Calculation of Optimum Transit Times with Real-Coded Genetic Algorithm
Abstract
Electron energy analysers have been designed to analyse charged-particle beams at specific energies. The design is based on the principle that electrons with different energies arrive at the detector at different times. Since electrons with different energies follow different orbits within these analysers. In collision experiments, it is very important to determine the trajectories and transit times of the charged particles in the analyser. In this study, optimum solutions for transit times of charged particles were provided using a real-coded genetic algorithm. Hyper parameters and types of genetic algorithm were obtained using trial and error methods, in this study. The results of this study indicate that genetic algorithm gives time resolution values in a wide data set with high accuracy. The results show that genetic algorithms (GA) are a fascinating approach for solving search and optimization problems.
Keywords
Electron spectroscopy , electron beam , energy analyser , genetic algorithm.
References
- Baguenard B., Wills J. B., Pagliarulo F., Lépine F., Climen B., Barbaire M., Clavier C., Lebeault M. A., Bordas C., (2004). Velocity-map imaging electron spectrometer with time resolution, Rev Sci Instrum 75, 324–328.
- Caprari, R. S., (1995). Exit position and transit-time analysis of hemispherical electrostatic analysers, Measurement Science & Technology, 6(7), 1063–1064.
- Davis, L., (1991). Handbook of genetic algorithms,
- Dogan, M., Sise O., Ulu M., (2007). Design of electron energy analyzers for electron impact studies, Radiation Physics and Chemistry 76 445-449.
- Goldberg, D.E., (1989). Genetic algorithms in search optimization and machine learning. Addison Wesley, Reading Menlo Park.
- Goldberg, D.E., Holland, J.H. (1988). Genetic algorithms and machine learning. Machine learning; 3: 95-99.
- Heddle, D.W.O., (2000). Electrostatic Lens Systems, IOP Press, London,
- Imhof, R. E., Adams A., King G. C., (1976) Energy and time resolution of the 180 degrees hemispherical electrostatic analyser, Journal of Physics E 9 138.
- Ince, M., Isik, N., (2020) Optimization of Base Energy Resolution in Hemispherical Deflector Analyzer by using Genetic Algorithm, Celal Bayar University Journal of Science 16 345-349.
- Isik N., (2016). Determination of Electron Optical Properties for Aperture Zoom Lenses Using an Artificial Neural Network Method, Microscopy and Microanalysis 22 458-462.
