed Matter · Physics 2009-11-10 Vassiliy Lubchenko , Peter G. Wolynes

We establish the global existence of weak entropy solutions for 1D isentropic gas dynamics with general pressure laws ($\gamma > 1$). To address vacuum degeneracy, we introduce a novel structural regularization via a "Synchronized Dual…

Analysis of PDEs · Mathematics 2026-01-22 Kewang Chen

We develop a method of obtaining a hierarchy of new higher-order entropies in the context of compressible models with local and non-local diffusion and isentropic pressure. The local viscosity is allowed to degenerate as the density…

Analysis of PDEs · Mathematics 2019-08-07 Peter Constantin , Theodore D. Drivas , Roman Shvydkoy

This key-issues review is a plea for a new focus on simpler and more realistic models of glass-forming fluids. It seems to me that we have too often been led astray by sophisticated mathematical models that beautifully capture some of the…

Statistical Mechanics · Physics 2015-06-17 J. S. Langer

Identifying the conditions under which glass formation occurs is crucial for a fundamental understanding of the glass transition mechanism. Pure liquids devoid of any frustration avoid glass transition and undergo crystallization. In this…

Soft Condensed Matter · Physics 2026-03-04 Saumya Suvarna , Prabhat K. Jaiswal , Madhu Priya

The complex dynamics of an increasing number of systems is attributed to the emergence of a rugged energy landscape with an exponential number of metastable states. To develop this picture into a predictive dynamical theory I discuss how to…

Disordered Systems and Neural Networks · Physics 2021-09-15 Tommaso Rizzo

By defining a spatially varying replica overlap parameter for a supercooled liquid referenced to an ensemble of fiducial liquid state configurations we explicitly construct a constrained replica free energy functional that maps directly…

Soft Condensed Matter · Physics 2009-11-13 Jacob D. Stevenson , Aleksandra M. Walczak , Randall W. Hall , Peter G. Wolynes

This work primarily focuses on an operator inference methodology aimed at constructing low-dimensional dynamical models based on a priori hypotheses about their structure, often informed by established physics or expert insights. Stability…

Machine Learning · Computer Science 2024-03-04 Igor Pontes Duff , Pawan Goyal , Peter Benner