Tags: Monte Carlo

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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.

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  1. Miguel Angel Gosalvez

    Miguel A. Gosálvez received the M.S. degree (licentiate) in Material Physics in 1996 from Universidad Complutense de Madrid, Spain, and the Ph.D. degree in Computational Physics from Helsinki...

    https://nanohub.org/members/69121

  2. Jul 23 2012

    Illinois 2012: Summer School on Computational Materials Science Quantum Monte Carlo: Theory and Fundamentals

    2012 Icon This school brings together scientists from the fields of geophysics, physics, materials science, chemistry and high-performance computing to learn fundamentals of Quantum Monte Carlo...

    https://nanohub.org/events/details/336

  3. Manual for Archimedes, the GNU Monte Carlo simulator

    25 Jun 2012 | | Contributor(s):: Jean Michel D Sellier

    Please, feel free to download the manual of Archimedes.Archimedes is the GNU package for semiconductor device simulations that has been released for the first time on 2005 under GPL. It has been created by Jean Michel D. Sellier who is, since then, the leader of the project and the main...

  4. Particle Simulations of Ion Generation and Transport in Microelectromechanical Systems and Micropropulsion

    29 May 2012 | | Contributor(s):: Venkattraman Ayyaswamy

    The first part of the talk deals with use of the PIC method with Monte Carlo collisions (MCC) between electrons and the ambient neutral gas to develop models to predict charge accumulation, breakdown voltage, etc. for various ambient gases, gap sizes, cathode material, and frequency of applied...

  5. ECE 656 Lecture 41: Transport in a Nutshell

    21 Feb 2012 | | Contributor(s):: Mark Lundstrom

  6. ECE 656 Lecture 34a: Monte Carlo Simulation I

    21 Feb 2012 | | Contributor(s):: Mark Lundstrom

    OutlineIntroductionReview of carrier scatteringSimulating carrier trajectoriesFree flightCollisionUpdate after collisionPutting it all togetherSummary

  7. ECE 656 Lecture 34b: Monte Carlo Simulation II

    21 Feb 2012 | | Contributor(s):: Mark Lundstrom

    OutlineIntroductionReview of carrier scatteringSimulating carrier trajectoriesFree flightCollisionUpdate after collisionPutting it all togetherSummary

  8. Bhupesh Bishnoi

    https://www.iitk.ac.in/new/bhupesh-bishnoi

    https://nanohub.org/members/62512

  9. ECE 656 Lecture 32: Balance Equation Approach III

    19 Jan 2012 | | Contributor(s):: Mark Lundstrom

    Outline:Review of L31Carrier temperature and heat fluxHeterostructuresSummary

  10. Dierk Raabe

    PROFESSIONAL SKETCHPROF. DIERK RAABEDepartment of Microstructure Physics and Alloy DesignMax-Planck-Institut fuer EisenforschungFax: ++49 –(0)211-6792-278E-mail: d.raabe@mpie.dewww.mpie.de- - - -...

    https://nanohub.org/members/58719

  11. Chih-Wei Lai

    https://nanohub.org/members/58478

  12. Mesoscopic Simulations of Nitromethane

    22 Sep 2011 | | Contributor(s):: Jean-Bernard Maillet

    We present recent developments on the dissipative particle model that allow simulating the physico-chemical behavior of a molecular material at the mesoscale level. Several ingredients have been added to the previous model, in particular concerning the intermolecular force field and the...

  13. Discussion about Ion Channels Using Reduced Model Approaches

    21 Sep 2011 | | Contributor(s):: James Fonseca

    The seminar will cover the reasons how the channels are able to selectively permit the flow of certain species of ions while blocking other physiological cations.

  14. Test for Monte Carlo Learning Module

    30 Jul 2011 | | Contributor(s):: Dragica Vasileska, Gerhard Klimeck

    this is a test for the MC Learning Module.

  15. Bulk Monte Carlo Learning Materials

    By completing the Bulk Monte Carlo Lab exercises and tests, users will be able to: a) understand the way the Boltzmann Transport Equation (BTE) is solved using the Monte Carlo method, b) the...

    https://nanohub.org/wiki/BMC

  16. Buddy Damm

    I am interested in applying computational materials science tools to practicle issues in ferrous metallurgy in order to advance our understanding and applications of steels. My educational...

    https://nanohub.org/members/56465

  17. Monte Carlo and Path Integral Formulation

    30 Jun 2011 | | Contributor(s):: Dragica Vasileska

    This set of handwritten notes is part of the Semiconductor Transport class.

  18. Single Particle and Ensemble Monte Carlo Method

    30 Jun 2011 | | Contributor(s):: Dragica Vasileska

    This set of handwritten notes is part of the Semiconductor Transport class.

  19. How to do 3D quantum monte carlo in Silvaco Atlas

    Q&A|Closed | Responses: 0

    I am trying to simulation LER, RDF, variation of Fin height and fin thickness of tri-gate FINFET. I have access to Silvaco atlas. Do anybody has experience on 3D monter carlo in Silvac Atlas. I...

    https://nanohub.org/answers/question/822

  20. Manual for the Generalized Bulk Monte Carlo Tool

    24 Jun 2011 | | Contributor(s):: Raghuraj Hathwar, Dragica Vasileska

    This manual describes the physics implemented behind the generalized bulk Monte Carlo tool.