Monte Carlo generator for full simulation of e(+)e(-)-> hadrons cross section scan experiment
文献类型:期刊论文
作者 | Zhang D(张丹); Rong G(荣刚); Chen JC(陈江川); Zhang, D; Rong, G; Chen, JC |
刊名 | PHYSICAL REVIEW D |
出版日期 | 2006 |
卷号 | 74期号:5页码:54012 |
通讯作者 | Inst High Energy Phys, Beijing 100049, Peoples R China |
英文摘要 | A generator with alpha(2) order radiative correction effects, including both the initial state radiative corrections and the photon vacuum polarization corrections, is built for the full simulation of e(+)e(-)-> hadrons in a cross section scan experiment in the quarkonium energy region. The contributions from the hadron production structures including the resonances of 1(--) quarkonium families and the light hadrons spectrum below 2 GeV as well as the QED continuum hadron spectrum are all taken into account in the event generation. It was employed successfully to determine the detection efficiency for selection of the events of e(+)e(-)-> hadrons from the data taken in the energy region from 3.650 GeV to 3.872 GeV covering both the psi(3686) and psi(3770) resonances in BES experiment. The generator reproduces the properties of hadronic event production and inclusive decays well. |
学科主题 | Astronomy & Astrophysics; Physics |
类目[WOS] | Astronomy & Astrophysics ; Physics, Particles & Fields |
研究领域[WOS] | Astronomy & Astrophysics ; Physics |
原文出处 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000240873900033 |
源URL | [http://ir.ihep.ac.cn/handle/311005/240661] |
专题 | 高能物理研究所_实验物理中心 高能物理研究所_多学科研究中心 |
作者单位 | 中国科学院高能物理研究所 |
推荐引用方式 GB/T 7714 | Zhang D,Rong G,Chen JC,et al. Monte Carlo generator for full simulation of e(+)e(-)-> hadrons cross section scan experiment[J]. PHYSICAL REVIEW D,2006,74(5):54012. |
APA | 张丹,荣刚,陈江川,Zhang, D,Rong, G,&Chen, JC.(2006).Monte Carlo generator for full simulation of e(+)e(-)-> hadrons cross section scan experiment.PHYSICAL REVIEW D,74(5),54012. |
MLA | 张丹,et al."Monte Carlo generator for full simulation of e(+)e(-)-> hadrons cross section scan experiment".PHYSICAL REVIEW D 74.5(2006):54012. |
入库方式: OAI收割
来源:高能物理研究所
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