Higher-order sampling strategies in Monte Carlo simulations of electron energy distribution functions in plasmas
- 15 April 1994
- journal article
- Published by AIP Publishing in Journal of Applied Physics
- Vol. 75 (8) , 3785-3788
- https://doi.org/10.1063/1.356053
Abstract
A new method of gathering statistics for Monte Carlo methods, Legendre polynomial weighted sampling (LPWS), is presented. LPWS requires only a minimum of particles to extract higher-order derivative information about a particle’s distribution function. In this technique, when calculating a particle’s distribution function, higher-order derivative information about the Monte Carlo particles is recorded along with just counting the number of particles in a bin. The distribution function is then constructed from this information. Specifically, in this paper, second-order Legendre polynomial weighted sampling is employed. Legendre polynomial weighted sampling is demonstrated by calculating the electron energy distribution functions in an inductively coupled plasma reactor.This publication has 3 references indexed in Scilit:
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