Volume 5 Number 3 (Jul. 2015)
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IJAPM 2015 Vol.5(3): 218-226 ISSN: 2010-362X
doi: 10.17706/ijapm.2015.5.3.218-226

Fast Monte Carlo Method in Stochastic Modelling of Charged Particle Multiplication

Alla V. Shymanska, Vitali A. Babakov
Abstract—Development of electronic devices, where the secondary electron emission is used to amplify input signals, requires simulation of complicated stochastic processes. The essence of the method proposed here consists of separating the amplification process into serial and parallel stages. The mean and variance of the amplitude distribution at the output of the entire system are obtained using the mean and variance of each stage. Theorems about serial amplification stages and parallel amplification paths constitute the key part of the method with partial Monte Carlo simulation for one simple stage. Here, the method is used to investigate the effect of the contact conducting layer on the gain and the noise factor of the channel amplifier. The case of image converters and intensifiers with an inverting electron-optical system and microchannel plate as an amplifier is taken for the consideration.

Index Terms—Contact conducting layer, microchannel electron amplifier, Monte Carlo simulations, noise factor, theorems about serial, parallel amplification stages.

The authors are with School of Computer and Mathematical Sciences, Auckland University of Technology, Private Bag 92006, Auckland 1142, New Zealand (email: alla.shymanska@aut.ac.nz).

Cite: Alla V. Shymanska, Vitali A. Babakov, "Fast Monte Carlo Method in Stochastic Modelling of Charged Particle Multiplication," International Journal of Applied Physics and Mathematics vol. 5, no. 3, pp. 218-226, 2015.

General Information

ISSN: 2010-362X
Frequency: Bimonthly (2011-2014); Quarterly (Since 2015)
DOI: 10.17706/IJAPM
Editor-in-Chief: Prof. Haydar Akca
Abstracting/ Indexing: Index Copernicus, EI (INSPEC, IET), Chemical Abstracts Services (CAS), Electronic Journals Library, Nanowerk Database, Google Scholar and ProQuest
E-mail: ijapm@iap.org
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