A Genetically Based Algorithm to Improve Execution Speed in Multipactor Simulations in Parallel-Plate Waveguides

IEEE TRANSACTIONS ON ELECTRON DEVICES(2024)

引用 0|浏览0
暂无评分
摘要
This article presents an approach to enhance the convergence speed of Monte Carlo simulations for multipactor phenomena in parallel-plate geometries. Multipactor, a self-sustained electron discharge, may cause significantly harmful effects in electronic device operation. An adaptive genetic modification method is introduced to explore the parameter space of electron trajectories efficiently, leading to rapid identification of the critical combinations that induce population growth or decay. The proposed approach involves modifying key parameters, such as the initial phases and kinetic energies of individual particles, based on their performance in multipactor simulations. The reported results demonstrate a substantial improvement in convergence speed, achieving accurate results with fewer tracked particles. The adaptive genetic modification proves to be a promising technique for fast multipactor threshold predictions in parallel-plate configurations and has potential applications when analyzing electron-induced phenomena in a wide range of electronic systems.
更多
查看译文
关键词
Radio frequency,Genetics,Monte Carlo methods,Statistics,Sociology,Discharges (electric),Kinetic energy,Adaptive learning,convergence,genetic algorithm,multipactor,parallel plates
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要