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. Generalized Monte Carlo Presentation

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

    This presentation goes along with the Bulk Monte Carlo tool on the nanoHUB that calculates transients and steady-state velocity-field characteristics of arbitrary materials such as Si, Ge, GaAs, GaN, SiC, etc. The tool employs a non-parabolic bandstructure.

  2. Monte Carlo Method and Its Applications

    29 Jan 2011 | Contributor(s):: Dragica Vasileska

    This book chapter describes the solution of the Boltzmann transport equation via the MC method and it also presents its application of various types of devices simulations.

  3. High Field Transport and the Monte Carlo Method for the Solution of the Boltzmann Transport Equation

    23 Jul 2010 | Contributor(s):: Dragica Vasileska

    This set of slides first describes the path-integral solution of the BTE and then discusses in details the Monte Carlo Method for the Solution of the Boltzmann Transport Equation.

  4. Goranka Bilalbegovic

    https://nanohub.org/members/45672

  5. Atomistic Simulations of Reliability

    06 Jul 2010 | Contributor(s):: Dragica Vasileska

    Discrete impurity effects in terms of their statistical variations in number and position in the inversion and depletion region of a MOSFET, as the gate length is aggressively scaled, have recently been researched as a major cause of reliability degradation observed in intra-die and die-to-die...

  6. Bulk Monte Carlo: Implementation Details and Source Codes Download

    01 Jun 2010 | Contributor(s):: Dragica Vasileska, Stephen M. Goodnick

    The Ensemble Monte Carlo technique has been used now for over 30 years as a numerical method to simulate nonequilibrium transport in semiconductor materials and devices, and has been the subject of numerous books and reviews. In application to transport problems, a random walk is generated to...

  7. Darwin Barayang Putungan

    https://nanohub.org/members/43753

  8. Lecture 7: Initialization and Equilibrium

    Presentation Materials | 05 Jan 2010 | Contributor(s):: Ashlie Martini

    Topics:Initial positionsInitial velocitiesEvaluating equilibrium

  9. ECE 656 Lecture 31: Monte Carlo Simulation

    Online Presentations | 01 Dec 2009 | Contributor(s):: Mark Lundstrom

    Outline:IntroductionReview of carrier scatteringSimulating carrier trajectoriesFree flightCollisionUpdate after collisionPutting it all togetherSummary

  10. ECE 656 Lecture 30: Balance Equation Approach III

    Online Presentations | 01 Dec 2009 | Contributor(s):: Mark Lundstrom

    OutlineCarrier Temperature and Heat FluxBalance equations in 3DHeterostructuresSummary

  11. From Semi-Classical to Quantum Transport Modeling: Particle-Based Device Simulations

    Teaching Materials | 10 Aug 2009 | Contributor(s):: Dragica Vasileska

    This set of powerpoint slides series provides insight on what are the tools available for modeling devices that behave either classically or quantum-mechanically. An in-depth description is provided to the approaches with emphasis on the advantages and disadvantages of each approach. Conclusions...

  12. Band Structure Lab: First-Time User Guide

    Teaching Materials | 15 Jun 2009 | Contributor(s):: Abhijeet Paul, Benjamin P Haley, Gerhard Klimeck

    This document provides useful information about Band Structure Lab. First-time users will find basic ideas about the physics behind the tool such as band formation, the Hamiltonian description, and other aspects. Additionally, we provide explanations of the input settings and the results of the...

  13. Illinois PHYS 466, Lecture 18: Kinetic Monte Carlo (KMC)

    Online Presentations | 04 May 2009 | Contributor(s):: David M. Ceperley, Omar N Sobh

  14. Archimedes, GNU Monte Carlo simulator

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

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

  15. Illinois MatSE485/Phys466/CSE485 - Atomic-Scale Simulation

    0.0 out of 5 stars 

    Courses | 27 Jan 2009 | Contributor(s):: David M. Ceperley

    THE OBJECTIVE is to learn and apply fundamental techniques used in (primarily classical) simulations in order to help understand and predict properties of microscopic systems in materials science, physics, chemistry, and biology. THE EMPHASIS will be on connections between the simulation...

  16. Quantum and Thermal Effects in Nanoscale Devices

    4.5 out of 5 stars 

    Online Presentations | 18 Sep 2008 | Contributor(s):: Dragica Vasileska

    To investigate lattice heating within a Monte Carlo device simulation framework, we simultaneously solve the Boltzmann transport equation for the electrons, the 2D Poisson equation to get the self-consistent fields and the hydrodynamic equations for acoustic and optical phonons. The phonon...

  17. Homework Assignment for Bulk Monte Carlo Lab: Velocity vs. Field for Arbitrary Crystallographic Orientations

    0.0 out of 5 stars 

    Teaching Materials | 21 Aug 2008 | Contributor(s):: Dragica Vasileska, Gerhard Klimeck

    User needs to calculate and compare to experiment the velocity field characteristics for electrons in Si for different crystalographic directions and 77K and 300K temperatures.

  18. Bulk Monte Carlo Lab

    3.0 out of 5 stars 

    Tools | 27 Apr 2008 | Contributor(s):: Dragica Vasileska, Mark Lundstrom, Stephen M. Goodnick, Gerhard Klimeck

    This tool calculates the bulk values of the carrier drift velocity and average electron energy in any material in which the conduction band is represented by a three valley model. Examples include Si, Ge and GaAs.

  19. Homework Assignment for Bulk Monte Carlo Lab: Arbitrary Crystallographic Direction

    0.0 out of 5 stars 

    Teaching Materials | 20 Aug 2008 | Contributor(s):: Dragica Vasileska, Gerhard Klimeck

    This exercise teaches the users how the average carrier velocity, average carrier energy and vally occupation change with the application of the electric field in arbitrary crystalographic direction

  20. Spin Coupled Quantum Dots

    0.0 out of 5 stars 

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

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