高亮度电子束相空间重建技术的实验研究

束团相空间是描述加速器中束流运行状态的重要参数，了解相空间的真实分布对于加速器设计、束团操纵具有非常重要的意义，利用相空间重建技术能够直观地得到束团二维相空间分布。本文结合计算机断层扫描技术（Computer Tomography,CT）与归一化相空间理论，在理论推导和模拟验证的基础上，分别利用MENT（Maximum Entropy）算法和FBP（Filtered Back Projection）算法在上海x射线自由电子激光装置（ShanghaiSoft X-ray Free Electron Laser facility,SXFEL）专用束测段（B11）对电子束团的横向归一化相空间进行重建...

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Bibliographic Details
Published in核技术 Vol. 41; no. 3; pp. 13 - 19
Main Author 于清林;张猛;谷端;赵明华
Format Journal Article
LanguageChinese
Published 中国科学院上海应用物理研究所 嘉定园区 上海 201800 10.03.2018
中国科学院大学 北京 100049%中国科学院上海应用物理研究所 嘉定园区 上海 201800
Subjects
归一化相空间;相空间重建;MENT算法;上海X射线自由电子激光装置
上海X射线自由电子激光装置
Normalized phase space
相空间重建
SXFEL
Phase space reconstruction
归一化相空间
MENT算法
MENT algorithm
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ISSN0253-3219
DOI10.11889/j.0253-3219.2018.hjs.41.030103

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Summary:束团相空间是描述加速器中束流运行状态的重要参数，了解相空间的真实分布对于加速器设计、束团操纵具有非常重要的意义，利用相空间重建技术能够直观地得到束团二维相空间分布。本文结合计算机断层扫描技术（Computer Tomography,CT）与归一化相空间理论，在理论推导和模拟验证的基础上，分别利用MENT（Maximum Entropy）算法和FBP（Filtered Back Projection）算法在上海x射线自由电子激光装置（ShanghaiSoft X-ray Free Electron Laser facility,SXFEL）专用束测段（B11）对电子束团的横向归一化相空间进行重建。通过重建算法变换得到电子束团的真实相空间分布，并对重建结果进行对比和误差分析。实验结果表明，MENT算法能够精确测量电子束团横向相空间分布。
Bibliography:YU Qinglin1,2 ZHANG Meng1, GU Duan1, ZHAO Minghua1 （1.Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Jiading Campus, Shanghai 201800, China;2.University of Chinese Academy of Sciences, Beijing 100049, China）
Deep penetration;Variance reduction;Monte Carlo;Electron irradiation accelerator
[Background] Variance reduction is a common method to resolve the problems in deep penetration application such as radiation shielding, medical physics and well-logging. Currently, the study of the variance reduction techniques is based on simple theoretical geometric model, lacking the discussion on complex practical applications. [Purpose] This paper aims to find an optimized combined variance reduction technique in deep penetration application on the practical complex model. [Methods] With an electron irradiation accelerator as the model, this paper studied the effects of combined variance reduction techniques on MCNP5（Monte Carlo N Particle Transport Code） platform, including geometry splitting, biasing
ISSN:0253-3219
DOI:10.11889/j.0253-3219.2018.hjs.41.030103