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Parameter estimation for discretely observed Markov processes is a challenging problem. However, simulation of Markov processes is straightforward using the Gillespie algorithm. We exploit this ease of simulation to develop an effective…

Computation · Statistics 2014-04-17 Peter Neal

We introduce an algorithm to systematically improve the efficiency of parallel tempering Monte Carlo simulations by optimizing the simulated temperature set. Our approach is closely related to a recently introduced adaptive algorithm that…

Other Condensed Matter · Physics 2007-05-23 Helmut G. Katzgraber , Simon Trebst , David A. Huse , Matthias Troyer

Multiparticle collision dynamics (MPC), a particle-based mesoscale simulation technique for com- plex fluid, is widely employed in non-equilibrium simulations of soft matter systems. To maintain a defined thermodynamic state, thermalization…

Soft Condensed Matter · Physics 2015-03-30 Chien-Cheng Huang , Anoop Varghese , Gerhard Gompper , Roland G. Winkler

Solvent-free coarse grained models represent one of the most promising approaches for molecular simulations of mesoscopically large membranes. In these models, the size of the simulated membrane is limited by the slow relaxation time of…

Soft Condensed Matter · Physics 2009-11-13 Oded Farago

Solid-solid collapse transition in open framework structures is ubiquitous in nature. The real difficulty in understanding detailed microscopic aspects of such transitions in molecular systems arises from the interplay between different…

Soft Condensed Matter · Physics 2015-06-15 Rakesh S. Singh , Biman Bagchi

We study the static and dynamic properties of bromine electrosorption onto single-crystal silver (100) electrodes by Monte Carlo simulation. At room temperature the system displays a second-order phase transition between a low-coverage…

Materials Science · Physics 2009-10-31 S. J. Mitchell , G. Brown , P. A. Rikvold

Which phenomenon slows down the dynamics in super-cooled liquids and turns them into glasses is a long-standing question of condensed-matter. Most popular theories posit that as the temperature decreases, many events must occur in a…

Soft Condensed Matter · Physics 2024-03-22 Massimo Pica Ciamarra , Wencheng Ji , Matthieu Wyart

Is Stochastic Gradient Descent (SGD) substantially different from Metropolis Monte Carlo dynamics? This is a fundamental question at the time of understanding the most used training algorithm in the field of Machine Learning, but it…

Disordered Systems and Neural Networks · Physics 2024-05-31 Maria Chiara Angelini , Angelo Giorgio Cavaliere , Raffaele Marino , Federico Ricci-Tersenghi

We present an algorithm for the simulation of the exact real-time dynamics of classical many-body systems with discrete energy levels. In the same spirit of kinetic Monte Carlo methods, a stochastic solution of the master equation is found,…

Statistical Mechanics · Physics 2016-07-20 Alejandro Mendoza-Coto , Rogelio Díaz-Méndez , Guido Pupillo

The efficiency of Monte Carlo samplers is dictated not only by energetic effects, such as large barriers, but also by entropic effects that are due to the sheer volume that is sampled. The latter effects appear in the form of an entropic…

Computational Physics · Physics 2009-11-13 Cristian Predescu

A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm is shown to thermalize well below the Mode Coupling temperature and to outperform other…

Statistical Mechanics · Physics 2009-05-21 L. A. Fernandez , V. Martin-Mayor , P. Verrocchio

Colloids have a striking relevance in a wide spectrum of industrial formulations, spanning from personal care products to protective paints. Their behaviour can be easily influenced by extremely weak forces, which disturb their…

Soft Condensed Matter · Physics 2018-06-14 Daniel Corbett , Alejandro Cuetos , Matthew Dennison , Alessandro Patti

We use a swap Monte Carlo algorithm to numerically prepare bulk glasses with kinetic stability comparable to that of glass films produced experimentally by physical vapor deposition. By melting these systems into the liquid state, we show…

Soft Condensed Matter · Physics 2017-10-18 Christopher J. Fullerton , Ludovic Berthier

A parallelized hybrid Monte Carlo (HMC) methodology is devised to quantify the microstructural evolution of polycrystalline material under elastic loading. The approach combines a time explicit material point method (MPM) for the mechanical…

Materials Science · Physics 2010-09-03 Liangzhe Zhang , Timothy Bartel , Mark T. Lusk

In this paper, we introduce a dynamical Monte Carlo algorithm for spin models in which the number of the spins fluctuates from zero to a given number by addition and deletion of spins with a probabilistic rule. Such simulations are realized…

Statistical Mechanics · Physics 2009-10-31 Yukito Iba

We introduce an approach based on mirror descent and sequential Monte Carlo (SMC) to perform joint parameter inference and posterior estimation in latent variable models. This approach is based on minimisation of a functional over the…

Computation · Statistics 2025-11-07 Francesca R. Crucinio

A Monte Carlo algorithm to simulate the isothermal recrystallization process of snow is presented. The snow metamorphism is approximated by two mass redistribution processes, surface diffusion and sublimation-deposition. The algorithm is…

Soft Condensed Matter · Physics 2020-07-31 Roman Vetter , Stephan Sigg , Herman M. Singer , Dirk Kadau , Hans J. Herrmann , Martin Schneebeli

Previous studies have suggested a conundrum in the relaxation dynamics of polydisperse supercooled liquids. It has been shown that in two dimensions, the relative relaxation times of particles of different sizes become more similar as the…

Soft Condensed Matter · Physics 2025-03-06 Ilian Pihlajamaa , Lotte van Gessel , Corentin Laudicina , Luc van Burik , Liesbeth Janssen

Metallic glasses are promising materials with unique mechanical and thermal properties, but their atomic-scale dynamics remain challenging to understand. In this work, we develop a unified approach to investigate the glass transition and…

Materials Science · Physics 2025-02-07 Anh D. Phan , Do T. Nga , Ngo T. Que , Hailong Peng , Thongchanh Norhourmour , Le M. Tu

We present two Diffusion Monte Carlo (DMC) algorithms for systems of ultracold quantum gases featuring synthetic spin-orbit interactions. The first one is a discrete spin generalization of the T- moves spin-orbit DMC, which provides an…

Quantum Gases · Physics 2018-12-05 J. Sanchez-Baena , J. Boronat , F. Mazzanti
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