Application of genetic algorithm for optimization design of free electron laser

Baixin ZHANG; Tong ZHANG; Jianhui CHEN; Bo LIU; Dong WANG

doi:10.11889/j.0253-3219.2016.hjs.39.020101

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Application of genetic algorithm for optimization design of free electron laser

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- Application of genetic algorithm for optimization design of free electron laser
  封面论文
- NUCLEAR TECHNIQUES Vol. 39, Issue 2, Article number: 020101(2016)
- 作者机构：
  
  1.中国科学院上海应用物理研究所嘉定园区上海 201800;
  2.中国科学院大学北京 100049
- 作者简介：
- 基金信息：
- DOI：10.11889/j.0253-3219.2016.hjs.39.020101
  CLC： TL506
- Received：01 December 2015，
  
  Accepted：2015-12-30，
  
  Published：25 January 2016
- 稿件说明：
移动端阅览
Baixin ZHANG, Tong ZHANG, Jianhui CHEN, et al. Application of genetic algorithm for optimization design of free electron laser[J]. Nuclear techniques, 2016, 39(2): 020101
DOI：

Baixin ZHANG, Tong ZHANG, Jianhui CHEN, et al. Application of genetic algorithm for optimization design of free electron laser[J]. Nuclear techniques, 2016, 39(2): 020101 DOI： 10.11889/j.0253-3219.2016.hjs.39.020101.

摘要

自由电子激光(Free-Electron Laser

FEL)的辐射功率、光谱等关键量是表征FEL品质的重要因素

这些量往往依赖于多种参量

所以优化这些品质参量的问题即可等效为如何寻求合适的参数来获得更优的FEL的输出。遗传算法是解决这类多变量优化问题常用的算法之一。本文基于遗传算法设计了一个用于FEL优化的应用程序

该应用程序利用实数编码方式

选择合适的算子并作相应的改进

同时利用Java Swing构建了友好的用户界面。实验结果表明

在进行辐射功率优化时

该算法能够在较短的时间内寻找到非常接近全局最优解的较优解。该应用程序具有良好的通用性与可扩展性

在一定程度上为FEL装置的运行优化提供帮助。

Abstract

Background:

Optimization of free-electron laser (FEL) facilities is of great significance to achieve radiations of high-quality

e.g. higher brilliance

purer spectrum. In addition

these properties are affected by various parameters

e.g. the electron trajectory along the accelerator and undulator

the beam envelope or beta function

which could be changed by tuning the correctors and quadrupoles.

Purpose:

This study aims to find a set of suitable parameters to optimize the radiation power.

Methods:

The genetic algorithm (GA) is applied to investigation of the FEL power optimization with respect to the focus-defocus-focus (FODO) lattice configuration between the undulator segmentations. A friendly graphical user interface (GUI) is designed for deployment of the software.

Results:

The preliminary study of the machine optimization shows that it is efficient to find good pair of FODO lattice to get power high enough even if it is not globally optimized.

Conclusion:

This application of genetic algorithm for optimization design of free electron laser is efficient and stable based on many experiments of multi-variable optimization problems

and it is helpful to the future application to the genuine FEL machine optimization.

关键词

Keywords

references

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