Monte Carlo Simulation of Models for Low-Dimensional Conductors

1987 ◽  
pp. 71-86 ◽  
Author(s):  
J. E. Hirsch
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Low Dimensional

Monte Carlo Simulation of Low-Dimensional Nanostructures

1991 ◽  
pp. 177-180
Author(s):  
D. Jovanovic ◽  
S. Briggs ◽  
J. P. Leburton
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Low Dimensional

Monte Carlo simulation of the non-equilibrium critical dynamics of low-dimensional magnetics and multilayer structures

2017 ◽  
Vol 38 (5) ◽  
pp. 944-947 ◽  
Author(s):  
M. V. Mamonova ◽  
I. S. Popov ◽  
P. V. Prudnikov ◽  
V. V. Prudnikov ◽  
A. N. Purtov
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Multilayer Structures ◽  
Critical Dynamics ◽  
Low Dimensional ◽  
Non Equilibrium

scholarly journals Monte Carlo simulation and analytic approximation of epidemic processes on large networks

2013 ◽  
Vol 11 (4) ◽  
Author(s):  
Noémi Nagy ◽  
Péter Simon
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Markov Chain ◽  
Continuous Time ◽  
Analytic Approximation ◽  
Continuous Time Markov Chain ◽  
Expected Number ◽  
The Third ◽  
Low Dimensional ◽  
Cycle Graph

AbstractLow dimensional ODE approximations that capture the main characteristics of SIS-type epidemic propagation along a cycle graph are derived. Three different methods are shown that can accurately predict the expected number of infected nodes in the graph. The first method is based on the derivation of a master equation for the number of infected nodes. This uses the average number of SI edges for a given number of the infected nodes. The second approach is based on the observation that the epidemic spreads along the cycle graph as a front. We introduce a continuous time Markov chain describing the evolution of the front. The third method we apply is the subsystem approximation using the edges as subsystems. Finally, we compare the steady state value of the number of infected nodes obtained in different ways.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

A Monte Carlo simulation study of associated liquid crystals

1999 ◽  
Vol 97 (11) ◽  
pp. 1173-1184 ◽  
Author(s):  
R. Berardi, M. Fehervari, C. Zannoni
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Liquid Crystals ◽  
Simulation Study ◽  
Monte Carlo Simulation Study
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