The analysis of electron scattering among multiplying layer in EBAPS using optimized Monte Carlo method

2020 ◽  
Vol 34 (34) ◽  
pp. 2050398
Author(s):  
Jinzhou Bai ◽  
Yonglin Bai ◽  
Xun Hou ◽  
Weiwei Cao ◽  
Yang Yang ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Electron Scattering ◽  
Uv Spectroscopy ◽  
Structural Parameters ◽  
Spectral Response ◽  
Low Noise ◽  
Detection Sensitivity ◽  
Electron Multiplier ◽  
Proposed Model

Electron bombarded Active Pixel Sensor (EBAPS) is well known for its low noise in low-light level imaging, high mechanical integration, and a relatively low cost. It plays an important role in areas of the industrial process as well as the fundamental scientific research. However, the performance of EBAPS is intensively influenced by the structural parameters (i.e. the acceleration voltage between cathode and anode, thickness of the passivation layer, etc.). Due to the influence of these factors mentioned above, the performance of EBAPS is restricted to achieve its best condition. Herein, a model based on the optimized Monte Carlo method was proposed for effectively analyzing the scattering behavior of electrons within the electron multiplier layer. Unlike traditional simulation, which only deals with the electron scattering in longitudinal, in this paper, we simulate the electron scattering character not only in horizontal but also vertical among the multiplier layer, which would react to the influence induced by structural parameters more complete and more precise. Based on the proposed model, an experimental prototype of EBAPS is built and its detection sensitivity achieves [Formula: see text] lux under spectral response of ultraviolet (UV) spectroscopy, which improved a lot from our former design. The proposed model can be used for analyzing the influence induced by structural parameters, which exhibit enormous potential for exploring the high-gain EBAPS.

Simulation of Thermal Cooling Curves in the Process to Ordering Alloys by the Monte Carlo Method

2021 ◽  
Vol 410 ◽  
pp. 227-234
Author(s):  
Albert R. Khalikov ◽  
Sergey V. Dmitriev
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Stoichiometric Composition ◽  
Square Lattice ◽  
Cooling Curves ◽  
Ordering Kinetics ◽  
The Monte Carlo Method ◽  
Proposed Model ◽  
Coordination Spheres ◽  
Thermal Cooling

An algorithm is proposed for constructing curves of thermal cooling and ordering kinetics with a monotonic decrease in temperature for alloys to stoichiometric composition. Modeling is carried out by the Monte Carlo method in the model of a rigid crystal lattice and pair interatomic interactions. The application of the algorithm is illustrated by the example to a square lattice, taking into account interatomic interactions in the first two coordination spheres for alloys with the composition AB, A3B, and A3B5. The proposed model makes it possible to calculate individual sections of the phase diagrams to the state for binary alloys.

scholarly journals Using Monte Carlo method to estimate the behavior of neural training between balanced and unbalanced data in classification of patterns

2018 ◽  
Vol 7 (2) ◽  
pp. 1
Author(s):  
Paulo Marcelo Tasinaffo ◽  
Gildárcio Sousa Gonçalves ◽  
Adilson Marques da Cunha ◽  
Luiz Alberto Vieira Dias
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Mean Squared Error ◽  
Classification Problem ◽  
Computational Environment ◽  
The Monte Carlo Method ◽  
Proposed Model ◽  
Artificial Neural

This paper proposes to develop a model-based Monte Carlo method for computationally determining the best mean squared error of training for an artificial neural network with feedforward architecture. It is applied for a particular non-linear classification problem of input/output patterns in a computational environment with abundant data. The Monte Carlo method allows computationally checking that balanced data are much better than non-balanced ones for an artificial neural network to learn by means of supervised learning. The major contribution of this investigation is that, the proposed model can be tested by analogy, considering also the fraud detection problem in credit cards, where the amount of training patterns used are high.

Application of the monte carlo method to high energy electron scattering (0.3-1.5 MeV)

1978 ◽  
Vol 36 (1) ◽  
pp. 202-203
Author(s):  
G. Soum ◽  
F. Arnal ◽  
J.L. Balladore ◽  
B. Jouffrey ◽  
P. Verdier
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Transmission Coefficient ◽  
Electron Scattering ◽  
High Energy ◽  
Angular Aperture ◽  
Method Of Calculation ◽  
Total Transmission ◽  
The Monte Carlo Method

Techniques for using the Monte-Carlo method for studying electron scattering in solids have been developed by several authors (1). The method is used to determine the angular distribution of electrons emerging from amorphous or polycrystalline specimens ; the total transmission and backscattering coefficients can also be obtained.- Method of calculation -Let Iθ be the intensity scattered in the direction making an angle θ with the incident electrons ; thus Iθ represents the number of electrons scattered in this direction within a solid angle Δw = πα2, where α is the semi-angle of the collector as seen from the specimen. For a specimen of thickness x, the angular distribution function may be written:I∘ denotes the intensity of the incident monoenergetic electron beam, Tα the transmission coefficient along the direction of incidence for a semi-angular aperture α and TθN the normalized transmission coefficient in the direction θ

Quantum-trajectory Monte Carlo method for study of electron–crystal interaction in STEM

2015 ◽  
Vol 17 (27) ◽  
pp. 17628-17637 ◽  
Author(s):  
Z. Ruan ◽  
R. G. Zeng ◽  
Y. Ming ◽  
M. Zhang ◽  
B. Da ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Electron Scattering ◽  
Secondary Electron ◽  
Quantum Trajectory ◽  
Cascade Process ◽  
Electron Cascade ◽  
Electron Crystal

A quantum trajectory Monte Carlo method is developed to simulate electron scattering and secondary electron cascade process in crystalline specimen.

Simulation of electron scattering in thin films using Monte-Carlo method in discrete looses approximation

2006 ◽  
Author(s):  
S. S. Borisov ◽  
S. I. Zaitsev ◽  
E. A. Grachev ◽  
N. Ivanov
Keyword(s):  
Thin Films ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Electron Scattering

scholarly journals USING MODEL-INDEPENDENT LOWER BOUNDS TO IMPROVE PRICING OF ASIAN STYLE OPTIONS IN LÉVY MARKETS

2014 ◽  
Vol 44 (2) ◽  
pp. 237-276 ◽  
Author(s):  
Griselda Deelstra ◽  
Grégory Rayée ◽  
Steven Vanduffel ◽  
Jing Yao
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Lower Bounds ◽  
Mathematical Finance ◽  
Asian Option ◽  
Asian Options ◽  
Option Prices ◽  
Control Variates ◽  
Proposed Model ◽  
Model Independent

AbstractAlbrecheret al. (Albrecher, H., Mayer Ph., Schoutens, W. (2008) General lower bounds for arithmetic Asian option prices.Applied Mathematical Finance,15, 123–149) have proposed model-independent lower bounds for arithmetic Asian options. In this paper we provide an alternative and more elementary derivation of their results. We use the bounds as control variates to develop a simple Monte Carlo method for pricing contracts with Asian-style features. The conditioning idea that is inherent in our approach also inspires us to propose a new semi-analytic pricing approach. We compare both approaches and conclude that these both have their merits and are useful in practice. In particular, we point out that our newly proposed Monte Carlo method allows to deal with Asian-style products that appear in insurance (e.g., unit-linked contracts) in a very efficient way, and outperforms other known Monte Carlo methods that are based on control variates.

scholarly journals Parameter identification for structural health monitoring based on Monte Carlo method and likelihood estimate

2018 ◽  
Vol 14 (7) ◽  
pp. 155014771878688 ◽  
Author(s):  
Songtao Xue ◽  
Bo Wen ◽  
Rui Huang ◽  
Liyuan Huang ◽  
Tadanobu Sato ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Structural Health Monitoring ◽  
Parameter Identification ◽  
Health Monitoring ◽  
Gaussian Noise ◽  
Damage Identification ◽  
Structural Parameters ◽  
Likelihood Estimate ◽  
Structural Health

Structural parameters are the most important factors reflecting structural performance and conditions. As a result, their identification becomes the most essential aspect of the structural assessment and damage identification for the structural health monitoring. In this article, a structural parameter identification method based on Monte Carlo method and likelihood estimate is proposed. With which, parameters such as stiffness and damping are identified and studied. Identification effects subjected to three different conditions with no noise, with Gaussian noise, and with non-Gaussian noise are studied and compared. Considering the existence of damage, damage identification is also realized by the identification of the structural parameters. Both simulations and experiments are conducted to verify the proposed method. Results show that structural parameters, as well as the damages, can be well identified. Moreover, the proposed method is much robust to the noises. The proposed method may be prospective for the application of real structural health monitoring.

STUDY OF THE STATIC CHARACTERISTICS OF THE WORKSPACE AR600E ROBOT

2020 ◽  
Vol 5 (4) ◽  
pp. 6-12
Author(s):  
Evgeniy Shakhmatov ◽  
Vladimir Ilyukhin ◽  
Dmitry Mezentsev
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Structural Parameters ◽  
Kinematic Model ◽  
Basic Structure ◽  
Planning And Control ◽  
Working Space ◽  
The Monte Carlo Method ◽  
And Control ◽  
Kinematic Solution

The workspace is one of the most important parameters for evaluating robot flexibility and is important for optimizing robotic configuration, motion planning and control. Firstly, a kinematic model of the manipulator based on its basic structure was put forward. The systems of connection coordinates are established and the direct kinematic solution derived using DH methods. On its basis, the working space of the manipulator analyzed by the Monte Carlo method, based on random probability and software simulation MATLAB for the structural parameters of the robot. A cloud of workspace points has been compiled. Considering the problem of insufficient accuracy of the traditional Monte Carlo method in calculating the working space of the robot, an improved Monte Carlo method using the Beta distribution proposed. 

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