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The utility of a cooperative length scale for describing the dynamics of small molecule glass-formers is shown. Molecular Dynamics and Monte Carlo simulations reveal a distribution of cooperatively moving fractal events below the…

Other Condensed Matter · Physics 2007-05-23 B. M. Erwin , R. H. Colby , S. Y. Kamath , S. K. Kumar

The finite-size scaling method in the equilibrium Monte Carlo(MC) simulations and the finite-time scaling method in the nonequilibrium-relaxation simulations are compromised. MC time data of various physical quantities are scaled by the MC…

Statistical Mechanics · Physics 2010-08-02 Tota Nakamura

This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the…

Computation · Statistics 2016-03-04 Pierre Del Moral , Ajay Jasra , Kody Law , Yan Zhou

Facilitated spin models were introduced some decades ago to mimic systems characterized by a glass transition. Recent developments have shown that a class of facilitated spin models is also able to reproduce characteristic signatures of the…

Disordered Systems and Neural Networks · Physics 2014-11-07 Peter G. Fennell , James P. Gleeson , Davide Cellai

Dissipative particle dynamics (DPD) and multi-particle collision (MPC) dynamics are powerful tools to study mesoscale hydrodynamic phenomena accompanied by thermal fluctuations. To understand the advantages of these types of mesoscale…

Soft Condensed Matter · Physics 2009-11-11 Hiroshi Noguchi , Norio Kikuchi , Gerhard Gompper

We propose a new Monte Carlo method for sampling from multimodal distributions. The idea of this technique is based on splitting the task into two: finding the modes of a target distribution $\pi$ and sampling, given the knowledge of the…

Computation · Statistics 2019-01-14 Emilia Pompe , Chris Holmes , Krzysztof Łatuszyński

We simulate the compression of a two-component Lennard-Jones liquid at a variety of constant temperatures using a molecular dynamics algorithm in an isobaric-isothermal ensemble. The viscosity of the liquid increases with pressure,…

chem-ph · Physics 2009-10-22 Shelly L. Shumway , Andrew S. Clarke , Hannes Jónsson

Upon heating, ultrastable glassy films transform into liquids via a propagating equilibration front, resembling the heterogeneous melting of crystals. A microscopic understanding of this robust phenomenology is however lacking because…

Statistical Mechanics · Physics 2023-09-20 Cecilia Herrero , Mark D. Ediger , Ludovic Berthier

We introduce a powerful Monte Carlo (MC) algorithm for the atomistic simulation of bulk models of oligo- and poly-thiophenes by redesigning MC moves originally developed for considerably simpler polymer structures and architectures, such as…

Soft Condensed Matter · Physics 2019-03-06 Flora D. Tsourtou , Stavros D. Peroukidis , Loukas D. Peristeras , Vlasis G. Mavrantzas

We applied a multicanonical algorithm (entropic sampling) to a two-dimensional and a three-dimensional Lennard-Jones system with quasicrystalline and glassy ground states. Focusing on the ability of the algorithm to locate low lying energy…

Statistical Mechanics · Physics 2009-10-30 Kamal K. Bhattacharya , James P. Sethna

We performed extensive molecular dynamics (MD) simulations, supplemented by Mode Coupling Theory (MCT) calculations, for the Square Shoulder (SS) model, a purely repulsive potential where the hard-core is complemented by a finite shoulder.…

Soft Condensed Matter · Physics 2015-06-15 Gayatri Das , Nicoletta Gnan , Francesco Sciortino , Emanuela Zaccarelli

We have developed a novel Monte Carlo method for simulating the dynamical evolution of stellar systems in arbitrary geometry. The orbits of stars are followed in a smooth potential represented by a basis-set expansion and perturbed after…

Astrophysics of Galaxies · Physics 2014-12-04 Eugene Vasiliev

We investigate hydrodynamic noise in a dilute granular gas during the homogeneous cooling state, by means of a proper application of the Direct Simulation Monte Carlo (DSMC) algorithm. The DSMC includes a source of randomization which is…

Soft Condensed Matter · Physics 2010-09-27 Giulio Costantini , Andrea Puglisi

Molecular simulation technologies have afforded researchers a unique look into the nanoscale interactions driving physical processes. However, a limitation for molecular dynamics (MD) simulations is that they must be performed on…

Computational Physics · Physics 2022-09-22 Martin Kulke , Josh V Vermaas

We report the results of simulations of the Lebwohl-Lasher model of the nematic-isotropic transition using a new cluster Monte Carlo algorithm. The algorithm is a modification of the Wolff algorithm for spin systems, and greatly reduces…

Soft Condensed Matter · Physics 2009-10-31 N. Priezjev , Robert A. Pelcovits

Recently a new class of Monte Carlo methods, called Time Relaxed Monte Carlo (TRMC), designed for the simulation of the Boltzmann equation close to fluid regimes have been introduced. A generalized Wild sum expansion of the solution is at…

Numerical Analysis · Mathematics 2010-09-16 L. Pareschi , S. Trazzi , B. Wennberg

A new class of Markov chain Monte Carlo (MCMC) algorithms, based on simulating piecewise deterministic Markov processes (PDMPs), have recently shown great promise: they are non-reversible, can mix better than standard MCMC algorithms, and…

Computation · Statistics 2020-10-23 Augustin Chevallier , Paul Fearnhead , Matthew Sutton

New hybrid Molecular Dynamics-Monte Carlo methods are proposed to increase the efficiency of constant-pressure simulations. Two variations of the isobaric Molecular Dynamics component of the algorithms are considered. In the first, we use…

Soft Condensed Matter · Physics 2009-11-07 Roland Faller , Juan J. de Pablo

In this article, we propose a novel and general dimension-hopping MCMC methodology that can update all the parameters as well as the number of parameters simultaneously using simple deterministic transformations of some low-dimensional…

Computation · Statistics 2017-03-16 Moumita Das , Sourabh Bhattacharya

Discrete diffusion models have become highly effective across various domains. However, real-world applications often require the generative process to adhere to certain constraints. To this end, we propose a Sequential Monte Carlo (SMC)…

Machine Learning · Computer Science 2026-03-17 Zijing Ou , Chinmay Pani , Yingzhen Li
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