Optimization of Base Energy Resolution in Hemispherical Deflector Analyzer by using Genetic Algorithm

Abstract

The aim of this study is to demonstrate the Genetic Algorithm (GA) optimization results for energy resolutions of Hemispherical Deflector Analyzer (HDA). The HDAs are designed specifically to distinguish electrons according to their energies. In this context, high energy resolutions are important for the prevention of experimental data loss. In this study, the energy resolution values can be obtained in a short time with the aid of the genetic algorithm implemented in the software. Genetic algorithm (GA) is an effective method developed with artificial intelligence technology. For the first time in this study, analyzer resolution values in the widest range in the literature were calculated by genetic algorithm software. Optimum solutions not only for centric entry HDA but also for paracentric entry Hemispherical Deflector Analyzer (HDA) were obtained by the genetic algorithm.

Keywords

• Artificial intelligence,electron optics,electrostatic energy analyzer,genetic algorithm,optimization

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