Identification of hadronic tau lepton decays using a deep neural network

doi:10.1088/1748-0221/17/07/P07023

IHEP OpenIR > 实验物理中心

	Identification of hadronic tau lepton decays using a deep neural network
	The CMS collaboration
	2022
发表期刊	Journal of Instrumentation (IF:1.22[JCR-2016],1.297[5-Year])
EISSN	17480221
卷号	17 期号:7 页码:7023
条目编号	IHEP00034872
文章类型	Article
摘要	A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (τ h) that originate from genuine tau leptons in the CMS detector against τ h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a τ h candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine τ h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient τ h reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved τ h reconstruction method are validated with LHC proton-proton collision data at s = 13 TeV. © 2022 CERN.
DOI	10.1088/1748-0221/17/07/P07023
收录类别	ADS
语种	英语
EI主题词	Charged particles - Deep neural networks - Efficiency - Multilayer neural networks
EI分类号	461.4 Ergonomics and Human Factors Engineering - 913.1 Production Engineering
ADS Bibcode	2022JInst..17P7023T
ADS URL	https://ui.adsabs.harvard.edu/abs/2022JInst..17P7023T
ADS引文	https://ui.adsabs.harvard.edu/abs/2022JInst..17P7023T/citations
引用统计	正在获取... 被引频次：18 [ADS]
文献类型	期刊论文
条目标识符	https://ir.ihep.ac.cn/handle/311005/299047
专题	实验物理中心
作者单位	中国科学院高能物理研究所
第一作者单位	中国科学院高能物理研究所
推荐引用方式 GB/T 7714	The CMS collaboration. Identification of hadronic tau lepton decays using a deep neural network[J]. Journal of Instrumentation,2022,17(7):7023.
APA	The CMS collaboration.(2022).Identification of hadronic tau lepton decays using a deep neural network.Journal of Instrumentation,17(7),7023.
MLA	The CMS collaboration."Identification of hadronic tau lepton decays using a deep neural network".Journal of Instrumentation 17.7(2022):7023.