Photon-hadron discrimination with improved clustering for a preshower detector in high energy heavy ion experiments
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- 作者：Susanta Kumar Pal ; Subhasis Chattopadhyay ; Y.P. Viyogi
- 关键词：Fuzzy c-mean ; Weighted fuzzy c-mean ; Clustering ; Photon multiplicity detector ; Photon&ndash ; hadron discrimination ; Artificial neural network
- 刊名：Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
- 出版年：2012
- 出版时间：21 November, 2012
- 年：2012
- 卷：693
- 期：Complete
- 页码：285-293
- 全文大小：469 K
文摘
The fuzzy c-mean clustering algorithm has been applied to the data set consisting of hits in a highly granular photon multiplicity detector installed in the ALICE experiment at the LHC. The clusters obtained using a modification of the algorithm based on the intensity of cells (called weighted fuzzy c-mean algorithm) are used as input in an artificial neural network formalism for photon-hadron discrimination. Results are discussed in terms of the photon reconstruction efficiency and the purity of photon sample and their centrality and pseudorapidity dependence at the LHC energy.