Improved nonlinear optimization in the storage ring of the modern synchrotron radiation light source
文献类型:期刊论文
作者 | Tian, SQ(田顺强) ; Liu, GM(刘桂民) ; Hou, J(后接) ; Chen, GL(陈光玲) ; Chen, SY(陈森玉) |
刊名 | CHINESE PHYSICS C
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出版日期 | 2009 |
卷号 | 33期号:1页码:65 |
ISSN号 | 1674-1137 |
通讯作者 | Tian, SQ (reprint author), Chinese Acad Sci, Shanghai Inst Appl Phys, Shanghai 201800, Peoples R China |
英文摘要 | In the storage ring of the third generation light sources, nonlinear optimization is an indispensable course in order to obtain ample dynamic acceptances and to reach high injection efficiency and long beam lifetime, especially in a low emittance lattice. An improved optimization algorithm based on the single resonance approach, which takes relative weight and initial Harmonic Sextupole Integral Strength (HSIS) as search variables, is discussed in this paper. Applications of the improved method in several test lattices are presented. Detailed analysis of the storage ring of the Shanghai Synchrotron Radiation Facility (SSRF) is particularly emphasized. Furthermore, cancellation of the driving terms is investigated to reveal the physical mechanism of the harmonic sextupole compensation. Sensitivity to the weight and the initial HSIS as well as dependence of the optimum solution on the convergent factor is analyzed. |
学科主题 | Physics |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000262408400014 |
公开日期 | 2012-04-18 |
源URL | [http://ir.sinap.ac.cn/handle/331007/7751] ![]() |
专题 | 上海应用物理研究所_中科院上海应用物理研究所2004-2010年 |
推荐引用方式 GB/T 7714 | Tian, SQ,Liu, GM,Hou, J,et al. Improved nonlinear optimization in the storage ring of the modern synchrotron radiation light source[J]. CHINESE PHYSICS C,2009,33(1):65. |
APA | Tian, SQ,Liu, GM,Hou, J,Chen, GL,&Chen, SY.(2009).Improved nonlinear optimization in the storage ring of the modern synchrotron radiation light source.CHINESE PHYSICS C,33(1),65. |
MLA | Tian, SQ,et al."Improved nonlinear optimization in the storage ring of the modern synchrotron radiation light source".CHINESE PHYSICS C 33.1(2009):65. |
入库方式: OAI收割
来源:上海应用物理研究所
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