Detecting an axion-like particle with machine learning at the LHC

doi:10.1007/JHEP11(2021)138

CORC > 理论物理研究所 > 中国科学院理论物理研究所 > 理论物理所科研产出 > 理论物理所1978-2010年知识产出

	Detecting an axion-like particle with machine learning at the LHC
	Ren, Jie ; Wang, Daohan 6,7; Wu, Lei 1,2; Yang, Jin Min 6,7; Zhang, Mengchao 3,4
刊名	JOURNAL OF HIGH ENERGY PHYSICS
	2021
期号	11 页码:138
ISSN号	1029-8479
DOI	10.1007/JHEP11(2021)138
英文摘要	Axion-like particles (ALPs) appear in various new physics models with spontaneous global symmetry breaking. When the ALP mass is in the range of MeV to GeV, the cosmology and astrophysics bounds are so far quite weak. In this work, we investi- gate such light ALPs through the ALP-strahlung production processes pp -> W(+/-)a, Za with the sequential decay alpha -> gamma gamma at the 14 TeV LHC with an integrated luminosity of 3000 fb(-1) (HL-LHC). Building on the concept of jet image which uses calorimeter towers as the pixels of the image and measures a jet as an image, we investigate the potential of machine learning techniques based on convolutional neural network (CNN) to identify the highly boosted ALPs which decay to a pair of highly collimated photons. With the CNN tagging algorithm, we demonstrate that our approach can extend current LHC sensitivity and probe the ALP mass range from 0.3 GeV to 5 GeV. The obtained bounds are stronger than the existing limits on the ALP-photon coupling.
学科主题	Physics
语种	英语
内容类型	期刊论文
源URL	[http://ir.itp.ac.cn/handle/311006/27607]
专题	理论物理研究所_理论物理所1978-2010年知识产出
作者单位	1.Univ Chinese Acad Sci, Sch Phys Sci, Beijing 100049, Peoples R China 2.Nanjing Normal Univ, Dept Phys, Nanjing 210023, Peoples R China 3.Nanjing Normal Univ, Inst Theoret Phys, Nanjing 210023, Peoples R China 4.Jinan Univ, Dept Phys, Guangzhou 510632, Peoples R China 5.Jinan Univ, Siyuan Lab, Guangzhou 510632, Peoples R China 6.Beijing Inst Technol, Sch Aerosp Engn, Beijing 100081, Peoples R China 7.Chinese Acad Sci, Inst Theoret Phys, CAS Key Lab Theoret Phys, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Ren, Jie,Wang, Daohan,Wu, Lei,et al. Detecting an axion-like particle with machine learning at the LHC[J]. JOURNAL OF HIGH ENERGY PHYSICS,2021(11):138.
APA	Ren, Jie,Wang, Daohan,Wu, Lei,Yang, Jin Min,&Zhang, Mengchao.(2021).Detecting an axion-like particle with machine learning at the LHC.JOURNAL OF HIGH ENERGY PHYSICS(11),138.
MLA	Ren, Jie,et al."Detecting an axion-like particle with machine learning at the LHC".JOURNAL OF HIGH ENERGY PHYSICS .11(2021):138.