Low-energy broad beam electron gun

Barefoot, Thomas W.; Ebinger, H. D.; Yates, John T.

doi:10.1116/1.580948

Cited by 8 publications

(1 citation statement)

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“…There is an emerging need for fine-variable electron guns in a number of applications including radar guns, cathode ray tubes, and many experimental designs [1][2][3][4][5][6]. For these purposes, electron guns have been successfully designed and operated with different methods [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Classification of Electron Gun Operation Modes Using Artificial Neural Networks

Isik

Işık

2016

Acta Phys. Pol. A

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In electron collision experiments, the seven-element electron gun is commonly used to accelerate and focus an electron beam. The main operation modes of this experimental device are afocal, zoom and broad beam-modes. Each of these operation modes can be used for producing electron beam with desired diameter. In this study, the artificial neural network classification technique (ANN) is used for classification of electron gun operation modes depending on electrostatic lens voltages. For this purpose, we investigate the focusing condition for the first three-element lens. Other ANN is employed for the second four-element lens voltages to find the electron gun operation modes. A comprehensive training data is obtained from SIMION software which uses traditional ray-tracing method. ANNs are trained with this dataset. Moreover, performance evaluations are carried out to determine the classification power of ANNs. High performance values show that the ANN can easily categorize the operation mode of the electron gun as a function of lens voltages. The proposed approach may help to adjust electron gun voltages before collision experiments. It is believed that this study will be a model for the future research in electron collision systems. Network can be trained with experimental data for practical applications.

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