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We describe collective-move Monte Carlo algorithms designed to approximate the overdamped dynamics of self-assembling nanoscale components equipped with strong, short-ranged and anisotropic interactions. Conventional Monte Carlo simulations…

Statistical Mechanics · Physics 2012-04-16 Stephen Whitelam

We investigate the liquid-glass phase transition in a system of point-like particles interacting via a finite-range attractive potential in D-dimensional space. The phase transition is driven by an `entropy crisis' where the available phase…

Disordered Systems and Neural Networks · Physics 2009-11-11 Vik. S. Dotsenko , G. Blatter

We perform stringent tests of thermodynamic theories of the glass transition over the experimentally relevant temperature regime for several simulated glass-formers. The swap Monte Carlo algorithm is used to estimate the configurational…

Statistical Mechanics · Physics 2019-10-03 Misaki Ozawa , Camille Scalliet , Andrea Ninarello , Ludovic Berthier

The rise of artificial intelligence (AI) hinges on the efficient training of modern deep neural networks (DNNs) for non-convex optimization and uncertainty quantification, which boils down to a non-convex Bayesian learning problem. A…

Computation · Statistics 2023-06-01 Wei Deng

We investigate the replica theory of the liquid-glass transition for a binary mixture of large and small additive hard spheres. We consider two different ans\"atze for this problem: the frozen glass ansatz (FGA) in whichs the exchange of…

Soft Condensed Matter · Physics 2019-05-10 Harukuni Ikeda , Francesco Zamponi

Many physical systems can be described in terms of matrix models that we often cannot solve analytically. Fortunately, they can be studied numerically in a straightforward way. Many commonly used algorithms follow the Monte Carlo method,…

High Energy Physics - Lattice · Physics 2022-05-11 Samuel Kováčik , Juraj Tekel

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

We introduce a new Monte Carlo method by incorporating a guided distribution function to the conventional Monte Carlo method. In this way, the efficiency of Monte Carlo methods is drastically improved. To further speed up the algorithm, we…

Computational Physics · Physics 2009-11-07 S. P. Li

A new algorithm for Monte Carlo calculation of the double exchange model is studied. The algorithm is commonly applicable to wide classes of strongly correlated electron systems which involve itinerant electrons coupled with…

Strongly Correlated Electrons · Physics 2009-11-07 Nobuo Furukawa , Yukitoshi Motome , Hisaho Nakata

Kinetic facilitated models and the Mode Coupling Theory (MCT) model B are within those systems known to exhibit a discontinuous dynamical transition with a two step relaxation. We consider a general scaling approach, within mean field…

Statistical Mechanics · Physics 2016-05-26 Antonio de Candia , Annalisa Fierro , Antonio Coniglio

Switching dynamical systems are an expressive model class for the analysis of time-series data. As in many fields within the natural and engineering sciences, the systems under study typically evolve continuously in time, it is natural to…

Machine Learning · Computer Science 2022-05-19 Lukas Köhs , Bastian Alt , Heinz Koeppl

In most sampling algorithms, including Hamiltonian Monte Carlo, transition rates between states correspond to the probability of making a transition in a single time step, and are constrained to be less than or equal to 1. We derive a…

Machine Learning · Statistics 2015-10-13 Andrew B. Berger , Mayur Mudigonda , Michael R. DeWeese , Jascha Sohl-Dickstein

The extreme slowing down associated with glass formation in experiments and in simulations results in serious difficulties to prepare deeply quenched, well annealed, glassy material. Recently, methods to achieve such deep quenching were…

Soft Condensed Matter · Physics 2020-07-08 Bhanu Prasad Bhowmik , Valery Iylin , Itamar Procaccia

Mean-field approximation is often used to explore the qualitative behaviour of phase transitions in classical spin models before employing computationally costly methods such as the Monte-Carlo techniques. We implement a 'lattice…

Mesoscale and Nanoscale Physics · Physics 2020-07-28 Ondrej Hovorka , Timothy J. Sluckin

Mainstream flow matching methods typically focus on learning the local velocity field, which inherently requires multiple integration steps during generation. In contrast, Mean Velocity Flow models establish a relationship between the local…

Machine Learning · Computer Science 2026-03-18 Chenrui Ma

Normalizing flows can transform a simple prior probability distribution into a more complex target distribution. Here, we evaluate the ability and efficiency of generative machine learning methods to sample the Boltzmann distribution of an…

Soft Condensed Matter · Physics 2024-09-16 Gerhard Jung , Giulio Biroli , Ludovic Berthier

We combine the swap Monte Carlo algorithm to long multi-CPU molecular dynamics simulations to analyse the equilibrium relaxation dynamics of model supercooled liquids over a time window covering ten orders of magnitude for temperatures down…

Soft Condensed Matter · Physics 2022-12-16 Camille Scalliet , Benjamin Guiselin , Ludovic Berthier

In this work a replica exchange Monte Carlo scheme which considers an extended isobaric-isothermal ensemble with respect to pressure is applied to study hard spheres (HS). The idea behind the proposal is expanding volume instead of…

Statistical Mechanics · Physics 2015-05-20 Gerardo Odriozola

In this paper and in the companion one we address the problem of identifying the effective theory that describes the statistics of the fluctuations of what is thought to be the relevant order parameter for glassy systems---the overlap field…

Statistical Mechanics · Physics 2018-11-21 G. Biroli , C. Cammarota , G. Tarjus , M. Tarzia

The glass problem is notoriously hard and controversial. Even at the mean-field level, little is agreed about how a fluid turns sluggish while exhibiting but unremarkable structural changes. It is clear, however, that the process involves…

Statistical Mechanics · Physics 2012-08-31 Patrick Charbonneau , Atsushi Ikeda , Giorgio Parisi , Francesco Zamponi