MONTE CARLO SIMULATION OF STEADY-STATE TRANSPORT IN SUBMICROMETER InP AND GaAsn+–i(n)–n+ DIODE

2010 ◽  
Vol 24 (06) ◽  
pp. 549-560 ◽  
Author(s):  
H. ARABSHAHI ◽  
M. REZAEE ROKN-ABADI ◽  
F. BADIEIAN BAGHSIAHI ◽  
M. R. KHALVATI

Monte Carlo simulation of electron transport in an InP diode of n+–i(n)–n+ structure is compared with GaAs diode. The anode voltage ranges from 0.5 to 1.5 V. The distributions of electron energies and electron velocities and the profiles of the electron density, electric field and potential and average electron velocity are computed. Based on these data, the near ballistic nature of the electron transport in the 0.2 μm-long diode and the importance of the back-scattering of electrons from the anode n+-layer are discussed. In addition, the effects of the lattice temperature and doping on the length of the active layer are discussed. Electronic states within the conduction band valleys at the Γ, L, and X are represented by non-parabolic ellipsoidal valleys centered on important symmetry points of the Brillouin zone. Our simulation results have also shown that the electron velocity characteristics in InP diode are more sensitive to temperature than in other III–V semiconductors such as GaAs .

2007 ◽  
Vol 21 (05) ◽  
pp. 287-294 ◽  
Author(s):  
H. ARABSHAHI

Monte Carlo simulation of electron transport in a GaN diode of n+nn+ structure with a 0.4 or 0.6 μm long active layer is described. The anode voltage ranges from 10 to 50 V. The distributions of electron energies and electron velocities, and the profiles of the electron density, electric field, potential and average electron velocity are computed. Based on these data, the near ballistic nature of the electron transport in the 0.4 μm-long diode and the importance of the back-scattering of electrons from the anode n+-layer are discussed. Also, the effects of the lattice temperature and doping on the length of the active layer are discussed.


2007 ◽  
Vol 21 (04) ◽  
pp. 199-206 ◽  
Author(s):  
H. ARABSHAHI

An ensemble Monte Carlo simulation has been used to model bulk electron transport at 300 K for both the natural wurtzite and the zincblende lattice phases of GaN . Electronic states within the conduction band are represented by non-parabolic ellipsoidal valleys centred on important symmetry points of the Brillouin zone, but for zincblende GaN , the simpler spherical parabolic band approximation has also been tested, for comparison. In the case of wurtzite GaN , transport has been modeled with an electric field applied both parallel and perpendicular to the (0001) c-axis. The steady state velocity-field characteristics are in fair agreement with other recent calculations.


2020 ◽  
Vol 26 (4) ◽  
pp. 263-271
Author(s):  
Evgenia Kablukova ◽  
Karl Sabelfeld ◽  
Dmitrii Y. Protasov ◽  
Konstantin S. Zhuravlev

AbstractMonte Carlo algorithms are developed to simulate the electron transport in semiconductors. In particular, the drift velocity in GaN semiconductors is calculated, and a comparison with experimental measurements is discussed. Explicit expressions for the scattering probabilities and distributions of the scattering angle of electrons on polar optical and intervalley phonons, and acoustic deformation potential as well are given. A good agreement of the simulation results and the experimental measurements reveals that the M-L valley is located at 0.7 eV higher than the Γ-valley. This value agrees with other experimental studies, while it is lower compared to ab initio calculations.


1997 ◽  
Vol 36 (8-9) ◽  
pp. 265-269
Author(s):  
Govert D. Geldof

In the practice of integrated water management we meet complexity, subjectivity and uncertainties. Uncertainties come into play when new urban water management techniques are applied. The art of a good design is not to reduce uncertainties as much as possible, but to find the middle course between cowardice and recklessness. This golden mean represents bravery. An interdisciplinary approach is needed to reach consensus. Calculating uncertainties by using Monte Carlo simulation results may be helpful.


2021 ◽  
Vol 48 (4) ◽  
pp. 53-61
Author(s):  
Andrea Marin ◽  
Carey Williamson

Craps is a simple dice game that is popular in casinos around the world. While the rules for Craps, and its mathematical analysis, are reasonably straightforward, this paper instead focuses on the best ways to cheat at Craps, by using loaded (biased) dice. We use both analytical modeling and simulation modeling to study this intriguing dice game. Our modeling results show that biasing a die away from the value 1 or towards the value 5 lead to the best (and least detectable) cheating strategies, and that modest bias on two loaded dice can increase the winning probability above 50%. Our Monte Carlo simulation results provide validation for our analytical model, and also facilitate the quantitative evaluation of other scenarios, such as heterogeneous or correlated dice.


2021 ◽  
Vol 49 (2) ◽  
pp. 262-293
Author(s):  
Vincent Dekker ◽  
Karsten Schweikert

In this article, we compare three data-driven procedures to determine the bunching window in a Monte Carlo simulation of taxable income. Following the standard approach in the empirical bunching literature, we fit a flexible polynomial model to a simulated income distribution, excluding data in a range around a prespecified kink. First, we propose to implement methods for the estimation of structural breaks to determine a bunching regime around the kink. A second procedure is based on Cook’s distances aiming to identify outlier observations. Finally, we apply the iterative counterfactual procedure proposed by Bosch, Dekker, and Strohmaier which evaluates polynomial counterfactual models for all possible bunching windows. While our simulation results show that all three procedures are fairly accurate, the iterative counterfactual procedure is the preferred method to detect the bunching window when no prior information about the true size of the bunching window is available.


Author(s):  
Gregory Gutin ◽  
Tomohiro Hirano ◽  
Sung-Ha Hwang ◽  
Philip R. Neary ◽  
Alexis Akira Toda

AbstractHow does social distancing affect the reach of an epidemic in social networks? We present Monte Carlo simulation results of a susceptible–infected–removed with social distancing model. The key feature of the model is that individuals are limited in the number of acquaintances that they can interact with, thereby constraining disease transmission to an infectious subnetwork of the original social network. While increased social distancing typically reduces the spread of an infectious disease, the magnitude varies greatly depending on the topology of the network, indicating the need for policies that are network dependent. Our results also reveal the importance of coordinating policies at the ‘global’ level. In particular, the public health benefits from social distancing to a group (e.g. a country) may be completely undone if that group maintains connections with outside groups that are not following suit.


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