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A 3D Likelihood Analysis Tool for LHAASO-KM2A data
Cao, Zhen1,2,3; Aharonian, F.4,5; An, Q.6,7; Axikegu8; Bai, L. X.9; Bai, Y. X.1,3; Bao, Y. W.10; Bastieri, D.11; Bi, X. J.1,2,3; Bi, Y. J.1,3; Cai, H.12; Cai, J. T.11; Cao, Zhe6,7; Chang, J.13; Chang, J. F.1,3,6; Chen, B. M.14; Chen, E. S.1,2,3; Chen, J.9; Chen, Liang15; Chen, Long8; Chen, M. J.1,3; Chen, M. L.1,3,6; Chen, Q. H.8; Chen, S. H.1,2,3; Chen, S. Z.1,3; Chen, T. L.16; Chen, X. L.1,2,3; Chen, Y.10; Cheng, N.1,3; Cheng, Y. D.1,3; Cui, S. W.14; Cui, X. H.17; Cui, Y. D.18; D'Ettorre Piazzoli, B.19; Dai, B. Z.20; Dai, H. L.1,3,6; Dai, Z. G.7; Danzengluobu16; della Volpe, D.21; Dong, X. J.1,3; Duan, Kaikai13; Fan, J. H.11; Fan, Y. Z.13; Fan, Z. X.1,3; Fang, J.20; Fang, K.1,3; Feng, C. F.22; Feng, L.13; Feng, S. H.1,3; Feng, Y. L.13; Gao, B.1,3; Gao, C. D.22; Gao, L. Q.1,2,3; Gao, Q.16; Gao, W.22; Ge, M. M.20; Geng, L. S.1,3; Gong, G. H.23; Gou, Q. B.1,3; Gu, M. H.1,3,6; Guo, F. L.15; Guo, J. G.1,2,3; Guo, X. L.8; Guo, Y. Q.1,3; Guo, Y. Y.1,2,3,13; Han, Y. A.24; He, H. H.1,2,3; He, H. N.13; He, J. C.1,2,3; He, S. L.11; He, X. B.18; He, Y.8; Heller, M.21; Hor, Y. K.18; Hou, C.1,3; Hou X(侯贤)25; Hu, H. B.1,2,3; Hu, S.9; Hu, S. C.1,2,3; Hu, X. J.23; Huang, D. H.8; Huang, Q. L.1,3; Huang, W. H.22; Huang, X. T.22; Huang, Xiaoyuan13; Huang, Z. C.8; Ji, F.1,3; Ji, X. L.1,3,6; Jia, H. Y.8; Jiang, K.6,7; Jiang, Z. J.20; Jin, C.1,2,3; Ke, T.1,3; Kuleshov, D.26; Levochkin, K.26; Li, B. B.14; Li, Cheng6,7; Li, Cong1,3; Li, F.1,3,6; Li, H. B.1,3; Li, H. C.1,3; Li, H. Y.7,13; Li, Jian7; Li, Jie1,3,6; Li, K.1,3; Li, W. L.22; Li, X. R.1,3; Li, Xin8; Li, Y.9; Li, Y. Z.1,2,3; Li, Zhe1,3; Li, Zhuo27; Liang, E. W.28; Liang, Y. F.28; Lin, S. J.18; Liu, B.7; Liu, C.1,3; Liu, D.22; Liu, H.8; Liu, H. D.24; Liu, J.1,3; Liu, J. L.29; Liu, J. S.18; Liu, J. Y.1,3; Liu, M. Y.16; Liu, R. Y.10; Liu, S. M.8; Liu, W.1,3; Liu, Y.11; Liu, Y. N.23; Liu, Z. X.9; Long, W. J.8; Lu, R.20; Lv, H. K.1,3; Ma, B. Q.27; Ma, L. L.1,3; Ma, X. H.1,3; Mao JR(毛基荣)25; Masood, A.8; Min, Z.1,3; Mitthumsiri, W.30; Montaruli, T.21; Nan, Y. C.22; Pang, B. Y.8; Pattarakijwanich, P.30; Pei, Z. Y.11; Qi, M. Y.1,3; Qi, Y. Q.14; Qiao, B. Q.1,3; Qin, J. J.7; Ruffolo, D.30; Rulev, V.26; Sáiz, A.30; Shao, L.14; Shchegolev, O.26,31; Sheng, X. D.1,3; Shi, J. R.1,3; Song, H. C.27; Stenkin, Yu. V.26,31; Stepanov, V.26; Su, Y.13; Sun, Q. N.8; Sun, X. N.28; Sun, Z. B.32; Tam, P. H.18; Tang, Z. B.6,7; Tian, W. W.2,17; Wang, B. D.1,3; Wang, C.32; Wang, H.8; Wang, H. G.11; Wang JC(王建成)25
Source PublicationProceedings of Science
Contribution Rank第25完成单位
Indexed ByEI
Conference Name37th International Cosmic Ray Conference, ICRC 2021
Conference Date2021-07-12
Conference PlaceVirtual, Berlin, Germany

The square kilometer array (KM2A) is the main array of the Large High Altitude Air Shower Observatory (LHAASO), which is the most sensitive gamma-ray detector for energies above a few tens of TeV. We are developing a software pipeline based on the experimental data, Monte-Carlo simulations and the pointing track of the arrays. The pipeline is able to perform 3D (sky images at different energies) fits of KM2A data, similar to those used for Fermi-LAT and DAMPE gamma-ray analysis. This 3D likelihood analysis could fit source models of arbitrary morphology to the sky images, and get energy spectra information and detection significances simultaneously. The analysis with this software could give consistent results with those using traditional method. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

Funding ProjectN/A
Funding OrganizationN/A
Subject Area天文学 ; 天体物理学 ; 高能天体物理学 ; 天文学其他学科
MOST Discipline Catalogue理学 ; 理学::天文学
SubtypeConference article (CA)
PublisherSissa Medialab Srl
EI Accession Number20225213316495
EI KeywordsPipelines
EI Classification Number619.1 Pipe, Piping and Pipelines - 657 Space Physics - 657.2 Extraterrestrial Physics and Stellar Phenomena - 723.4 Artificial Intelligence - 922.2 Mathematical Statistics - 931.3 Atomic and Molecular Physics - 932.1 High Energy Physics
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Document Type会议论文
Affiliation1.Key Laboratory of Particle Astrophyics, Experimental Physics Division, Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, 100049, China;
2.University of Chinese Academy of Sciences, Beijing, 100049, China;
3.TIANFU Cosmic Ray Research Center, Sichuan, Chengdu, China;
4.Dublin Institute for Advanced Studies, 31 Fitzwilliam Place, 2 Dublin, Ireland;
5.Max-Planck-Institut for Nuclear Physics, P.O. Box 103980, Heidelberg, 69029, Germany;
6.State Key Laboratory of Particle Detection and Electronics, China;
7.University of Science and Technology of China, Anhui, Hefei, 230026, China;
8.School of Physical Science and Technology, School of Information Science and Technology, Southwest Jiaotong University, Sichuan, Chengdu, 610031, China;
9.College of Physics, Sichuan University, Sichuan, Chengdu, 610065, China;
10.School of Astronomy and Space Science, Nanjing University, Jiangsu, Nanjing, 210023, China;
11.Center for Astrophysics, Guangzhou University, Guangdong, Guangzhou, 510006, China;
12.School of Physics and Technology, Wuhan University, Hubei, Wuhan, 430072, China;
13.Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Jiangsu, Nanjing, 210023, China;
14.Hebei Normal University, Hebei, Shijiazhuang, 050024, China;
15.Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, 200030, China;
16.Key Laboratory of Cosmic Rays, Tibet University, Ministry of Education, Tibet, Lhasa, 850000, China;
17.National Astronomical Observatories, Chinese Academy of Sciences, Beijing, 100101, China;
18.School of Physics and Astronomy, School of Physics (Guangzhou), Sun Yat-Sen University, Guangdong, Zhuhai, 519000, China;
19.Dipartimento di Fisica, Università di Napoli
20.School of Physics and Astronomy, Yunnan University, Yunnan, Kunming, 650091, China;
21.D'epartement de Physique Nucl'eaire et Corpusculaire, Facult'e de Sciences, Universit'e de Genève, 24 Quai Ernest Ansermet, Geneva, 1211, Switzerland;
22.Institute of Frontier and Interdisciplinary Science, Shandong University, Shandong, Qingdao, 266237, China;
23.Department of Engineering Physics, Tsinghua University, Beijing, 100084, China;
24.School of Physics and Microelectronics, Zhengzhou University, Henan, Zhengzhou, 450001, China;
25.Yunnan Observatories, Chinese Academy of Sciences, Yunnan, Kunming, 650216, China;
26.Institute for Nuclear Research, Russian Academy of Sciences, Moscow, 117312, Russia;
27.School of Physics, Peking University, Beijing, 100871, China;
28.School of Physical Science and Technology, Guangxi University, Guangxi, Nanning, 530004, China;
29.Tsung-Dao Lee Institute, School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240, China;
30.Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand;
31.Moscow Institute of Physics and Technology, Moscow, 141700, Russia;
32.National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China
Recommended Citation
GB/T 7714
Cao, Zhen,Aharonian, F.,An, Q.,et al. A 3D Likelihood Analysis Tool for LHAASO-KM2A data[C]:Sissa Medialab Srl,2022.
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