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Coulomb and log-gases are exchangeable singular Boltzmann-Gibbs measures appearing in mathematical physics at many places, in particular in random matrix theory. We explore experimentally an efficient numerical method for simulating such…

Probability · Mathematics 2019-02-28 Djalil Chafaï , Grégoire Ferré

In this paper, we present the Monte-Carlo Compressive Optimization algorithm, a new method to solve a combinatorial optimization problem that is assumed compressible. The method relies on random queries to the objective function in order to…

Optimization and Control · Mathematics 2025-10-30 Baptiste Chevalier , Shimpei Yamaguchi , Wojciech Roga , Masahiro Takeoka

The advances in materials and biological sciences have necessitated the use of molecular simulations to study polymers. The Markov chain Monte Carlo simulations enable the sampling of relevant microstates of polymeric systems by traversing…

Soft Condensed Matter · Physics 2023-07-24 Monika Angwani , Tushar Mahendrakar , Kaustubh Rane

Many modern production and measurement facilities incorporate multiphase systems at low pressures. In this region of flows at small, non-zero Knudsen- and low Mach numbers the classical mesoscopic Monte Carlo methods become increasingly…

Fluid Dynamics · Physics 2015-09-10 S. Schmieschek , D. K. N. Sinz , F. Keller , U. Nieken , J. Harting

Monte Carlo simulations are a powerful tool to investigate the thermodynamic properties of atomic systems. In practice however, sampling of the complete configuration space is often hindered by high energy barriers between different regions…

Statistical Mechanics · Physics 2020-05-04 Jonas A. Finkler , Stefan Goedecker

In the replica-exchange molecular dynamics method, where constant-temperature molecular dynamics simulations are performed in each replica, one usually rescales the momentum of each particle after replica exchange. This rescaling method had…

Statistical Mechanics · Physics 2010-04-14 Yoshiharu Mori , Yuko Okamoto

Sequential Monte Carlo Samplers are a class of stochastic algorithms for Monte Carlo integral estimation w.r.t. probability distributions, which combine elements of Markov chain Monte Carlo methods and importance sampling/resampling…

Probability · Mathematics 2007-05-23 Andreas Eberle , Carlo Marinelli

We demonstrate that the multicanonical approach is not restricted to Monte Carlo simulations, but can also be applied to simulation techniques such as molecular dynamics, Langevin, and hybrid Monte Carlo algorithms. The effectiveness of the…

Chemical Physics · Physics 2007-05-23 Ulrich H. E. Hansmann , Yuko Okamoto , Frank Eisenmenger

Quantum Monte Carlo (QMC) methods can very accurately compute ground state properties of quantum systems. We applied these methods to a system of boson hard spheres to get exact, infinite system size results for the ground state at several…

Computational Physics · Physics 2016-09-08 Mark Dewing

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

We study the 38-atom Lennard-Jones cluster with parallel tempering Monte Carlo methods in the microcanonical and molecular dynamics ensembles. A new Monte Carlo algorithm is presented that samples rigorously the molecular dynamics ensemble…

Chemical Physics · Physics 2009-11-06 F. Calvo , J. P. Neirotti , David L. Freeman , J. D. Doll

Computer simulation methods, such as Monte Carlo or Molecular Dynamics, are very powerful computational techniques that provide detailed and essentially exact information on classical many-body problems. With the advent of ab-initio…

Chemical Physics · Physics 2014-06-23 Thomas D. Kühne

We present a hybrid continuum-atomistic scheme which combines molecular dynamics (MD) simulations with on-the-fly machine learning techniques for the accurate and efficient prediction of multiscale fluidic systems. By using a Gaussian…

Fluid Dynamics · Physics 2016-03-16 David Stephenson , James R Kermode , Duncan A Lockerby

First of all, this paper presents some improvements of DSMC method in the form of new schemes and approaches, that, for a wide class of problems, increase performance and reduce the demands on computer resources. The most important…

Fluid Dynamics · Physics 2012-01-16 Roman V. Maltsev

A Monte Carlo method based on a density-of-states sampling is proposed for study of arbitrary statistical mechanical ensembles in a continuum. A random walk in the two-dimensional space of particle number and energy is used to estimate the…

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

Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform…

Statistical Mechanics · Physics 2015-06-19 Jean-Charles Walter , Gerard Barkema

Molecular dynamics simulations require barostats to be performed at constant pressure. The usual recipe is to employ the Berendsen barostat first, which displays a first-order volume relaxation efficient in equilibration but results in…

Computational Physics · Physics 2020-09-17 Mattia Bernetti , Giovanni Bussi

Monte Carlo simulations at constant pressure are performed to study coexistence and interfacial properties of the liquid-solid transition in hard spheres and in colloid-polymer mixtures. The latter system is described as a one-component…

Soft Condensed Matter · Physics 2015-05-18 T. Zykova-Timan , J. Horbach , K. Binder

The study of the high pressure phase diagram of hydrogen has continued with renewed effort for about one century as it remains a fundamental challenge for experimental and theoretical techniques. Here we employ an efficient molecular…

Chemical Physics · Physics 2014-04-23 Guglielmo Mazzola , Seiji Yunoki , Sandro Sorella

A general synthetic iterative scheme is proposed to solve the Enskog equation within a Monte Carlo framework. The method demonstrates rapid convergence by reducing intermediate Monte Carlo evolution and preserves the asymptotic-preserving…

Fluid Dynamics · Physics 2025-09-26 Bin Hu , Liyan Luo , Lei Wu