Support

Support Options

Submit a Support Ticket

 

Tags: quantum Monte Carlo

Resources (1-6 of 6)

  1. Computational Nanoscience, Lecture 20: Quantum Monte Carlo, part I

    15 May 2008 | Teaching Materials | Contributor(s): Elif Ertekin, Jeffrey C Grossman

    This lecture provides and introduction to Quantum Monte Carlo methods. We review the concept of electron correlation and introduce Variational Monte Carlo methods as an approach to going beyond...

    http://nanohub.org/resources/4564

  2. Computational Nanoscience, Lecture 21: Quantum Monte Carlo, part II

    15 May 2008 | Teaching Materials | Contributor(s): Jeffrey C Grossman, Elif Ertekin

    This is our second lecture in a series on Quantum Monte Carlo methods. We describe the Diffusion Monte Carlo approach here, in which the approximation to the solution is not restricted by choice...

    http://nanohub.org/resources/4566

  3. Computational Nanoscience, Lecture 4: Geometry Optimization and Seeing What You're Doing

    13 Feb 2008 | Teaching Materials | Contributor(s): Jeffrey C Grossman, Elif Ertekin

    In this lecture, we discuss various methods for finding the ground state structure of a given system by minimizing its energy. Derivative and non-derivative methods are discussed, as well as the...

    http://nanohub.org/resources/4035

  4. 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

    http://nanohub.org/resources/ucb_compnano

  5. Path Integral Monte Carlo

    13 Dec 2007 | Tools | Contributor(s): John Shumway, Matthew Gilbert

    Tool Description

    http://nanohub.org/resources/pimc

  6. Spin Coupled Quantum Dots

    09 Jul 2008 | Tools | Contributor(s): John Shumway, Matthew Gilbert

    Path integral calculation of exchange coupling of spins in neighboring quantum dots.

    http://nanohub.org/resources/spincoupleddots

nanoHUB.org, 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.