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arXiv · 1611.01721

Longitudinal RF capture simulation and BPM signal estimation

Yong-Chun Feng·Rui-Shi Mao·Yu-Cong Chen·Yan Yin·Xiao-Hu Zhang·Shuang Ruan·Tong Liu·Yao-Yao You·Xin-Cai Kang·Tie-Cheng Zhao·Zhi-Guo Xu·Peng Li·Yan-Yu Wang·You-Jin Yuan
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Abstract

In this paper, the theoretical aspects behind longitudinal RF capture are reviewed and the capture process is simulated via a program based on this theory. Four kinds of cases with different initial distribution and capture curve are considered, i.e. uniform distribution with adiabatic capture, uniform distribution with non-adiabatic capture, Gaussian distribution with adiabatic capture and Gaussian distribution with non-adiabatic capture. The simulation results are compared each other and discussed, and Gaussian distribution with adiabatic capture is demonstrated having a higher capture efficiency and leading to a shorter bunch length. In addition, the BPM induced signal is simulated with high input impendence, i.e. $1M\Omega$, and low input impendence, i.e. $50\Omega$, respectively. Finally, the BPM signal of Heavy Ion Medical Machine (HIMM) is estimated and compared with measured one, and a good agreement is achieved.

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Yong-Chun Feng, Rui-Shi Mao, Yu-Cong Chen, Yan Yin, Xiao-Hu Zhang, Shuang Ruan, Tong Liu, Yao-Yao You, Xin-Cai Kang, Tie-Cheng Zhao, Zhi-Guo Xu, Peng Li, Yan-Yu Wang, You-Jin Yuan. 2016-11-06. Longitudinal RF capture simulation and BPM signal estimation. https://arxiv.org/abs/1611.01721

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