现代防御技术2023，Vol.51Issue(6)：155-161,7.DOI:10.3969/j.issn.1009-086x.2023.06.018
基于粒子群算法的量子测量系统最优参数求解
Fast Search of Quantum Measurement System Parameters via Particle Swarm Optimization
杜石桥 1李贵兰 1寇军 1郝赫 1吴同 1秦国卿 1高红卫1
作者信息
- 1. 北京无线电测量研究所,北京 100854
- 折叠
摘要
Abstract
The quantum measurement system based on Rydberg atoms has subversive advantages over traditional measurement methods and is an important development direction in the field of quantum detection.However,quantum measurement systems need to optimize multiple experimental parameters to improve performance.It is usually difficult to use the direct optimization method of full-space parameter scanning in theory and experiment.By building a theoretical model of the quantum measurement system and applying the particle swarm optimization algorithm to the parameter optimization of the model,this paper can quickly solve the global optimal parameters of the system.The computational complexity is reduced by more than one order of magnitude compared with that of the traditional method.In principle,the particle swarm algorithm can be applied to any other quantum measurement system to guide the system to quickly improve performance and promote the practical process.关键词
粒子群算法/量子测量系统/里德堡原子/实验参数/全局搜索Key words
particle swarm optimization(PSO)/quantum measurement system/Rydberg atom/experimental conditions/global search分类
数理科学引用本文复制引用
杜石桥,李贵兰,寇军,郝赫,吴同,秦国卿,高红卫..基于粒子群算法的量子测量系统最优参数求解[J].现代防御技术,2023,51(6):155-161,7.
