http://arxiv.org/abs/1709.02109
Recently, neural networks have found many applications in different fields including Genetics, Pharmacy, Astrophysics and High Energy Physics [1-3]. In the field of accelerator physics it has been used for control systems [4]. In this paper we present the results based on machine learning techniques motivated to predict the behaviour of ion source in terms of composition of the ion beam while using the Hydrogen gas to produce $H^+$ ions. In the framework of Stellarator type Figure-8 Storage Ring (F8SR) project a volume type ion source was designed for low energy beam transport experiments. In the early stage the functioning of this ion source was studied and the results were published, but only small number of observations were analysed as the main requirement for on going experiments was fulfilled. Though at a later stage, more number of observations were recorded with larger parameter space, to investigate the properties of extracted ion beams from this source further. With recent interests and improved techniques in the applications of machine learning algorithms, we tried to introduce data analysis using neural network to study the ion beams from this plasma ion source.
N. Joshi
Fri, 8 Sep 17
49/65
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