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Glassy soft matter is often continuously polydisperse, in which the sizes or various properties of the constituent particles are distributed continuously. However, most of the microscopic theories of the glass transition focus on the…

Soft Condensed Matter · Physics 2024-05-14 Hyonggi Kim , Atsushi Ikeda

We study the Blume-Emery-Griffiths spin glass model in presence of an attractive coupling between real replicas, and evaluate the effective potential as a function of the density overlap. We find that there is a region, above the first…

Statistical Mechanics · Physics 2009-11-07 A. de Candia

The spherical mean field approximation of a spin-1 model with p-body quenched disordered interaction is investigated. Depending on temperature and chemical potential the system is found in a paramagnetic or in a glassy phase and the…

Disordered Systems and Neural Networks · Physics 2012-03-06 Ulisse Ferrari , Luca Leuzzi

We use a structure analysis technique that quantifies cluster geometries using machine learning to identify a bicapped square antiprism (BSAP) as the nearest-neighbor cluster involved in the glass transition in Pd82Si18, a prototype…

Materials Science · Physics 2019-01-23 Jason J. Maldonis , Paul M. Voyles

The understanding of glassy dynamics above the devitrification temperature of a glass remains poorly understood. Here, we use real-time AFM imaging to build a spatio-temporal map of the relaxation dynamics of a highly stable glass into its…

We show that a glass transition, signaled by a peak in the specific heat vs. temperature, can occur because a glassy system that shows no signs of aging progresses so slowly through the energy landscape that the time needed to obtain an…

Disordered Systems and Neural Networks · Physics 2007-05-23 Clare C. Yu , Herve M. Carruzzo

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

We use event driven simulations to analyze glassy dynamics as a function of density and energy dissipation in a two-dimensional bidisperse granular fluid under stationary conditions. Clear signatures of a glass transition are identified,…

Statistical Mechanics · Physics 2011-10-05 Iraj Gholami , Andrea Fiege , Annette Zippelius

The mode-coupling theory (MCT) of the glass transition ranks among the most successful first-principles kinetic theories to describe glassy dynamics. However, MCT does not fully account for crucial aspects of the dynamics near the glass…

Soft Condensed Matter · Physics 2024-08-22 Ilian Pihlajamaa , Liesbeth M. C. Janssen

Two coarse-grained models for polymer chains in dense glass-forming polymer melts are studied by computer simulation: the bond-fluctuation model on a simple cubic lattice, where a bond-length potential favors long bonds, is treated by…

Soft Condensed Matter · Physics 2007-05-23 K. Binder , J. Baschnagel , C. Bennemann , W. Paul

Monte Carlo simulations are widely employed to measure the physical properties of glass-forming liquids in thermal equilibrium. Combined with local Monte Carlo moves, the Metropolis algorithm can also be used to simulate the relaxation…

Statistical Mechanics · Physics 2024-09-23 Ludovic Berthier , Federico Ghimenti Frédéric van Wijland

We consider the theory of the glass phase and jamming of hard spheres in the large space dimension limit. Building upon the exact expression for the free-energy functional obtained previously, we find that the Random First Order Transition…

Statistical Mechanics · Physics 2013-12-02 Jorge Kurchan , Giorgio Parisi , Pierfrancesco Urbani , Francesco Zamponi

The performance of flow matching and diffusion models can be greatly improved at inference time using reward alignment algorithms, yet efficiency remains a major limitation. While several algorithms were proposed, we demonstrate that a…

Machine Learning · Computer Science 2026-02-12 Peter Holderrieth , Uriel Singer , Tommi Jaakkola , Ricky T. Q. Chen , Yaron Lipman , Brian Karrer

We develop a model free energy from an expansion that basically includes graphs without loops. From this calculation, we derive the temperature dependence of the density (or specific volume), the typical time scale of the…

Disordered Systems and Neural Networks · Physics 2016-10-28 Henrich Frielinghaus

The interrelation of dynamic processes active on separated time-scales in glasses and viscous liquids is investigated using a model displaying two time-scale bifurcations both between fast and secondary relaxation and between secondary and…

Disordered Systems and Neural Networks · Physics 2015-03-19 Andrea Crisanti , Luca Leuzzi , Matteo Paoluzzi

Strong changes in bulk properties, such as modulus and viscosity, are observed near the glass transition temperature, T_{g}, of amorphous materials. For more than a century, intense efforts have been made to define a microscopic origin for…

Disordered Systems and Neural Networks · Physics 2024-04-24 Joseph B. Schlenoff , Khalil Akkaoui

We present a model and protocol that enable the generation of extremely stable computer glasses at minimal computational cost. The protocol consists of an instantaneous quench in an augmented potential energy landscape, with particle radii…

Soft Condensed Matter · Physics 2019-01-08 Geert Kapteijns , Wencheng Ji , Carolina Brito , Matthieu Wyart , Edan Lerner

Glass-forming liquids exhibit a dramatic dynamical slowdown as the temperature is lowered. This can be attributed to relaxation proceeding via large structural rearrangements whose characteristic size increases as the system cools. These…

Statistical Mechanics · Physics 2015-03-31 Allan Adams , Tarek Anous , Jaehoon Lee , Sho Yaida

Understanding the mechanical properties of glasses remains elusive since the glass transition itself is not fully understood, even in well studied examples of glass formers in two dimensions. In this context we demonstrate here: (i) a…

We explore the relationship between a machine-learned structural quantity (softness) and excess entropy in simulations of supercooled liquids. Excess entropy is known to scale well the dynamical properties of liquids, but this…

Soft Condensed Matter · Physics 2023-06-07 Ian R. Graham , Paulo E. Arratia , Robert A. Riggleman
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