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Dynamic Monte Carlo method
About: Dynamic Monte Carlo method is a research topic. Over the lifetime, 13294 publications have been published within this topic receiving 371256 citations.
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22 Nov 2000
235 citations
Book•
26 Sep 2011
TL;DR: Corrections to Conditional Monte Carlo: Gradient Estimation and Optimization Applications by Michael C. Fu and Jian-Qiang Hu can be found at the Internet.
Abstract: Preface. Selected Notation. 1. Introduction. 2. Three Extended Examples. 3. Conditional Monte Carlo Gradient Estimation. 4. Links to Other Settings. 5. Synopsis and Preview. 6. Queueing Systems. 7. (s,S) Inventory Systems. 8. Other Applications. References. Index. Corrections to Conditional Monte Carlo: Gradient Estimation and Optimization Applications (Kluwer International Series in Engineering and Computer Science, 392) by Michael C. Fu and Jian-Qiang Hu can be found at the Internet.
234 citations
TL;DR: The Swendsen-Wang and Wolff Monte Carlo algorithms are described in some detail, using the Potts model as an example, and various generalizations are reviewed.
Abstract: The Swendsen-Wang and Wolff Monte Carlo algorithms are described in some detail, using the Potts model as an example. Various generalizations are then reviewed and some applications are discussed. Two complete Fortran programs for the algorithms are provided.
234 citations
TL;DR: In this article, Monte Carlo calculations of the energies of several low-lying energy states of one-dimensional spin-1 Heisenberg antiferromagnets with linear sizes up to n=32 were performed.
Abstract: We have performed Monte Carlo calculations of the energies of several low-lying energy states of one-dimensional, spin-1 Heisenberg antiferromagnets with linear sizes up to n=32. Our results support Haldane's prediction that a gap exists in the excitation spectrum for n\ensuremath{\rightarrow}\ensuremath{\infty}. .AE
233 citations
02 Jun 1987-Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms
TL;DR: In this paper, the authors concentrate mainly on sputtering calculations with the Monte Carlo code TRIM, which treats ion and recoil transport in amorphous matter and is based on binary collisions with target atoms initially at rest.
Abstract: Monte Carlo simulations have become a useful tool for studying ion radiation effects at or near surfaces or interfaces, such as sputtering, reflection, mixing, etc. The principal advantage of Monte Carlo calculations is that any physical process can be included directly. Also multielement and multilayer targets, even complex geometries, can be treated exactly in order to simulate realistic cases. The present paper will concentrate mainly on sputtering calculations with the Monte Carlo code TRIM, which treats ion and recoil transport in amorphous matter. It is based — as are analytic theories and most other Monte Carlo codes — on binary collisions with target atoms initially at rest. Over the past few years, the basic physical input has been greatly improved. Both the interatomic potentials and the electronic stopping powers proved to be of crucial importance even for the lowest energies occurring in recoil cascades. With the Kr-C or universal potential and the recent ZBL electronic stopping, which includes the Z oscillations, and a planar surface binding energy set equal to the heat of sublimation, realistic sputtering predictions could be obtained for most metals — without the use of any adjustable parameters.
232 citations