Study on the efficiency of the underground muon detectors in YangBaJing Hybrid Array
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Abstract
PurposeThe \gamma -ray astronomy at 100 TeV is important to unravel the puzzles related to the origin and acceleration of the Galactic cosmic rays up to PeV energy. The YangBaJing Hybrid Array (YBJ-HA), about 2% the scale of LHAASO-KM2A, is such a kind of detection instrument capable of detecting 100 TeV \gamma -rays. And the muon detection efficiency stability of the MD array in YBJ-HA is crucial for high quality \gamma -ray observation. To measure and monitor the muon detection efficiency, we develop a method in this work.
MethodsWe develop a muon bundle method to measure and monitor the efficiency of each muon detector. In this method, muon detection efficiency of the target MD unit is calculated based on the surrounding MD units and the MC simulation.
ResultsThe average actual muon detection efficiency of the 16 MD units is up to 83.4% during 4 years’ observation.
ConclusionsThe muon detection efficiency of each MD unit is found to be stable during 4 years’ operation. In the future, a similar method may be applicable to the muon detection efficiency study for LHAASO.
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Zhen Wang, Youliang Feng, Cheng Liu, et al. Study on the efficiency of the underground muon detectors in YangBaJing Hybrid Array[J]. Radiation Detection Technology and Methods, 2019, 3(3): 29-29. DOI: 10.1007/s41605-019-0107-1
Citation:
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Zhen Wang, Youliang Feng, Cheng Liu, et al. Study on the efficiency of the underground muon detectors in YangBaJing Hybrid Array[J]. Radiation Detection Technology and Methods, 2019, 3(3): 29-29. DOI: 10.1007/s41605-019-0107-1
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Zhen Wang, Youliang Feng, Cheng Liu, et al. Study on the efficiency of the underground muon detectors in YangBaJing Hybrid Array[J]. Radiation Detection Technology and Methods, 2019, 3(3): 29-29. DOI: 10.1007/s41605-019-0107-1
Citation:
|
Zhen Wang, Youliang Feng, Cheng Liu, et al. Study on the efficiency of the underground muon detectors in YangBaJing Hybrid Array[J]. Radiation Detection Technology and Methods, 2019, 3(3): 29-29. DOI: 10.1007/s41605-019-0107-1
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