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A neural network clustering algorithm for the ATLAS silicon pixel detector
ATLAS collaboration
2014
发表期刊JOURNAL OF INSTRUMENTATION
卷号9
通讯作者Aad, G (reprint author), Aix Marseille Univ, CPPM, Marseille, France.
摘要A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.
学科领域Instruments & Instrumentation
DOI10.1088/1748-0221/9/09/P09009
收录类别SCI
语种英语
WOS类目Instruments & Instrumentation
WOS记录号WOS:000343281300046
引用统计
被引频次:4[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ihep.ac.cn/handle/311005/213794
专题实验物理中心
作者单位中国科学院高能物理研究所
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ATLAS collaboration. A neural network clustering algorithm for the ATLAS silicon pixel detector[J]. JOURNAL OF INSTRUMENTATION,2014,9.
APA ATLAS collaboration.(2014).A neural network clustering algorithm for the ATLAS silicon pixel detector.JOURNAL OF INSTRUMENTATION,9.
MLA ATLAS collaboration."A neural network clustering algorithm for the ATLAS silicon pixel detector".JOURNAL OF INSTRUMENTATION 9(2014).
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