[Table of Contents]

Plasma and Fusion Research

Volume 10, 3406049 (2015)

Regular Articles

Determination of Resonant State Parameters from Ab Initio Data by Artificial Neural Network and Statistical Pade Approximation
Lukáš PICHL and Jiří HORÁČEK1)
International Christian University, 3-10-2 Osawa, Mitaka, Tokyo 181-8585, Japan
1)
Institute of Theoretical Physics, Charles University Prague, V Holešovičkách 2, 180 00 Praha 8, Czech Republic
(Received 27 October 2014 / Accepted 8 March 2015 / Published 26 May 2015)

Abstract

Resonant states in electron molecule collisions mediate a variety of energy transfer processes in the plasma edge region, such as vibrational excitation, dissociative recombination, dissociative attachment, associative detachment etc. Here we show that the resonance parameters, in general difficult to obtain, can be computed from standard bound-state ab initio data by means of analytical continuation in the coupling constant. The procedure uses artificial neural network and statistical Pade approximation to extrapolate from the bound-state region to that of the resonant state by varying the strength of the attractive potential term added. We present benchmark data for the ethylene molecule and demonstrate a reasonable stability of the results over the quantum chemical basis sets employed.

Keywords

fusion edge plasma, electron-molecule collision, resonance energy, resonance width, artificial neural network, statistical Pade approximation

DOI: 10.1585/pfr.10.3406049

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This paper may be cited as follows:

Lukáš PICHL and Jiří HORÁČEK, Plasma Fusion Res. 10, 3406049 (2015).