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We implement the Wang-Landau algorithm to sample with equal probabilities the static configurations of a model granular system. The "non-interacting rigid arch model" used is based on the description of static configurations by means of…

Soft Condensed Matter · Physics 2016-08-31 D. Slobinsky , Luis A. Pugnaloni

We use a standard Monte-Carlo algorithm to study the slow dynamics of a binary Lennard-Jones glass-forming mixture at low temperature. We find that Monte-Carlo is by far the most efficient way to simulate a stochastic dynamics since…

Statistical Mechanics · Physics 2015-06-25 Ludovic Berthier , Walter Kob

As far as we know, there is no flat-histogram algorithm to sample the stationary distribution of non-equilibrium stochastic processes. The present work addresses this gap by introducing a generalization of the Wang-Landau algorithm, applied…

Statistical Mechanics · Physics 2026-02-27 L. M. C. Alencar , T. F. A. Alves , G. A. Alves , F. W. S. Lima , A. Macedo-Filho , R. S. Ferreira

In the quest to understand how structure and dynamics are connected in glasses, a number of machine learning based methods have been developed that predict dynamics in supercooled liquids. These methods include both increasingly complex…

Soft Condensed Matter · Physics 2022-06-08 Rinske M. Alkemade , Emanuele Boattini , Laura Filion , Frank Smallenburg

Boltzmann Machines (BMs) are graphical models with interconnected binary units, employed for the unsupervised modeling of data distributions. When trained on real data, BMs show the tendency to behave like critical systems, displaying a…

Disordered Systems and Neural Networks · Physics 2024-06-28 Enrico Ventura , Simona Cocco , Rémi Monasson , Francesco Zamponi

In this work, we study the nature of transitions between inherent structures of a two-dimensional model supercooled liquid. We demonstrate that these transitions occur predominately along a small number of directions on the energy…

Statistical Mechanics · Physics 2013-03-12 Glen M. Hocky , David R. Reichman

Random graphs offer a useful mathematical representation of a variety of real world complex networks. Exponential random graphs, for example, are particularly suited towards generating random graphs constrained to have specified statistical…

Statistical Mechanics · Physics 2026-02-09 Alessio Catanzaro , Diego Garlaschelli , Subodh P. Patil

In this paper we study the cooperative behavior of agents playing the Prisoner's Dilemma game in random scale-free networks. We show that the survival of cooperation is enhanced with respect to random homogeneous graphs but, on the other…

Physics and Society · Physics 2015-05-13 J. Poncela , J. Gomez-Gardenes , Y. Moreno , L. M. Floria

Recent experimental results for covalent glasses suggest the existence of an intermediate phase attributed to the self-organization of the glass network resulting from the tendency to minimize its internal stress. However, the exact nature…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. V. Chubynsky , M. -A. Briere , N. Mousseau

We introduce a parallel Wang-Landau method based on the replica-exchange framework for Monte Carlo simulations. To demonstrate its advantages and general applicability for simulations of complex systems, we apply it to different spin models…

Computational Physics · Physics 2013-05-27 Thomas Vogel , Ying Wai Li , Thomas Wüst , David P. Landau

Hierarchical dynamics in glass-forming systems span multiple timescales, from fast vibrations to slow structural rearrangements, appearing in both supercooled fluids and glassy states. Understanding how these diverse processes interact…

Soft Condensed Matter · Physics 2025-05-28 Wensi Sun , Yanshuang Chen , Wencheng Ji , Yi Zhou , Hua Tong , Ke Chen , Xiaosong Chen , Hajime Tanaka , Peng Tan

We analyze numerically the training dynamics of deep neural networks (DNN) by using methods developed in statistical physics of glassy systems. The two main issues we address are (1) the complexity of the loss landscape and of the dynamics…

Machine Learning · Statistics 2019-12-23 M. Baity-Jesi , L. Sagun , M. Geiger , S. Spigler , G. Ben Arous , C. Cammarota , Y. LeCun , M. Wyart , G. Biroli

This study examines long-term trends and shifting behavior in the collaboration network of mathematics literature, using a subset of data from Mathematical Reviews spanning 1985-2009. Rather than modeling the network cumulatively, this…

We introduce a family of local models of dynamics based on ``word problems'' from computer science and group theory, for which we can place rigorous lower bounds on relaxation timescales. These models can be regarded either as random…

Quantum Physics · Physics 2024-08-05 Shankar Balasubramanian , Sarang Gopalakrishnan , Alexey Khudorozhkov , Ethan Lake

We present a study on the performance of Wang-Landau algorithm in a lattice model of liquid crystals which is a continuous lattice spin model. We propose a novel method of the spin update scheme in a continuous lattice spin model. The…

Statistical Mechanics · Physics 2012-09-27 Suman Sinha

Hierarchical spin-glasses are Ising spin models defined by recursively coupling together two equally-sized sub-systems. In this work a new hierarchical spin system is introduced wherein the sub-systems are recursively coupled together…

Disordered Systems and Neural Networks · Physics 2023-04-05 Gavin S Hartnett

In this contribution, we investigate the fundamental mechanism of plasticity in a model two-dimensional network glass. The glass is generated by using a Monte Carlo bond-switching algorithm and subjected to athermal simple shear…

Materials Science · Physics 2020-09-30 Firaz Ebrahem , Franz Bamer , Bernd Markert

We study a microscopic mean-field model for the dynamics of the electron glass, near a local equilibrium state. Phonon-induced tunneling processes are responsible for generating transitions between localized electronic sites, which…

Disordered Systems and Neural Networks · Physics 2009-11-30 Ariel Amir , Yuval Oreg , Yoseph Imry

Diverse equilibrium systems with heterogeneous interactions lie at the edge of stability. Such marginally stable states are dynamically selected as the most abundant ones or as those with the largest basins of attraction. On the other hand,…

Disordered Systems and Neural Networks · Physics 2025-10-10 Carles Martorell , Rubén Calvo , Alessia Annibale , Miguel A. Muñoz

Glasses are traditionally characterized by their rugged landscape of disordered low-energy states and their slow relaxation towards thermodynamic equilibrium. Far from equilibrium, dynamical forms of glassy behavior with anomalous algebraic…

Disordered Systems and Neural Networks · Physics 2026-04-17 Zachary G. Nicolaou , Hangjun Cho , Yuanzhao Zhang , J. Nathan Kutz , Steven L. Brunton