Tags: Monte Carlo

Description

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.

All Categories (1-20 of 79)

  1. IWCN 2021: Effective Monte Carlo Simulator of Hole Transport in SiGe alloys

    25 Jul 2021 | | Contributor(s):: Caroline dos Santos Soares, Alan Rossetto, Dragica Vasileska, Gilson Wirth

    In this work, an Ensemble Monte Carlo (EMC) transport simulator is presented for simulation of hole transport in SiGe alloys.

  2. IWCN 2021: Computational Research of CMOS Channel Material Benchmarking for Future Technology Nodes: Missions, Learnings, and Remaining Challenges

    15 Jul 2021 | | Contributor(s):: raseong kim, Uygar Avci, Ian Alexander Young

    In this preentation, we review our journey of doing CMOS channel material benchmarking for future technology nodes. Through the comprehensive computational research for past several years, we have successfully projected the performance of various novel material CMOS based on rigorous physics...

  3. MIT Atomic-Scale Modeling Toolkit

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

    Tools for Atomic-Scale Modeling

  4. Gibbs Adsorption Simulator

    23 Sep 2019 | | Contributor(s):: Julian C Umeh, Thomas A Manz

    Simulates the adsorption of gases using Gibbs ensemble

  5. Mixed Gas Diffusion Calculator

    25 Jun 2019 | | Contributor(s):: Julian C Umeh, Thomas A Manz

    Simulates the diffusion of a gas mixture onto a metal organic framework

  6. VLE Simulator

    10 Jun 2019 | | Contributor(s):: Julian C Umeh, Thomas A Manz

    Simulates the vapor liquid equilibrium of the first five Alkanes

  7. Gas Adsorption Calculator

    07 Mar 2019 | | Contributor(s):: Julian C Umeh, Thomas A Manz

    Simulates gas adsorption onto metal organic frameworks

  8. Multi-walled/Single-walled Carbon Nanotube (MWCNT/SWCNT) Interconnect Lumped Compact Model Considering Defects, Contact resistance and Doping impact

    11 Jul 2018 | Compact Models | Contributor(s):

    By Rongmei Chen1, Jie LIANG1, Jaehyun Lee2, Vihar Georgiev2, Aida Todri1

    1. CNRS 2. University of Glasgow

    In this project, we present SWCNT and MWCNT interconnect compact models. These models consider the impact of CNT defects, the chirality and contact resistance between CNT-electrode (Pd) on CNT...

    https://nanohub.org/publications/243/?v=1

  9. ME 597UQ Lecture 24: Bayesian Model Comparison using Sequential Monte Carlo

    10 Apr 2018 | | Contributor(s):: Ilias Bilionis

  10. Novel EM Nanoscale Techniques

    27 Nov 2017 | | Contributor(s):: Brian Demczyk

    Describes unconventional use of conventional techniques (SAD,CBED, HREM and Fourier analysis) to elucidate hard-to-access structural information at the nano scale.

  11. ZENO

    16 Nov 2016 | | Contributor(s):: Derek Juba, Debra Audus, Michael Mascagni, Jack Douglas, Walid Keyrouz

    Calculation of hydrodynamic, electrical, and shape properties of polymer and particle suspensions

  12. Michael Worku

    https://nanohub.org/members/150665

  13. Memory-Efficient Particle Annihilation Algorithm for Wigner Monte Carlo Simulations

    10 Feb 2016 | | Contributor(s):: Paul Ellinghaus

    IWCE 2015 presentation. The Wigner Monte Carlo solver, using the signed-particle method, is based on the generation and annihilation of numerical particles. The memory demands of the annihilation algorithm can become exorbitant, if a high spatial resolution is used, because the entire discretized...

  14. High Dimensional Uncertainty Quantification via Multilevel Monte Carlo

    02 Feb 2016 | | Contributor(s):: Hillary Fairbanks

    Multilevel Monte Carlo (MLMC) has been shown to be a cost effective way to compute moments of desired quantities of interest in stochastic partial differential equations when the uncertainty in the data is high-dimensional. In this talk, we investigate the improved performance of MLMC versus...

  15. Multilevel Markov Chain Monte Carlo for Uncertainty Quantification in Subsurface Flow

    02 Feb 2016 | | Contributor(s):: Christian Ketelsen

    The multilevel Monte Carlo method has been shown to be an effective variance reduction technique for quantifying uncertainty in subsurface flow simulations when the random conductivity field can be represented by a simple prior distribution. In state-of-the-art subsurface simulation the...

  16. Study of the Interface Roughness Models using 3D Finite Element Schrödinger Equation Corrected Monte Carlo Simulator on Nanoscaled FinFET

    16 Dec 2015 | | Contributor(s):: Daniel Nagy, Muhammad Ali A. Elmessary, Manuel Aldegunde, Karol Kalna

    IWCE 2015 presentation.  Interface roughness scattering (IRS) is one of the key limiting scattering mechanism for both planar and non-planar CMOS devices. To predict the performance of future scaled devices and new structures the quantum mechanical confinement based IRS models are essential....

  17. Sensitivity Analysis of Multiscale Reaction Networks with Stochastic Averaging

    21 Jan 2016 | | Contributor(s):: Araz Ryan Hashemi

    We shall show how stochastic averaging may be employed to speed computations and obtain estimates of mean values and sensitivities with respect to the steady state distribution. Further, we shall establish bounds which show the bias induced by the averaging method decays to zero as the disparity...

  18. Anisotropic Schrödinger Equation Quantum Corrections for 3D Monte Carlo Simulations of Nanoscale Multigate Transistors

    16 Dec 2015 | | Contributor(s):: Karol Kalna, Muhammad Ali A. Elmessary, Daniel Nagy, Manuel Aldegunde

    IWCE 2015 presentation. We incorporated anisotropic 2D Schrodinger equation based quantum corrections (SEQC) that depends on valley orientation into a 3D Finite Element (FE) Monte Carlo (MC) simulation toolbox. The MC toolbox was tested against experimental ID-VG characteristics of the 22 nm gate...

  19. Atomistic Modeling: Past, Present, and Future, MGI, ICME, etc.

    03 Nov 2015 | | Contributor(s):: Paul Saxe

    I will present a perspective on atomistic modeling — tools using quantum methods such as DFT, as well as molecular dynamics and Monte Carlo methods based on forcefields — over the past 30 years or so. While we are all caught up in the present, it is important to remember and realize...

  20. Lecture 3: The Wigner Monte Carlo Method for Density Functional Theory

    15 Nov 2014 | | Contributor(s):: Jean Michel D Sellier

    In this lecture, Dr. Sellier discusses the Wigner Monte Carlo method in the framework of density functional theory (DFT).