Chinese Physics C > 2005, Vol. 29 > Issue(5): 485-490

Identification of Primary γ-Rays in ARGO Experiment at Yangbajing Using ANNS

School of Physics and Microelectronics Shandong University, Ji’nan 250100,China

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Abstract：
The lateral distributions, as measured by ARGO array, of the extensive air showers induced by γ and hadrons with energy range from 100GeV to 10 TeV, zenith angle from 0° to 45°, were studied using Monte Carlo generated data. Several parameters such as average lateral distribution, minimum tree length and so on, which could be used to the difference of the lateral distributions between the showers induced by γ and hadrons were obtained. These parameters were used as the input for an artificial neural network, which was then trained to study the γ/hadron discrimination power. The result indicated that using this method could effectively separate the showers induced by γ-rays and hadrons.

References

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MA Li-Na, FENG Cun-Feng, ZHANG Yao and ZHANG Xue-Rao. Identification of Primary γ-Rays in ARGO Experiment at Yangbajing Using ANNS[J]. Chinese Physics C, 2005, 29(5): 485-490.

MA Li-Na, FENG Cun-Feng, ZHANG Yao and ZHANG Xue-Rao. Identification of Primary γ-Rays in ARGO Experiment at Yangbajing Using ANNS[J]. Chinese Physics C, 2005, 29(5): 485-490. shu

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Received: 2004-09-08
Revised: 1900-01-01

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通讯作者:陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

Identification of Primary γ-Rays in ARGO Experiment at Yangbajing Using ANNS

Corresponding author:MA Li-Na,

School of Physics and Microelectronics Shandong University, Ji’nan 250100,China

Received Date:2004-09-08

Accepted Date:1900-01-01

Available Online:2005-05-05

Abstract:The lateral distributions, as measured by ARGO array, of the extensive air showers induced by γ and hadrons with energy range from 100GeV to 10 TeV, zenith angle from 0° to 45°, were studied using Monte Carlo generated data. Several parameters such as average lateral distribution, minimum tree length and so on, which could be used to the difference of the lateral distributions between the showers induced by γ and hadrons were obtained. These parameters were used as the input for an artificial neural network, which was then trained to study the γ/hadron discrimination power. The result indicated that using this method could effectively separate the showers induced by γ-rays and hadrons.

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Identification of Primary γ-Rays in ARGO Experiment at Yangbajing Using ANNS

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