A Study of Mixing Event Method in Relativistic Heavy Ion Collision Experiments

FENG Sheng-Qin; LIU Lian-Shou

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《中国物理C》（英文）编辑部

2024年10月30日

Chinese Physics C> 2003, Vol. 27> Issue(4) : 349-353

A Study of Mixing Event Method in Relativistic Heavy Ion Collision Experiments

FENG Sheng-Qin ^, ,
LIU Lian-Shou

Institute of Particle Physics, Huazhong Normal University, Wuhan 430079, China

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Abstract：
A new mixing event method is developed in the analysis of relativistic heavy ion collision experiments with a relatively complicated background by using RQMD (Relativistic Quantum Molecular Dynamics) as input data sample. The proposed method is then applied to the study of invariant mass distribution of Δ⁺⁺ resonance as an example. A new iterative algorithm is also proven by providing the invariant mass spectra of Δ⁺⁺'s using different algorithms for the combinatorial background subtraction.

References

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FENG Sheng-Qin and LIU Lian-Shou. A Study of Mixing Event Method in Relativistic Heavy Ion Collision Experiments[J]. Chinese Physics C, 2003, 27(4): 349-353.

FENG Sheng-Qin and LIU Lian-Shou. A Study of Mixing Event Method in Relativistic Heavy Ion Collision Experiments[J]. Chinese Physics C, 2003, 27(4): 349-353. shu

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Received: 2002-05-27
Revised: 1900-01-01

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沈阳化工大学材料科学与工程学院沈阳 110142

A Study of Mixing Event Method in Relativistic Heavy Ion Collision Experiments

FENG Sheng-Qin ^,
LIU Lian-Shou

Corresponding author: FENG Sheng-Qin,

Institute of Particle Physics, Huazhong Normal University, Wuhan 430079, China

Received Date: 2002-05-27
Accepted Date: 1900-01-01
Available Online: 2003-04-05

Abstract: A new mixing event method is developed in the analysis of relativistic heavy ion collision experiments with a relatively complicated background by using RQMD (Relativistic Quantum Molecular Dynamics) as input data sample. The proposed method is then applied to the study of invariant mass distribution of Δ⁺⁺ resonance as an example. A new iterative algorithm is also proven by providing the invariant mass spectra of Δ⁺⁺'s using different algorithms for the combinatorial background subtraction.