Self-calibration of LHAASO-KM2A electromagnetic particle detectors using single particles within extensive air showers

Aharonian, F.; An, Q.; Axikegu,; Bai, Lixin; Bai, Y.; Bao, Yiwei; Bastieri, D.; Bi, X. J.; Bi, Y. J.; Cai, J. T.; Cao, Z.; Chang, Jin; Chen, E. S.; Chen, L.; Chen, M. J.; Chen, M. L.; Chen, Q. H.; Chen, S. H.; Chen, S. Z.; Chen, T. L.; Chen, Y.; Cheng, Huzi; Cheng, Ning; Cheng, Yaodong; Cui, S. W.; Cui, Xiaohong; Cui, Yudong; Piazzoli, B. D’Ettorre; Dai, B. Z.; Dai, H. L.; Dai, Z. G.; Danzengluobu,; Volpe, D. della; Duan, Kai-Kai; Fan, J. H.; Fan, Yi‐Zhong; Zhou, Fan; Fang, Jun; Fang, Kun; Feng, C.; Feng, Li; Feng, S. H.; Feng, X. T.; Feng, Y. L.; Gao, Bo; Gao, Chengyong; Gao, Liang; Gao, Qi; Gao, Wei; Ge, M. M.; Geng, L. S.; Gong, Guanghua; Gou, Q. B.; Gu, M. H.; Guo, Fulai; Guo, J. G.; Guo, Xiaolei; Guo, Y. Q.; Guo, Y. Y.; Han, Y. A.; He, H. H.; He, Hao-Ning; He, S. L.; He, Xinbo; He, Y.; Heller, M.; Hor, Y. K.; Hou, Chao; Hou, X.; Hu, Hongbo; Hu, Qing Sheng; Hu, S. C.; Hu, X.; Huang, D.; Huang, Wenhao; Huang, X. T.; Huang, Xingtao; Huang, Yun‐Feng; Huang, Z. C.; Ji, X. L.; Jia, H. Y.; Jia, K.; Jiang, K.; Jiang, Z. J.; Jin, Ming; Kang, Mingming; Tang, Ke; Kuleshov, D.A.; Levochkin, K.; Li, B. B.; Li, C.; Li, F.; Li, H. B.; Li, H. C.; Li, H. Y.; Li, J.; Li, J.; Li, J.; Li, K.; Li, W. L.; Li, X. R.; Li, X.; Li, Y. Z.; Li, Z.; Liang, En‐Wei; Liang, Yun-Feng; Lin, S. J.; Liu, Baolin; Liu, C.; Liu, D.; Liu, H.; Liu, H. D.; Liu, J.; Liu, J. L.; Liu, J. S.; Liu, J. Y.; Liu, M. Y.; Liu, R. Y.; Liu, S. M.; Liu, W.; Liu, Y.; Liu, Y. N.; Long, W. J.; Lü, Rui; Luo, Qing; Lv, Hongkui; Q., B.; Ma, L. L.; H., X.; Mao, J.; Masood, A.; Min, Z.; Mitthumsiri, W.; Nan, Y. C.; Ou, Zhanpeng; Pang, B. Y.; Pattarakijwanich, P.; Pei, Z. Y.; Qi, M. Y.; Qi, Y. Q.; Qiao, Bing-Qiang; Qin, Jiajun; Ruffolo, D.; Sáiz, A.; Shao, Chen; Shao, L.; Shchegolev, O. B.; Sheng, X. D.; Shi, J. Y.; Song, H. C.; Stenkin, Yu. V.; Stepanov, V.; Su, Yang; Sun, Q. N.; Sun, Xiao-Na; Sun, Zhang‐Hua; Tam, P. H. T.; Tang, Z.; Tian, Wei; Wang, B. D.; Wang, C.; Wang, H.; Wang, H. G.; Wang, J. C.; Wang, J. S.; Wang, L. P.; Wang, L. Y.; Wang, R.; Wang, R. N.; Wang, W.; Wang, X. G.; Wang, X. Y.; Wang, Y.; Wang, Y. D.; Wang, Y. J.; Wang, Y. P.; Wang, Z. H.; Wang, Z. X.; Wang, Z.; Wei, Da-Ming; Wei, J. J.; Wei, Y. J.; Wen, Tao; Wu, C. Y.; Wu, Hong; Wu, Sha Sha; Wu, Xue-Feng; Wu, Yuping; Xi, Shao-Qiang; Xia, J.; Xiang, G. M.; Xiao, D. X.; Xiao, G. C.; Xin, G. G.; Xin, Y.; Xing, Yongzhong; Xiong, Z.; Xu, D. L.; Xu, R. X.; Xue, L.; Yan, Dahai; Yan, Jun; Yang, Chaowen; Yang, Fang; Yang, H. W.; Yang, Jian-Huan; Yang, Lili; Yang, Min; Yang, R.; Yang, S. B.; Yao, Y. H.; Yao, Z. G.; Ye, Y. M.; Yin, L. Q.; Yin, Na; You, X. H.; You, Z. Y.; Yu, Y. H.; Yuan, Q.; Yue, H.; Zeng, Houdun; Zeng, Tingxuan; Zeng, W.; Zeng, Z. K.; Zha, M.; Zhai, X. X.; Zhang, B. B.; Zhang, F.; Zhang, H. M.; Zhang, H. Y.; Zhang, J. L.; Zhang, L. X.; Zhang, L.; Zhang, P. F.; Zhang, P. P.; Zhang, R.; Zhang, S. B.; Zhang, S. R.; Zhang, S. S.; Zhang, X.; Zhang, X. P.; Zhang, Y. F.; Zhang, Y. L.; Zhang, Y.; Zhao, Bing; Zhao, Jing; Liu, Zhao; Zhao, S. P.; Zheng, F.; Zheng, Y.; Zhou, Bin; Zhou, H.; Zhou, J. N.; Zhou, Ping; Zhou, Rong; Zhou, X. X.; Zhu, C. G.; Zhu, F. R.; Zhu, Hui; Zhu, K. J.; Zuo, Xin

doi:10.1103/physrevd.106.122004

Cited by 5 publications

(2 citation statements)

References 38 publications

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“…The typical detection efficiency is about 98% and time resolution is about 2 ns. The response time and signal amplitude of each ED is calibrated using offline methods (Lv et al 2018;Aharonian et al 2022). A trigger is generated when 20 EDs are fired within a 400 ns window.…”

Section: The Lhaaso Detector and Datamentioning

confidence: 99%

The First LHAASO Catalog of Gamma-Ray Sources

Cao,

Aharonian,

et al. 2024

ApJS

Self Cite

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We present the first catalog of very-high-energy and ultra-high-energy gamma-ray sources detected by the Large High Altitude Air Shower Observatory. The catalog was compiled using 508 days of data collected by the Water Cherenkov Detector Array from 2021 March to 2022 September and 933 days of data recorded by the Kilometer Squared Array from 2020 January to 2022 September. This catalog represents the main result from the most sensitive large coverage gamma-ray survey of the sky above 1 TeV, covering decl. from −20° to 80°. In total, the catalog contains 90 sources with an extended size smaller than 2° and a significance of detection at >5σ. Based on our source association criteria, 32 new TeV sources are proposed in this study. Among the 90 sources, 43 sources are detected with ultra-high energy (E > 100 TeV) emission at >4σ significance level. We provide the position, extension, and spectral characteristics of all the sources in this catalog.

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Section: The Lhaaso Detector and Datamentioning

confidence: 99%

The First LHAASO Catalog of Gamma-Ray Sources

Cao,

Aharonian,

et al. 2024

ApJS

Self Cite

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“…Based on the experimental capabilities of the LHAASO square kilometer array (KM2A) experiment [42,43], which includes 5249 electromagnetic detectors spaced at 15 meters and 1188 muon detectors spaced at 30 meters, we can expect that the method proposed in this study is a suitable tool for reconstructing the mass composition around the knee from the forthcoming measurements of the LHAASO experiment.…”

Section: Jcap09(2023)020mentioning

confidence: 99%

Cosmic ray mass composition at the knee using azimuthal fluctuations of air shower particles detected at ground by the KASCADE experiment

Arsene

2023

J. Cosmol. Astropart. Phys.

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The presence of hadronic sub-showers causes azimuthal non-uniformity in the particle distributions on the ground in vertical air showers. The LCm parameter, which quantifies the non-uniformity of the signal recorded in detectors located at a given distance on a ring around the shower axis, has been successfully introduced as a gamma/hadron discriminator at PeV energies [23]. In this work, we demonstrate that the LCm parameter can effectively serve as a mass composition discriminator in experiments that employ a compact array of detectors, like KASCADE. We reconstruct the LCm parameter distributions in the energy range lg(E/eV) = [15.0 – 16.0] using measurements from the KASCADE experiment, with intervals of lg(E/eV) = 0.2, which are then fitted with MC templates for five primary nuclei species p, He, C, Si, and Fe considering three hadronic interaction models: QGSjet-II-04, EPOS-LHC and SIBYLL 2.3d. We find that the LCm parameter exhibits minimal dependence on the specific hadronic interaction model considered. The reconstructed fractions of individual species demonstrate a linear decrease in the abundance of protons and He nuclei with increasing energy, while the heavier components become prevalent above the knee as predicted by all three hadronic interaction models. Our findings indicate that the abundance of particle types as a function of energy aligns with different astrophysical models that link the knee to the acceleration and propagation of cosmic rays within the Galaxy. Furthermore, they also demonstrate excellent agreement with three more recent data-driven astrophysical models. These findings suggest that the LCm parameter could be a valuable tool for forthcoming measurements of the LHAASO experiment to enhance our knowledge about the origin and acceleration mechanisms of cosmic rays.

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