The Investigation of Electron-Optical Parameters Using Artificial Neural Networks

The optimization of scientific instruments is crucially important to increase the quality of measurements. A major challenge for the development of these experimental tools is the precise determination of focal parameters. Therefore, usage of an innovative technique that meets our requirements is desirable. Among intelligent algorithms, artificial neural network (ANN) has an advantage of obtaining the optical parameters data with high accuracy. One of the most popular geometries used in electrostatic optical devices is geometry with cylinder lenses. In this study, the artificial neural network is applied for the first time to the subject of the magnification parameters of three-element electrostatic cylinder lenses for a wide range of values of the applied voltages. ANN-based optimization has been performed using Matlab/Simulink, and the performance analysis has also been conducted. High-performance results have been achieved using ANN approach. The commercial simulation package SIMION software is used as a data source for artificial neural network results. This approach provides new perspectives for the effective solution for the problems related to electrostatic lenses with different geometries.