Quantum Monte Carlo Techniques and Defects in Semiconductors

2006 ◽  
pp. 141-164 ◽  
Author(s):  
R. J. Needs
Keyword(s):  
Monte Carlo ◽  
Quantum Monte Carlo ◽  
Monte Carlo Techniques ◽  
Defects In Semiconductors

scholarly journals STRUCTURE AND SPECTROSCOPY OF DOPED HELIUM CLUSTERS USING QUANTUM MONTE CARLO TECHNIQUES

2003 ◽  
Vol 17 (28) ◽  
pp. 5267-5277 ◽  
Author(s):  
ALEXANDRA VIEL ◽  
K. BIRGITTA WHALEY
Keyword(s):  
Monte Carlo ◽  
Quantum Monte Carlo ◽  
Fluid Model ◽  
Direct Determination ◽  
Rotational Constant ◽  
Excitation Energies ◽  
Monte Carlo Techniques ◽  
Monte Carlo Studies ◽  
Two Fluid Model ◽  
Two Fluid

We present a comparative study of the rotational characteristics of various molecule-doped 4 He clusters using quantum Monte Carlo techniques. The theoretical conclusions obtained from both zero and finite temperature Monte Carlo studies confirm the presence of two different dynamical regimes that correlate with the magnitude of the rotational constant of the molecule, i.e. fast or slow rotors. For a slow rotor, the effective rotational constant for the molecule inside the helium droplet can be determined by a microscopic two-fluid model in which helium densities computed by path integral Monte Carlo are used as input, as well as by direct computation of excited energy levels. For a faster rotor, the conditions for application of the two-fluid model for dynamical analysis are usually not fulfilled and the direct determination of excitation energies is then mandatory. Quantitative studies for three molecules are summarised, showing in each case excellent agreement with experimental results.

VARIATIONAL COMPUTATIONS FOR EXCITONS IN QUANTUM DOTS: A QUANTUM MONTE CARLO STUDY

2011 ◽  
Vol 25 (01) ◽  
pp. 119-130
Author(s):  
A. YILDIZ ◽  
S. ŞAKİROĞLU ◽  
Ü. DOĞAN ◽  
K. AKGÜNGÖR ◽  
H. EPİK ◽  
...  
Keyword(s):  
Quantum Dots ◽  
Monte Carlo ◽  
Ground State ◽  
Quantum Monte Carlo ◽  
Three Dimensional ◽  
Monte Carlo Study ◽  
Wave Functions ◽  
Monte Carlo Techniques ◽  
Oscillator Basis ◽  
Ground State Energies

A study of variational wave functions for calculation of the ground-state energies of excitons confined in a two-dimensional (2D) disc-like and three-dimensional (3D) spherical parabolic GaAs quantum dots (QDs) is presented. We have used four variational trial wave functions constructed as the harmonic-oscillator basis multiplied by different correlation functions. The proposed correlation function formed by including linear expansion in terms of Hylleraas-like coordinates to the Jastrow factor is able to capture nearly exactly the ground-state energies of 3D excitons, and it properly account for the results of 2D excitons. Quantum Monte Carlo techniques combined with the proposed wave function are a powerful tool for studying excitons in parabolic QDs.

scholarly journals A comparison between quantum chemistry and quantum Monte Carlo techniques for the adsorption of water on the (001) LiH surface

2017 ◽  
Vol 146 (20) ◽  
pp. 204108 ◽  
Author(s):  
Theodoros Tsatsoulis ◽  
Felix Hummel ◽  
Denis Usvyat ◽  
Martin Schütz ◽  
George H. Booth ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Quantum Chemistry ◽  
Quantum Monte Carlo ◽  
Monte Carlo Techniques ◽  
Adsorption Of Water

Bayesian Estimation of DSGE Models

2015 ◽  
Author(s):  
Edward P. Herbst ◽  
Frank Schorfheide
Keyword(s):  
Monte Carlo ◽  
Sequential Monte Carlo ◽  
Likelihood Function ◽  
Academic Research ◽  
Dynamic Stochastic General Equilibrium ◽  
Computational Techniques ◽  
Dsge Models ◽  
Monte Carlo Techniques ◽  
Dynamic Stochastic ◽  
Theoretical Foundations

Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. The book is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

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