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Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results. Monte Carlo methods are often used in simulating physical and mathematical systems. Because of their reliance on repeated computation of random or pseudo-random numbers, these methods are most suited to calculation by a computer and tend to be used when it is unfeasible or impossible to compute an exact result with a deterministic algorithm.
Learn more about quantum dots from the many resources on this site, listed below. More information on Monte Carlo method can be found here.
Novel EM Nanoscale Techniques
27 Nov 2017 | | Contributor(s):: Brian Demczyk
Describes unconventional use of conventional techniques (SAD,CBED, HREM and Fourier analysis) to elucidate hard-to-access structural information at the nano scale.
kinetic Monte Carlo Simulations (kMC)
25 Mar 2014 | | Contributor(s):: Jingyuan Liang, R. Edwin García, Ding-Wen Chung
kMC is a set of scientific libraries designed to deploy kinetic Monte Carlo simulations (kMC). kMC allows the user to intuitively generate single component crystal lattices to simulate, post process, and visualize the kinetic Monte Carlo-based dynamics of materials.Philosophically, kMC was...
Lecture 7: Initialization and Equilibrium
05 Jan 2010 | | Contributor(s):: Ashlie Martini
Topics:Initial positionsInitial velocitiesEvaluating equilibrium