Monte Carlo in statistical physics refers to the application of the Monte Carlo method to problems in statistical physics, or statistical mechanics. The...

Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical...

In physics, statistical mechanics is a mathematical framework that applies statistical methods and probability theory to large assemblies of microscopic...

War: Rome II's implementation in the high level campaign AI) and applications outside of games. The Monte Carlo method, which uses random sampling for...

In statistics and statistical physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random...

Metropolis Monte Carlo simulation to molecular systems. It is therefore also a particular subset of the more general Monte Carlo method in statistical physics...

"Simulation of Liquids and Solids. Molecular Dynamics and MonteCarlo Methods in Statistical Mechanics. A reprint Book". G. Ciccotti, D. Frenkel and I. R. Mc...

kinetic Monte Carlo (KMC) method is a Monte Carlo method computer simulation intended to simulate the time evolution of some processes occurring in nature...

Biology Monte Carlo methods (BioMOCA) have been developed at the University of Illinois at Urbana-Champaign to simulate ion transport in an electrolyte...

Collocation Monte Carlo sampler (SCMC sampler) within a polynomial chaos expansion framework. This allows us to generate any number of Monte Carlo samples...

Particle filters, also known as sequential Monte Carlo methods, are a set of Monte Carlo algorithms used to find approximate solutions for filtering problems...

Path integral Monte Carlo (PIMC) is a quantum Monte Carlo method used to solve quantum statistical mechanics problems numerically within the path integral...

The Monte Carlo method for electron transport is a semiclassical Monte Carlo (MC) approach of modeling semiconductor transport. Assuming the carrier motion...

include statistical mechanics, renormalization group, rough path theory, etc. Kinetic Monte Carlo (KMC) is a form of computer simulation in which atoms...

method or Monte Carlo wave function (MCWF) method, developed by Dalibard, Castin and Mølmer. Other contemporaneous works on wave-function-based Monte...

point for the applications of the Monte Carlo method to statistical mechanics and the Markov chain Monte Carlo literature in Bayesian statistics. Teller was...

outcomes for the project. The method can be understood as an extension of the net present value (NPV) multi-scenario Monte Carlo model with an adjustment for...

The Reverse Monte Carlo (RMC) modelling method is a variation of the standard Metropolis–Hastings algorithm to solve an inverse problem whereby a model...

in convex optimization. Several exact or inexact Monte-Carlo-based algorithms exist: In this method, random simulations are used to find an approximate...

particle models, and particle Markov chain Monte Carlo methods In physics, and more particularly in statistical mechanics, these nonlinear evolution equations...

introduced a new Monte Carlo computational method for doing so. In applications of the Monte Carlo method to problems in statistical mechanics prior to the...

15 August 1926) is a Russian mathematician, known for his work on Monte Carlo methods. His research spans several applications, from nuclear studies to...

In physics, specifically statistical mechanics, an ensemble (also statistical ensemble) is an idealization consisting of a large number of virtual copies...

Direct simulation Monte Carlo (DSMC) method uses probabilistic Monte Carlo simulation to solve the Boltzmann equation for finite Knudsen number fluid flows...

in a presentation titled "Genesis of the Monte Carlo Algorithm for Statistical Mechanics". Further historical clarification is made by Gubernatis in a...

polymer. Monte Carlo in the context of materials science most often refers to atomistic simulations relying on rates. In kinetic Monte Carlo (kMC) rates...

-C.; Barkema, G.T. (2015). "An introduction to Monte Carlo methods". Physica A: Statistical Mechanics and Its Applications. 418: 78–87. arXiv:1404.0209...

is known in the computational physics community for the Swendsen-Wang algorithm, the Monte Carlo Renormalization Group, and related methods that enable...

simulation method aimed at improving the dynamic properties of Monte Carlo method simulations of physical systems, and of Markov chain Monte Carlo (MCMC)...

semi-empirical methods, density functional theory, Hartree–Fock calculations, quantum Monte Carlo methods, and coupled cluster methods. Understanding...