Mixing MC events in reactor neutrino experiment

ZHANG Yi-Chun; CHEN Xiao-Su; HE Miao; HUANG Xing-Tao; WANG Meng; LI Wei-Dong; ZHANG Zi-Ping

doi:10.1088/1674-1137/37/1/016201

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2024年10月30日

Chinese Physics C> 2013, Vol. 37> Issue(1) : 016201 DOI: 10.1088/1674-1137/37/1/016201

Mixing MC events in reactor neutrino experiment

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In reactor neutrino experiments, the analysis of time correlations between different physical events is an important task. Such analysis can help to understand the physical mechanisms of the signal and background events as well as the details of event selection and background estimation. This study investigates a "sampling and mixing" method used for producing large MC data samples for the Daya Bay reactor neutrino experiment. We designed a simple, generic mixing algorithm and generated large MC data samples for physics analysis from several samples according to their respective event rates. Basic plots based on the mixed data are shown.

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ZHANG Yi-Chun, CHEN Xiao-Su, HE Miao, HUANG Xing-Tao, WANG Meng, LI Wei-Dong and ZHANG Zi-Ping. Mixing MC events in reactor neutrino experiment[J]. Chinese Physics C, 2013, 37(1): 016201. doi: 10.1088/1674-1137/37/1/016201

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Received: 2012-03-02
Revised: 2012-04-17

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沈阳化工大学材料科学与工程学院沈阳 110142

Mixing MC events in reactor neutrino experiment

Corresponding author: ZHANG Yi-Chun,

Received Date: 2012-03-02
Accepted Date: 2012-04-17
Available Online: 2013-01-05

Abstract: In reactor neutrino experiments, the analysis of time correlations between different physical events is an important task. Such analysis can help to understand the physical mechanisms of the signal and background events as well as the details of event selection and background estimation. This study investigates a "sampling and mixing" method used for producing large MC data samples for the Daya Bay reactor neutrino experiment. We designed a simple, generic mixing algorithm and generated large MC data samples for physics analysis from several samples according to their respective event rates. Basic plots based on the mixed data are shown.