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Related papers: Multilevel simulation of hard-sphere mixtures

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In this paper the application of the multi-level Monte Carlo (MLMC) method on numerical simulations of turbulent flows with uncertain parameters is investigated. Several strategies for setting up the MLMC method are presented, and the…

Computation · Statistics 2016-08-22 Qingsha Chen , Ju Ming

Simulation in media with multiple continua where each continuum interacts with every other is often challenging due to multiple scales and high contrast. One needs some types of model reduction. One of the approaches is multi-continuum…

Numerical Analysis · Mathematics 2019-06-12 Jun Sur Richard Park , Viet Ha Hoang

This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the…

Computation · Statistics 2017-04-25 Ajay Jasra , Kody Law , Carina Suciu

Sequential Monte Carlo methods have been a major breakthrough in the field of numerical signal processing for stochastic dynamical state-space systems with partial and noisy observations. However, these methods still present certain…

Applications · Statistics 2023-12-14 Samuel Nyobe , Fabien Campillo , Serge Moto , Vivien Rossi

An overview of recent work on Monte Carlo simulations of a granular binary mixture is presented. The results are obtained numerically solving the Enskog equation for inelastic hard-spheres by means of an extension of the well-known direct…

Fluid Dynamics · Physics 2007-05-23 J. M. Montanero

A first-order, Monte Carlo ensemble method has been recently introduced for solving parabolic equations with random coefficients in [26], which is a natural synthesis of the ensemble-based, Monte Carlo sampling algorithm and the…

Numerical Analysis · Mathematics 2018-02-19 Yan Luo , Zhu Wang

Stochastic collocation methods for approximating the solution of partial differential equations with random input data (e.g., coefficients and forcing terms) suffer from the curse of dimensionality whereby increases in the stochastic…

Numerical Analysis · Mathematics 2014-05-23 Aretha L. Teckentrup , Peter Jantsch , Clayton G. Webster , Max Gunzburger

An efficient scheme for one-dimensional extensive air shower simulation and its implementation in the program CONEX are presented. Explicit Monte Carlo simulation of the high-energy part of hadronic and electromagnetic cascades in the…

Astrophysics · Physics 2009-07-22 T. Bergmann , R. Engel , D. Heck , N. N. Kalmykov , S. Ostapchenko , T. Pierog , T. Thouw , K. Werner

Continuous level Monte Carlo is an unbiased, continuous version of the celebrated multilevel Monte Carlo method. The approximation level is assumed to be continuous resulting in a stochastic process describing the quantity of interest.…

Numerical Analysis · Mathematics 2024-02-19 Cedric Aaron Beschle , Andrea Barth

Canonical ensemble Monte Carlo calculations have been carried out on spheres with two different length scales. Radial distribution functions at various temperatures and densities were computed and compared. Preliminary results indicate that…

Statistical Mechanics · Physics 2007-05-23 E. V. R. Chan

The rational function approximation method, density functional theory, and NVT Monte Carlo simulation are used to obtain the density profiles of multicomponent hard-sphere mixtures near a planar hard wall. Binary mixtures with a size ratio…

Statistical Mechanics · Physics 2007-06-06 Alexandr Malijevsky , Santos B. Yuste , Andres Santos , Mariano Lopez de Haro

In this work, we consider the problem of estimating summary statistics to characterise biochemical reaction networks of interest. Such networks are often described using the framework of the Chemical Master Equation (CME). For…

Quantitative Methods · Quantitative Biology 2018-11-27 Christopher Lester , Christian A. Yates , Ruth E. Baker

Many problems in materials science and biology involve particles interacting with strong, short-ranged bonds, that can break and form on experimental timescales. Treating such bonds as constraints can significantly speed up sampling their…

Numerical Analysis · Mathematics 2020-12-02 Miranda Holmes-Cerfon

We present a novel Monte Carlo algorithm which enhances equilibrization of low-temperature simulations and allows sampling of configurations over a large range of energies. The method is based on a non-Boltzmann probability weight factor…

Condensed Matter · Physics 2009-10-30 Ulrich H. E. Hansmann , Yuko Okamoto

We developed an implicit Particle-in-cell/Monte Carlo model in two-dimensional and axisymmetric geometry for the simulations of the radio-frequency discharges, by introducing several numerical schemes which include variable weights,…

Plasma Physics · Physics 2011-04-19 Hong-yu Wang , Wei Jiang , You-nian Wang

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

We consider the application of multilevel Monte Carlo methods to elliptic PDEs with random coefficients. We focus on models of the random coefficient that lack uniform ellipticity and boundedness with respect to the random parameter, and…

Numerical Analysis · Mathematics 2012-04-17 A. L. Teckentrup , R. Scheichl , M. B. Giles , E. Ullmann

We discuss the improvement in the accuracy of a Monte Carlo integration that can be obtained by optimization of the `a-priori weights' of the various channels. These channels may be either the strata in a stratified-sampling approach, or…

High Energy Physics - Phenomenology · Physics 2009-10-28 R. Kleiss , R. Pittau

This chapter is devoted to the computation of equilibrium (thermodynamic) properties of quantum systems. In particular, we will be interested in the situation where the interaction between particles is so strong that it cannot be treated as…

Mesoscale and Nanoscale Physics · Physics 2016-02-03 Alexei Filinov , Jens Böning , Michael Bonitz

We present a new and general Monte Carlo iteration method for generalized ensembles. It consists of two elements: (1) a simple algorithm to distinguish between distributions arising from respectively equilibrium- and non-equilibrium…

Condensed Matter · Physics 2007-05-23 J. Borg
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