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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.

Tools (1-9 of 9)

  1. Exciton Dynamics Simulator

    31 Dec 2012 | Tools | Contributor(s): Michael Heiber

    Simulates the exciton dynamics in organic photovolatic devices

  2. Archimedes, GNU Monte Carlo simulator

    29 May 2008 | Tools | Contributor(s): Jean Michel D Sellier

    GNU Monte Carlo simulation of 2D semiconductor devices, III-V materials

  3. biomoca

    30 May 2006 | Tools | Contributor(s): Reza Toghraee, Umberto Ravaioli

    Ion channel simulator

  4. BioMOCA Suite

    04 Feb 2008 | Tools | Contributor(s): David Papke, Reza Toghraee, Umberto Ravaioli, Ankit Raj

    Simulates ion flow through a channel.

  5. MIT Atomic Scale Modeling Toolkit

    15 Jan 2008 | Tools | Contributor(s): daniel richards, Elif Ertekin, Jeffrey C Grossman, David Strubbe, Justin Riley

    Tools for Atomic Scale Modeling

  6. QWalk Quantum Monte Carlo Tutorial

    15 Jun 2007 | Tools | Contributor(s): Lucas Wagner, Jeffrey C Grossman, Jeffrey B. Neaton, Ian Michael Rousseau

    An accurate method to calculate the many body ground state of electrons

  7. Illinois Tools: MOCA

    28 Mar 2007 | Tools | Contributor(s): Mohamed Mohamed, Umberto Ravaioli, Nahil Sobh, derrick kearney

    A 2D Full-band Monte Carlo (MOCA) Simulation of SOI Device Structures

  8. QuaMC2D

    13 Mar 2006 | Tools | Contributor(s): Shaikh S. Ahmed, Dragica Vasileska

    Quantum-corrected Monte-Carlo transport simulator for two-dimensional MOSFET devices.

  9. demons

    31 Oct 2006 | Tools | Contributor(s): M. E. Klausmeier-Brown, C. M. Maziar, P. E. Dodd, M. A. Stettler, Xufeng Wang, Gerhard Klimeck

    Improved program consists of DEMON and SDEMON, a resource for nanoscience and nanotechnology, is supported by the National Science Foundation and other funding agencies. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.