{"title":"Calculation of Optimum Transit Times with Real-Coded Genetic Algorithm","authors":"Nimet IŞIK","doi":"10.31466/kfbd.1249873","DOIUrl":null,"url":null,"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.","PeriodicalId":17795,"journal":{"name":"Karadeniz Fen Bilimleri Dergisi","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Karadeniz Fen Bilimleri Dergisi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31466/kfbd.1249873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.