Chinese Physics C > 1999, Vol. 23 > Issue(10): 998-1003

An Algorithm for Increasing the Ratio of QGP Candidate Events in Relativistie Heavy Ion Collision Data Sample Using Factorial Moment Technique

Institute of Particle Physics, Huazhong Normal University, Wuhan 430079

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Abstract：
The formation of quark-gluon plasma (QGP) in relativistic heavy ion collision, is expected to be accompanied by a background of ordinary collision events without phase transition. In this short note an algorithm is proposed to select the QGP candidate events from the whole event sample. This algorithm is based on a simple geometrical consideration together with some ordinary QGP signal, e.g. the increasing of K/π ratio. This algorithm increases the "signal to noise ratio" of QGP events in the selected sub-sample in shown explicitly by using Monte-Carlo simulation.

References

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Cheng Qinghua, Hu Yuan and Liu Lianshou. An Algorithm for Increasing the Ratio of QGP Candidate Events in Relativistie Heavy Ion Collision Data Sample Using Factorial Moment Technique[J]. Chinese Physics C, 1999, 23(10): 998-1003.

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Received: 1998-07-28
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

An Algorithm for Increasing the Ratio of QGP Candidate Events in Relativistie Heavy Ion Collision Data Sample Using Factorial Moment Technique

Corresponding author:Cheng Qinghua,

Institute of Particle Physics, Huazhong Normal University, Wuhan 430079

Received Date:1998-07-28
Accepted Date:1900-01-01
Available Online:1999-10-05

Abstract:The formation of quark-gluon plasma (QGP) in relativistic heavy ion collision, is expected to be accompanied by a background of ordinary collision events without phase transition. In this short note an algorithm is proposed to select the QGP candidate events from the whole event sample. This algorithm is based on a simple geometrical consideration together with some ordinary QGP signal, e.g. the increasing of K/π ratio. This algorithm increases the "signal to noise ratio" of QGP events in the selected sub-sample in shown explicitly by using Monte-Carlo simulation.