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    Wyświetlanie 1-2 z 2
    Tytuł:
    Classification of Electron Gun Operation Modes Using Artificial Neural Networks
    Autorzy:
    Isik, N.
    Isik, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1186983.pdf
    Data publikacji:
    2016-04
    Wydawca:
    Polska Akademia Nauk. Instytut Fizyki PAN
    Tematy:
    41.85.Ne
    07.05.Rm
    84.35.+I
    07.05.Mh
    Opis:
    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.
    Źródło:
    Acta Physica Polonica A; 2016, 129, 4; 628-630
    0587-4246
    1898-794X
    Pojawia się w:
    Acta Physica Polonica A
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Time Series Artificial Neural Network Approach for Prediction of Optical Lens Properties
    Autorzy:
    Isik, A.
    Isik, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/1398712.pdf
    Data publikacji:
    2016-04
    Wydawca:
    Polska Akademia Nauk. Instytut Fizyki PAN
    Tematy:
    41.85.Ne
    07.05.Tp
    84.35.+I
    07.05.Mh
    Opis:
    Well-designed electrostatic cylindrical lenses are commonly used to control charged particles in atomic and molecular physics instruments such as electron guns and electron microscopes. The most commonly used of these, three-element electrostatic lenses are capable of keeping magnification constant for definite image position. The correct determination of focal and aberration characteristics of these lenses is very important for experimental studies. In this study, motions of electrons in three-element electrostatic cylindrical lenses have been investigated with nonlinear autoregressive exogenous based time series artificial neural network technique. The spherical and chromatic aberrations which affect the beam are also predicted with time series artificial neural network technique. This method is a mathematical model that emulates the biological neural networks. The basic working principle of time series artificial neural network technique is training of network with the known data and then prediction of the unknown data. Simulation results from SIMION 8.1 ray-tracing program are used as training and test data set. According to the results obtained from time series artificial neural network technique technique, a considerably agreement is found between simulation and artificial neural network technique prediction results. The study shows that such an artificial neural network model which has time advantage can be applicable to various electron and ion beam apparatus.
    Źródło:
    Acta Physica Polonica A; 2016, 129, 4; 514-516
    0587-4246
    1898-794X
    Pojawia się w:
    Acta Physica Polonica A
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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