Estimation of the proton energy spectrum in knee region by analog read-out ofARGO-YBJ experiment

QU Xiao-Bo; CHEN Song-Zhan; ZHA Min; ZHANG Xue-Yao; FENG Cun-Feng

doi:10.1088/1674-1137/32/10/008

Chinese Physics C> 2008, Vol. 32> Issue(10) : 807-811 DOI: 10.1088/1674-1137/32/10/008

Estimation of the proton energy spectrum in knee region by analog read-out ofARGO-YBJ experiment

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Abstract：
Based on the six months data set of ARGO-YBJ experiment with analog read-out and its Monte Carlo simulation, we study the difference between different primaries induced showers by using the space-time information of the charged particles in Extensive Air Showers. With five parameters which can efficiently pick out primary proton induced showers as inputs of an artificial neural network, the proton spectrum from 100 TeV to 10 PeV can be obtained.

References

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. Haungs A et al. Acta Phys. Polon B, 2004, 35: 331-3392. Horandel J R. Astroparticle Physics, 2004, 21: 241-2653. Amenomori M et al. Physics Letters B, 2006, 632: 58-644. Antoni T et al. Astroparticle Physics, 2005, 24: 1-255. Aielli G et al. Nuclear Physics B, 2007, 166(Proc. Suppl.):96-1026. Heck D et al. Report FZKA 6019, Forschungszentrum Karl-sruhe, 19987. Gaisser T K, Honda M. Ann. Rev. Nucl. Part. Sci., 2002,52: 153-1998. Horandel J R. Astroparticle Physics, 2003, 19: 193-2209. Hocker A et al. E-print arXiv: physics/0703039

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QU Xiao-Bo, CHEN Song-Zhan, ZHA Min, ZHANG Xue-Yao and FENG Cun-Feng. Estimation of the proton energy spectrum in knee region by analog read-out ofARGO-YBJ experiment[J]. Chinese Physics C, 2008, 32(10): 807-811. doi: 10.1088/1674-1137/32/10/008

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Received: 2008-01-18
Revised: 2008-06-16

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沈阳化工大学材料科学与工程学院沈阳 110142

Estimation of the proton energy spectrum in knee region by analog read-out ofARGO-YBJ experiment

Corresponding author: CHEN Song-Zhan,

Received Date: 2008-01-18
Accepted Date: 2008-06-16
Available Online: 2008-10-05

Abstract:

Based on the six months data set of ARGO-YBJ experiment with analog read-out and its Monte Carlo simulation, we study the difference between different primaries induced showers by using the space-time information of the charged particles in Extensive Air Showers. With five parameters which can efficiently pick out primary proton induced showers as inputs of an artificial neural network, the proton spectrum from 100 TeV to 10 PeV can be obtained.