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Related papers: A Kinetically Constrained Model with a Thermodynam…

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To study materials phenomena simultaneously at various length scales, descriptions in which matter can be coarse grained to arbitrary levels, are necessary. Attempts to do this in the static regime (i.e. zero temperature) have already been…

Materials Science · Physics 2009-11-07 Stefano Curtarolo , Gerbrand Ceder

Stochastic thermodynamics is formulated for variables that are odd under time reversal. The invariance under spatial rotation of the collision rates due to the isotropy of the heat bath is shown to be a crucial ingredient. An alternative…

Statistical Mechanics · Physics 2015-07-29 C. Van den Broeck , R. Toral

Two kinetic models are proposed for high-temperature rarefied (or non-equilibrium) gas flows with radiation. One of the models uses the Boltzmann collision operator to model the translational motion of gas molecules, which has the ability…

Fluid Dynamics · Physics 2023-06-28 Qi Li , Jianan Zeng , Lei Wu

Theoretical work has shed light on the phase behavior of idealized mixtures of many components with random interactions. But typical mixtures interact through particular physical features, leading to a structured, non-random interaction…

Statistical Mechanics · Physics 2022-09-05 Isabella R. Graf , Benjamin B. Machta

Kinetic lattice-gas models display fragile glass behavior, in spite of their trivial Gibbs-Boltzmann measure. This suggests that the nature of glass transition might be, at least in some cases, understood in purely kinetic or dynamical…

Statistical Mechanics · Physics 2009-10-31 Mauro Sellitto

In this work, we present a new model for the interpretation of the local dynamic behavior and the mechanical reinforcement mechanism in polymer nanocomposites. The temperature dependence of the dynamics in the glassy region is described by…

Soft Condensed Matter · Physics 2019-05-16 Georgios Kritikos , Kostas Karatasos

We numerically elucidate the microscopic mechanisms controlling the relaxation dynamics of a three-dimensional lattice glass model that has static properties compatible with the approach to a random first-order transition. At low…

Disordered Systems and Neural Networks · Physics 2024-02-09 Yoshihiko Nishikawa , Ludovic Berthier

Systems with a complex dynamics like glasses or models of biological evolution are often pictured in terms of complex landscapes, with a large number of possible collective states. We show on the example of a stochastic spin model with…

Disordered Systems and Neural Networks · Physics 2026-02-03 Laura Guislain , Eric Bertin

Motivated by dynamical experiments on cold atomic gases, we develop a quantum kinetic approach to weakly perturbed integrable models out of equilibrium. Using the exact matrix elements of the underlying integrable model we establish an…

Statistical Mechanics · Physics 2021-09-29 Joseph Durnin , M. J. Bhaseen , Benjamin Doyon

The low-temperature driven or thermally activated motion of several condensed matter systems is often modeled by the dynamics of interfaces (co-dimension-1 elastic manifolds) subject to a random potential. Two characteristic quantitative…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. Alan Middleton

We endow a system of interacting particles with two distinct, local, Markovian and reversible microscopic dynamics. Using common field-theoretic techniques used to investigate the presence of a glass transition, we find that while the…

Statistical Mechanics · Physics 2015-03-05 Hugo Jacquin , Bongsoo Kim , Kyozi Kawasaki , Frédéric Van Wijland

The minimal set of thermodynamic control parameters consists of a statistical (thermal) and a mechanical one. These suffice to introduce all the pertinent thermodynamic variables; thermodynamic processes can then be defined as paths on this…

Statistical Mechanics · Physics 2009-11-13 Jan Birjukov , Thomas Jahnke , Günter Mahler

Kinetically constrained models (KCM) are reversible interacting particle systems on $\mathbb Z^d$ with continuous time Markov dynamics of Glauber type, which represent a natural stochastic (and non-monotone) counterpart of the family of…

Probability · Mathematics 2018-07-20 Laure Marêché , Fabio Martinelli , Cristina Toninelli

We investigate the aging behavior of lattice-gas models with constrained dynamics in which particle exchange with a reservoir is allowed. Such models provide a particularly simple interpretation of aging phenomena as a slow approach to…

Statistical Mechanics · Physics 2009-10-30 Jorge Kurchan , Luca Peliti , Mauro Sellitto

The richness of the mean-field solution of simple glasses leaves many of its features challenging to interpret. A minimal model that illuminates glass physics the same way the random energy model clarifies spin glass behavior would…

Disordered Systems and Neural Networks · Physics 2025-03-14 Gilles Bonnet , Patrick Charbonneau , Giampaolo Folena

The microscopic understanding of the dramatic increase in viscosity of liquids when cooled towards the glass transition is a major unresolved issue in condensed matter physics. Here, we use machine learning methods to accelerate molecular…

Disordered Systems and Neural Networks · Physics 2025-03-06 Florian Pabst , Stefano Baroni

We review recent developments in structural-dynamical phase transitions in trajectory space. An open question is how the dynamic facilitation theory of the glass transition may be reconciled with thermodynamic theories that posit a…

Statistical Mechanics · Physics 2020-08-04 C. Patrick Royall , Francesco Turci , Thomas Speck

Computing reactive trajectories and free energy (FE) landscapes associated to rare event kinetics is key to understanding the dynamics of complex systems. The analysis of the FE surface on which the underlying dynamics takes place has…

Statistical Mechanics · Physics 2018-12-05 François Sicard

We present a unified framework for folding kinetics of proteins and RNA. The basis for this framework relies on the notion of topological frustration, which gives rise to several competing basins of attraction (CBA) in addition to the…

Soft Condensed Matter · Physics 2009-09-25 D. Thirumalai , D. K. Klimov , S. A. Woodson

The spherical p-spin model is not only a fundamental model in statistical mechanics of disordered system, but has recently gained popularity since many hard problems in machine learning can be mapped on it. Thus the study of the out of…

Disordered Systems and Neural Networks · Physics 2020-09-02 Giampaolo Folena , Silvio Franz , Federico Ricci-Tersenghi
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