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Study of BESIII trigger efficiencies with the 2018 J/ψ data

本站小编 Free考研考试/2022-01-01

M. Ablikim 1,
, M. N. Achasov 10,c,
, P. Adlarson 67,
, S. Ahmed 15,
, M. Albrecht 4,
, R. Aliberti 28,
, A. Amoroso 66,66,
, M. R. An 32,
, Q. An 49,63,
, X. H. Bai 57,
, Y. Bai 48,
, O. Bakina 29,
, R. Baldini Ferroli 23,
, I. Balossino 24,1,
, Y. Ban 38,k,
, K. Begzsuren 26,
, N. Berger 28,
, M. Bertani 23,
, D. Bettoni 24,
, F. Bianchi 66,66,
, J. Bloms 60,
, A. Bortone 66,66,
, I. Boyko 29,
, R. A. Briere 5,
, H. Cai 68,
, X. Cai 1,49,
, A. Calcaterra 23,
, G. F. Cao 1,54,
, N. Cao 1,54,
, S. A. Cetin 53,
, J. F. Chang 1,49,
, W. L. Chang 1,54,
, G. Chelkov 29,b,
, D. Y. Chen 6,
, G. Chen 1,
, H. S. Chen 1,54,
, M. L. Chen 1,49,
, S. J. Chen 35,
, X. R. Chen 25,
, Y. B. Chen 1,49,
, Z. J Chen 20,l,
, W. S. Cheng 66,
, G. Cibinetto 24,
, F. Cossio 66,
, X. F. Cui 36,
, H. L. Dai 1,49,
, X. C. Dai 1,54,
, A. Dbeyssi 15,
, R. E. de Boer 4,
, D. Dedovich 29,
, Z. Y. Deng 1,
, A. Denig 28,
, I. Denysenko 29,
, M. Destefanis 66,66,
, F. De Mori 66,66,
, Y. Ding 33,
, C. Dong 36,
, J. Dong 1,49,
, L. Y. Dong 1,54,
, M. Y. Dong 1,
, X. Dong 68,
, S. X. Du c,
, Y. L. Fan 68,
, J. Fang 1,49,
, S. S. Fang 1,54,
, Y. Fang 1,
, R. Farinelli 24,
, L. Fava 66,66,
, F. Feldbauer 4,
, G. Felici 23,
, C. Q. Feng 49,63,
, J. H. Feng 50,
, M. Fritsch 4,
, C. D. Fu 1,
, Y. Gao 64,
, Y. Gao 49,63,
, Y. Gao 38,k,
, Y. G. Gao 6,
, I. Garzia 24,24,
, P. T. Ge 68,
, C. Geng 50,
, E. M. Gersabeck 58,
, A Gilman 61,
, K. Goetzen 11,
, L. Gong 33,
, W. X. Gong 1,49,
, W. Gradl 28,
, M. Greco 66,66,
, L. M. Gu 35,
, M. H. Gu 1,49,
, S. Gu 2,
, Y. T. Gu 13,
, C. Y Guan 1,54,
, A. Q. Guo 22,
, L. B. Guo 34,
, R. P. Guo 40,
, Y. P. Guo 9,h,
, A. Guskov 29,
, T. T. Han 41,
, W. Y. Han 32,
, X. Q. Hao 16,
, F. A. Harris 56,
, H Hüsken 22,28,
, K. L. He 1,54,
, F. H. Heinsius 4,
, C. H. Heinz 28,
, T. Held 4,
, Y. K. Heng 1,
, C. Herold 51,
, M. Himmelreich 11,f,
, T. Holtmann 4,
, Y. R. Hou 54,
, Z. L. Hou 1,
, H. M. Hu 1,54,
, J. F. Hu 47,
, T. Hu 1,
, Y. Hu 1,
, G. S. Huang 49,63,
, L. Q. Huang 64,
, X. T. Huang 41,
, Y. P. Huang 1,
, Z. Huang 38,k,
, T. Hussain 65,
, W. Ikegami Andersson 67,
, W. Imoehl 22,
, M. Irshad 49,63,
, S. Jaeger 4,
, S. Janchiv 26,j,
, Q. Ji 1,
, Q. P. Ji 16,
, X. B. Ji 1,54,
, X. L. Ji 1,49,
, H. B. Jiang 41,
, X. S. Jiang 1,
, J. B. Jiao 41,
, Z. Jiao 18,
, S. Jin 35,
, Y. Jin 57,
, T. Johansson 67,
, N. Kalantar-Nayestanaki 55,
, X. S. Kang 33,
, R. Kappert 55,
, M. Kavatsyuk 55,
, B. C. Ke 1,43,
, I. K. Keshk 4,
, A. Khoukaz 60,
, P. Kiese 28,
, R. Kiuchi 1,
, R. Kliemt 11,
, L. Koch 30,
, O. B. Kolcu 53,e,
, B. Kopf 4,
, M. Kuemmel 4,
, M. Kuessner 4,
, A. Kupsc 67,
, M. G. Kurth 1,54,
, W. Kühn 30,
, J. J. Lane 58,
, J. S. Lange 30,
, P. Larin 15,
, A. Lavania 21,
, L. Lavezzi 66,66,1,
, Z. H. Lei 49,63,
, H. Leithoff 28,
, M. Lellmann 28,
, T. Lenz 28,
, C. Li 39,
, C. H. Li 32,
, Cheng Li 49,63,
, D. M. Li c,
, F. Li 1,49,
, G. Li 1,
, H. Li 43,
, H. Li 49,63,
, H. B. Li 1,54,
, H. J. Li 9,h,
, J. L. Li 41,
, J. Q. Li 4,
, J. S. Li 50,
, Ke Li 1,
, L. K. Li 1,
, Lei Li 3,
, P. R. Li 31,
, S. Y. Li 52,
, W. D. Li 1,54,
, W. G. Li 1,
, X. H. Li 49,63,
, X. L. Li 41,
, Z. Y. Li 50,
, H. Liang 49,63,
, H. Liang 1,54,
, H. Liang 27,
, Y. F. Liang 45,
, Y. T. Liang 25,
, L. Z. Liao 1,54,
, J. Libby 21,
, C. X. Lin 50,
, B. J. Liu 1,
, C. X. Liu 1,
, D. Liu 49,63,
, F. H. Liu 44,
, Fang Liu 1,
, Feng Liu 6,
, H. B. Liu 13,
, H. M. Liu 1,54,
, Huanhuan Liu 1,
, Huihui Liu 17,
, J. B. Liu 49,63,
, J. L. Liu 64,
, J. Y. Liu 1,54,
, K. Liu 1,
, K. Y. Liu 33,
, Ke Liu 6,
, L. Liu 49,63,
, M. H. Liu 9,h,
, P. L. Liu 1,
, Q. Liu 54,
, Q. Liu 68,
, S. B. Liu 49,63,
, Shuai Liu 46,
, T. Liu 1,54,
, W. M. Liu 49,63,
, X. Liu 31,
, Y. Liu 31,
, Y. B. Liu 36,
, Z. A. Liu 1,
, Z. Q. Liu 41,
, X. C. Lou 1,
, F. X. Lu 16,
, F. X. Lu 50,
, H. J. Lu 18,
, J. D. Lu 1,54,
, J. G. Lu 1,49,
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, Y. Lu 1,
, Y. P. Lu 1,49,
, C. L. Luo 34,
, M. X. Luo b,
, P. W. Luo 50,
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, X. L. Luo 1,49,
, S. Lusso 66,
, X. R. Lyu 54,
, F. C. Ma 33,
, H. L. Ma 1,
, L. L. Ma 41,
, M. M. Ma 1,54,
, Q. M. Ma 1,
, R. Q. Ma 1,54,
, R. T. Ma 54,
, X. X. Ma 1,54,
, X. Y. Ma 1,49,
, F. E. Maas 15,
, M. Maggiora 66,66,
, S. Maldaner 4,
, S. Malde 61,
, Q. A. Malik 65,
, A. Mangoni 23,
, Y. J. Mao 38,k,
, Z. P. Mao 1,
, S. Marcello 66,66,
, Z. X. Meng 57,
, J. G. Messchendorp 55,
, G. Mezzadri 24,1,
, T. J. Min 35,
, R. E. Mitchell 22,
, X. H. Mo 1,
, Y. J. Mo 6,
, N. Yu. Muchnoi 10,c,
, H. Muramatsu 59,
, S. Nakhoul 11,f,
, Y. Nefedov 29,
, F. Nerling 11,f,
, I. B. Nikolaev 10,c,
, Z. Ning 1,49,
, S. Nisar 8,i,
, S. L. Olsen 54,
, Q. Ouyang 1,
, S. Pacetti 23,23,
, X. Pan 9,h,
, Y. Pan 58,
, A. Pathak 1,
, P. Patteri 23,
, M. Pelizaeus 4,
, H. P. Peng 49,63,
, K. Peters 11,f,
, J. Pettersson 67,
, J. L. Ping 34,
, R. G. Ping 1,54,
, R. Poling 59,
, V. Prasad 49,63,
, H. Qi 49,63,
, H. R. Qi 52,
, K. H. Qi 25,
, M. Qi 35,
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, S. Qian 1,49,
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, Z. Qian 50,
, C. F. Qiao 54,
, L. Q. Qin 12,
, X. S. Qin 4,
, Z. H. Qin 1,49,
, J. F. Qiu 1,
, S. Q. Qu 36,
, K. H. Rashid 65,
, K. Ravindran 21,
, C. F. Redmer 28,
, A. Rivetti 66,
, V. Rodin 55,
, M. Rolo 66,
, G. Rong 1,54,
, Ch. Rosner 15,
, M. Rump 60,
, H. S. Sang 63,
, A. Sarantsev 29,d,
, Y. Schelhaas 28,
, C. Schnier 4,
, K. Schoenning 67,
, M. Scodeggio 24,24,
, D. C. Shan 46,
, W. Shan 19,
, X. Y. Shan 49,63,
, J. F. Shangguan 46,
, M. Shao 49,63,
, C. P. Shen 9,
, P. X. Shen 36,
, X. Y. Shen 1,54,
, H. C. Shi 49,63,
, R. S. Shi 1,54,
, X. Shi 1,49,
, X. D Shi 49,63,
, W. M. Song 1,27,
, Y. X. Song 38,k,
, S. Sosio 66,66,
, S. Spataro 66,66,
, K. X. Su 68,
, P. P. Su 46,
, F. F. Sui 41,
, G. X. Sun 1,
, H. K. Sun 1,
, J. F. Sun 16,
, L. Sun 68,
, S. S. Sun 1,54,
, T. Sun 1,54,
, W. Y. Sun 34,
, W. Y. Sun 27,
, X Sun 20,l,
, Y. J. Sun 49,63,
, Y. K. Sun 49,63,
, Y. Z. Sun 1,
, Z. T. Sun 1,
, Y. H. Tan 68,
, Y. X. Tan 49,63,
, C. J. Tang 45,
, G. Y. Tang 1,
, J. Tang 50,
, J. X. Teng 49,63,
, V. Thoren 67,
, I. Uman 53,
, B. Wang 1,
, C. W. Wang 35,
, D. Y. Wang 38,k,
, H. J. Wang 31,
, H. P. Wang 1,54,
, K. Wang 1,49,
, L. L. Wang 1,
, M. Wang 41,
, M. Z. Wang 38,k,
, Meng Wang 1,54,
, W. Wang 50,
, W. H. Wang 68,
, W. P. Wang 49,63,
, X. Wang 38,k,
, X. F. Wang 31,
, X. L. Wang 9,h,
, Y. Wang 49,63,
, Y. Wang 50,
, Y. D. Wang 37,
, Y. F. Wang 1,
, Y. Q. Wang 1,
, Y. Y. Wang 31,
, Z. Wang 1,49,
, Wang Z. Y. 1, 52,
, Ziyi Wang 54,
, Zongyuan Wang 1,54,
, D. H. Wei 12,
, P. Weidenkaff 28,
, F. Weidner 60,
, S. P. Wen 1,
, D. J. White 58,
, U. Wiedner 4,
, G. Wilkinson 61,
, M. Wolke 67,
, L. Wollenberg 4,
, J. F. Wu 1,54,
, L. H. Wu 1,
, L. J. Wu 1,54,
, X. Wu 9,h,
, Z. Wu 1,49,
, L. Xia 49,63,
, H. Xiao 9,h,
, S. Y. Xiao 1,
, Z. J. Xiao 34,
, X. H. Xie 38,k,
, Y. G. Xie 1,49,
, Y. H. Xie 6,
, T. Y. Xing 1,54,
, G. F. Xu 1,
, Q. J. Xu 14,
, W. Xu 1,54,
, X. P. Xu 46,
, F. Yan 9,h,
, L. Yan 9,h,
, W. B. Yan 49,63,
, W. C. Yan c,
, Xu Yan 46,
, H. J. Yang 42,g,
, H. X. Yang 1,
, L. Yang 43,
, S. L. Yang 54,
, Y. X. Yang 12,
, Yifan Yang 1,54,
, Zhi Yang 25,
, M. Ye 1,49,
, M. H. Ye 7,
, J. H. Yin 1,
, Z. Y. You 50,
, B. X. Yu 1,
, C. X. Yu 36,
, G. Yu 1,54,
, J. S. Yu 20,l,
, T. Yu 64,
, C. Z. Yuan 1,54,
, L. Yuan 2,
, X. Q. Yuan 38,k,
, Y. Yuan 1,
, Z. Y. Yuan 50,
, C. X. Yue 32,
, A. Yuncu 53,a,
, A. A. Zafar 65,
, Y. Zeng 20,l,
, B. X. Zhang 1,
, Guangyi Zhang 16,
, H. Zhang 63,
, H. H. Zhang 50,
, H. H. Zhang 27,
, H. Y. Zhang 1,49,
, J. J. Zhang 43,
, J. L. Zhang a,
, J. Q. Zhang 34,
, J. W. Zhang 1,
, J. Y. Zhang 1,
, J. Z. Zhang 1,54,
, Jianyu Zhang 1,54,
, Jiawei Zhang 1,54,
, L. Q. Zhang 50,
, Lei Zhang 35,
, S. Zhang 50,
, S. F. Zhang 35,
, Shulei Zhang 20,l,
, X. D. Zhang 37,
, X. Y. Zhang 41,
, Y. Zhang 61,
, Y. H. Zhang 1,49,
, Y. T. Zhang 49,63,
, Yan Zhang 49,63,
, Yao Zhang 1,
, Yi Zhang 9,h,
, Z. H. Zhang 6,
, Z. Y. Zhang 68,
, G. Zhao 1,
, J. Zhao 32,
, J. Y. Zhao 1,54,
, J. Z. Zhao 1,49,
, Lei Zhao 49,63,
, Ling Zhao 1,
, M. G. Zhao 36,
, Q. Zhao 1,
, S. J. Zhao c,
, Y. B. Zhao 1,49,
, Y. X. Zhao 25,
, Z. G. Zhao 49,63,
, A. Zhemchugov 29,b,
, B. Zheng 64,
, J. P. Zheng 1,49,
, Y. Zheng 38,k,
, Y. H. Zheng 54,
, B. Zhong 34,
, C. Zhong 64,
, L. P. Zhou 1,54,
, Q. Zhou 1,54,
, X. Zhou 68,
, X. K. Zhou 54,
, X. R. Zhou 49,63,
, A. N. Zhu 1,54,
, J. Zhu 36,
, K. Zhu 1,
, K. J. Zhu 1,
, S. H. Zhu 62,
, T. J. Zhu a,
, W. J. Zhu 36,
, W. J. Zhu 9,h,
, Y. C. Zhu 49,63,
, Z. A. Zhu 1,54,
, B. S. Zou 1,
, J. H. Zou 1,
, (BESIII Collaboration)
, 1.Institute of High Energy Physics, Beijing 100049, China
2.Beihang University, Beijing 100191, China
3.Beijing Institute of Petrochemical Technology, Beijing 102617, China
4.Bochum Ruhr-University, D-44780 Bochum, Germany
5.Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
6.Central China Normal University, Wuhan 430079, China
7.China Center of Advanced Science and Technology, Beijing 100190, China
8.COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
9.Fudan University, Shanghai 200443, China
10.G.I. Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
11.GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
12.Guangxi Normal University, Guilin 541004, China
13.Guangxi University, Nanning 530004, China
14.Hangzhou Normal University, Hangzhou 310036, China
15.Helmholtz Institute Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
16.Henan Normal University, Xinxiang 453007, China
17.Henan University of Science and Technology, Luoyang 471003, China
18.Huangshan College, Huangshan 245000, China
19.Hunan Normal University, Changsha 410081, China
20.Hunan University, Changsha 410082, China
21.Indian Institute of Technology Madras, Chennai 600036, India
22.Indiana University, Bloomington, Indiana 47405, USA
23.(A)INFN Laboratori Nazionali di Frascati, I-00044, Frascati, Italy; (B)INFN Sezione di Perugia, I-06100, Perugia, Italy; (C)University of Perugia, I-06100, Perugia, Italy
24.(A)INFN Sezione di Ferrara, I-44122, Ferrara, Italy; (B)University of Ferrara, I-44122, Ferrara, Italy
25.Institute of Modern Physics, Lanzhou 730000, China
26.Institute of Physics and Technology, Peace Ave. 54B, Ulaanbaatar 13330, Mongolia
27.Jilin University, Changchun 130012, China
28.Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
29.Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
30.Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
31.KVI-CART, University of Groningen, NL-9747 AA Groningen, The Netherlands
32.Lanzhou University, Lanzhou 730000, China
33.Liaoning Normal University, Dalian 116029, China
34.Liaoning University, Shenyang 110036, China
35.Nanjing Normal University, Nanjing 210023, China
36.Nanjing University, Nanjing 210093, China
37.Nankai University, Tianjin 300071, China
38.Peking University, Beijing 100871, China
39.Qufu Normal University, Qufu 273165, China
40.Shandong Normal University, Jinan 250014, China
41.Shandong University, Jinan 250100, China
42.Shanghai Jiao Tong University, Shanghai 200240, China
43.Shanxi Normal University, Linfen 041004, China
44.Shanxi University, Taiyuan 030006, China
45.Sichuan University, Chengdu 610064, China
46.Soochow University, Suzhou 215006, China
47.Southeast University, Nanjing 211100, China
48.State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, China
49.Sun Yat-Sen University, Guangzhou 510275, China
50.Tsinghua University, Beijing 100084, China
51.(A)Ankara University, 06100 Tandogan, Ankara, Turkey; (B)Istanbul Bilgi University, 34060 Eyup, Istanbul, Turkey; (C)Uludag University, 16059 Bursa, Turkey; (D)Near East University, Nicosia, North Cyprus, Mersin 10, Turkey
52.University of Chinese Academy of Sciences, Beijing 100049, China
53.University of Hawaii, Honolulu, Hawaii 96822, USA
54.University of Jinan, Jinan 250022, China
55.University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
56.University of Minnesota, Minneapolis, Minnesota 55455, USA
57.University of Muenster, Wilhelm-Klemm-Str. 9, 48149 Muenster, Germany
58.University of Oxford, Keble Rd, Oxford, UK OX13RH
59.University of Science and Technology Liaoning, Anshan 114051, China
60.University of Science and Technology of China, Hefei 230026, China
61.University of South China, Hengyang 421001, China
62.University of the Punjab, Lahore-54590, Pakistan
63.(A) University of Turin, I-10125, Turin, Italy; (B) University of Eastern Piedmont, I-15121, Alessandria, Italy; (C) INFN, I-10125, Turin, Italy
64.Uppsala University, Box 516, SE-75120 Uppsala, Sweden
65.Wuhan University, Wuhan 430072, China
66.Xinyang Normal University, Xinyang 464000, China
67.Zhejiang University, Hangzhou 310027, China
68.Zhengzhou University, Zhengzhou 450001, China
a.Also at Bogazici University, 34342 Istanbul, Turkey
b.Also at the Moscow Institute of Physics and Technology, Moscow 141700, Russia
c.Also at the Novosibirsk State University, Novosibirsk, 630090, Russia
d.Also at the NRC "Kurchatov Institute", PNPI, 188300, Gatchina, Russia
e.Also at Istanbul Arel University, 34295 Istanbul, Turkey
f.Also at Goethe University Frankfurt, 60323 Frankfurt am Main, Germany
g.Also at Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology; Institute of Nuclear and Particle Physics, Shanghai 200240, China
h.Also at Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics, Fudan University, Shanghai 200443, China
i.Also at Harvard University, Department of Physics, Cambridge, MA, 02138, USA
j.Currently at: Institute of Physics and Technology, Peace Ave.54B, Ulaanbaatar 13330, Mongolia
k.Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China
l.School of Physics and Electronics, Hunan University, Changsha 410082, China
Received Date:2020-09-29
Available Online:2021-02-15
Abstract:Using a dedicated data sample taken in 2018 on the J/ψ peak, we perform a detailed study of the trigger efficiencies of the BESIII detector. The efficiencies are determined from three representative physics processes, namely Bhabha scattering, dimuon production and generic hadronic events with charged particles. The combined efficiency of all active triggers approaches 100% in most cases, with uncertainties small enough not to affect most physics analyses.

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I.INTRODUCTION
The Beijing Electron-Positron Collider (BEPCII) is a double-ring multi-bunch $ e^{+}e^{-} $ collider with a design luminosity of $ 1 \times 10^{33}\; {\rm{c}}{{\rm{m}}^{{\rm{ - 2}}}}\;{{\rm{s}}^{{\rm{ - 1}}}} $, optimized for a center-of-mass energy of $ 2\times 1.89 $ GeV, an increase of a factor of 100 more than its predecessor. The Beijing Spectrometer III (BESIII) detector operating at BEPCII is a multipurpose detector designed for the precision study of $ \tau- $charm physics [1-3].
BEPCII collides electron and positron bunches at a frequency of 125 MHz. The main backgrounds in BESIII are caused by lost beam particles and their interaction with the detector, and the background event rate is estimated to be about 13 MHz [3]. In comparison, the signal rate at the $ J/\psi $ resonance is about 2 kHz and the BESIII data acquisition system can record events at a rate of up to 4 kHz. The task of the trigger system is thus to suppress backgrounds by more than three orders of magnitude whilst maintaining a high efficiency for signal events.
Monitoring the trigger efficiency carefully is important in order not to lose events due to inefficient triggers. A trigger efficiency study was performed in 2010 for data samples of $ J/\psi $ and $ \psi(2S) $ events recorded in 2009 [4]. Slightly changed trigger conditions in 2018 motivate the study presented here.
The BESIII trigger system combines the information from the electromagnetic calorimeter (EMC), the main drift chamber (MDC), the time-of-flight system (TOF) and the muon counter (MUC) to form a total of 48 trigger conditions (Table 1) to select for readout of interesting interactions. A detailed description of the trigger system can be found in Refs. [2, 5]. The trigger conditions are combined into 16 trigger channels (Table 2) by the global trigger logic (GTL). The trigger conditions included in trigger channel 12 are delayed by 576 ns in order to distinguish neutral events from charged events. The event is read out if any enabled trigger channel is active.
No. Trigger Condition Comments
Electromagnetic calorimeter (EMC)
0 NClus.GE.1 Number of Clusters $\geqslant$ 1
1 NClus.GE.2 Number of Clusters $\geqslant$ 2
2 BClus_BB Barrel Cluster Back to Back
3 EClus_BB Endcap Cluster Back to Back
4 Clus_Z Cluster Balance in z direction
5 BClus_Phi Barrel Cluster Balance in $\phi$ direction
6 EClus_Phi Endcap Cluster Balance in $\phi$ direction
7 BEtot_H Barrel total Energy, Higher threshold
8 EEtot_H Endcap total Energy, Higher threshold
9 Etot_L Total Energy, Lower threshold
10 Etot_M Total Energy, Middle threshold
11 BL_EnZ Energy Balance in z direction
12 NBClus.GE.1 Number of Barrel Clusters $\geqslant$ 1
13 NEClus.GE.1 Number of Endcap Clusters $\geqslant$ 1
14 BL_BBLK Barrel Energy Block Balance
15 BL_EBLK Endcap Energy Block Balance

Time of flight system (ToF)

16 ETOF_BB Endcap TOF Back to Back
17 BTOF_BB Barrel TOF Back to Back
18 NETOF.GE.2 Number of Endcap TOF hits $\geqslant$ 2
19 NETOF.GE.1 Number of Endcap TOF hits $\geqslant$ 1
20 NBTOF.GE.2 Number of Barrel TOF hits $\geqslant$ 2
21 NBTOF.GE.1 Number of Barrel TOF hits $\geqslant$ 1
22 NTOF.GE.1 Number of TOF hits $\geqslant$ 1

Muon counter (MUC)

32 NABMU.GE.1 Barrel Tracks number $\geqslant$ 1 for A
33 NAEMU.GE.1 Endcap Tracks number $\geqslant$ 1 for A
34 NCBMU.GE.1 Barrel Tracks number $\geqslant$ 1 for C
35 NCEMU.GE.1 Endcap Tracks number $\geqslant$ 1 for C
36 CBMU_BB Barrel Track Back to Back for C
37 CEMU_BB Endcap Track Back to Back for C

A: 2 of 4 Tracking; C: 3 of 4 Tracking

Main drift chamber (MDC)

38 STrk_BB Short Tracks Back to Back
39 NSTrk.GE.N Number of Short Tracks $\geqslant$ N
40 NSTrk.GE.2 Number of Short Tracks $\geqslant$ 2
41 NSTrk.GE.1 Number of Short Tracks $\geqslant$ 1
42 LTrk_BB Long Tracks Back to Back
43 NLTrk.GE.N Number of Long Tracks $\geqslant$ N
44 NLTrk.GE.2 Number of Long Tracks $\geqslant$ 2
45 NLTrk.GE.1 Number of Long Tracks $\geqslant$ 1
46 NItrk.GE.2 Number of Inner Tracks $\geqslant$ 2
47 NItrk.GE.1 Number of Inner Tracks $\geqslant$ 1


Table1.Trigger conditions.

Channel Conditions combination Comments
CH01 NEClus.GE.1&& NETOF.GE.1&& STrk_BB For Charged
CH02 NBClus.GE.1&& NBTOF.GE.2&& NLtrk.GE.2 For Charged
CH03 NBTOF.GE.2&& NLtrk.GE.2 Not used
CH04 BTOF_BB&& LTrk_BB For Charged
CH05 Etot_L&& NBTOF.GE.1&& NLtrk.GE.1 For Charged
CH06 NBClus.GE.1&& NBTOF.GE.1&& NLtrk.GE.2 For Charged
CH07 ? Not used
CH08 ? Not used
CH09 NClus.GE.1&& BEtot_H For Neutral
CH10 ? Random
CH11 NBTOF.GE.2&& LTrk_BB Not used
CH12 NClus.GE.2&& Etot_M Delayed Neutral
CH13 Etot_L&& NTOF.GE.1 Not used
CH14 BTOF_BB Not used
CH15 NClus.GE.1 Not used
CH16 ECLUS_BB Not used


Table2.Trigger channels.

Compared to earlier data taking periods, for the 2018 $ J/\psi $ data taking the CH09 trigger channel described in Table 2 was added as a high efficiency selection for neutral events with precise timing information. The CH03 channel described in Table 2 had to be disabled due to increased noise in the MDC, and some other trigger channels were not used, as marked in Table 2, since the trigger conditions in these trigger channels are already included or implied in “used” trigger channels.
Using a similar approach to that described in Ref. [4], we study the trigger efficiency for the $ J/\psi $ events taken in 2018 in order to understand the performance for the updated trigger system.
II.DATA SET
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A.Trigger menu for the 2018 data taking
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A.Trigger menu for the 2018 data taking

Table 3 shows the trigger menu used for the 2018 $ J/\psi $ data taking campaign, which has not changed since 2012, with the exception of CH03 mentioned above. The enabled channels are categorized into three almost independent groups, namely endcap charged, barrel charged and neutral.
Channel Conditions Group
CH01 NEClus.GE.1&& NETOF.GE.1&& STrk_BB Endcap Charged
CH02 NBClus.GE.1&& NBTOF.GE.2&& NLtrk.GE.2
CH04 BTOF_BB&& LTrk_BB Barrel Charged
CH05 Etot_L&& NBTOF.GE.1&& NLtrk.GE.1
CH06 NBClus.GE.1&& NBTOF.GE.1&& NLtrk.GE.2
CH09 NClus.GE.1&& BEtot_H Neutral
CH12 NClus.GE.2&& Etot_M


Table3.Trigger menu for 2018 $J/\psi$ data taking.

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B.Data sample for trigger study
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B.Data sample for trigger study

To study the trigger efficiency, we took two dedicated runs (run 56199 and run 56200) where a single trigger was enabled in order to determine the efficiencies of all trigger conditions using a set of independent conditions. The corresponding trigger menus are shown in Table 4.
Channel Run number
CH03 56199
CH12 56200


Table4.Trigger menu for the 2018 $J/\psi$ test runs.

III.CONTROL SAMPLE SELECTION
Control samples were selected from the 2018 $ J/\psi $ test runs (56199 and 56200). As widely used in BESIII physics analyses, only tracks with a polar angle $ \theta $ (defined relative to the positron beam direction) for which $ |\cos\theta| \leqslant 0.93 $ are taken into account. The barrel region is defined as $ |\cos\theta|<0.8 $, and the endcap region as $ 0.86<|\cos\theta|<0.92 $. The definitions of “barrel” and “endcap” vary slightly between the analysis definitions and the trigger system, for which the “barrel” and “endcap” are decided by the structure of the sub-detector (such as MDC, EMC,...). The charged lepton or hadron selection defines good charged particle tracks as those with a distance of closest approach to the interaction point within 10 cm along the beam direction and 1 cm in the plane transverse to the beam direction. The control samples were selected similarly to those in Ref. [4] and are described in the following subsections.
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A.Bhabha event selection
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A.Bhabha event selection

To select Bhabha events, two EMC clusters are required to have an opening angle larger than $ 166^{\circ} $ and an energy difference within 10% of the center-of-mass energy:
$ \frac{|E_{\rm{emc}}(e^{+})+E_{\rm{emc}}(e^{-})-3.097|}{3.097}\leqslant 10{\text{%}} \; . $
Two oppositely charged good tracks in the MDC with an opening angle of more than $ 175^{\circ} $ are selected. Potential backgrounds have been investigated using an inclusive Monte Carlo (MC) sample, which consists of the production of the $ J/\psi $ resonance, and the continuum processes incorporated in $ KKMC $ [6], where the known decay modes were modeled with $ EVTGEN $ [7, 8] using branching fractions taken from the Particle Data Group [9], and the remaining unknown decays from the charmonium states were generated with $ LUNDCHARM $ [10, 11]. Using this sample, the impurity of the selected Bhabha sample is determined to be about $ 1.6\times 10^{-6} $.
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B.Dimuon event selection
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B.Dimuon event selection

To select dimuon candidate events, two oppositely charged good tracks are required to have an opening angle of at least $ 178^{\circ} $. In addition, we require that the momentum of each track be less than 2 GeV/c, and that the deposited energy in the EMC is less than 0.7 GeV. The total four-momentum $ (E/c, P_{x}, P_{y}, P_{z}) $ is required to fall into the range (2.8 to 3.3, $ - $0.1 to 0.1, $ - $0.1 to 0.1, $ - $0.2 to 0.2) GeV/c, assuming that both tracks are muons. By using the inclusive $ J/\psi $ decay MC sample, we investigate potential backgrounds, and find the background levels to be less than 0.4%.
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C.Charged hadronic event selection
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C.Charged hadronic event selection

For the hadron selection, two or more good tracks are required in the MDC. If there are exactly two tracks, the opening angle between them is required to be less than $ 170^{\circ} $ in order to suppress Bhabha and dimuon backgrounds.
IV.TRIGGER EFFICIENCY DETERMINATION
All of the 2018 $ J/\psi $ data (runs 53207–56520) available were taken using the same trigger conditions, and the main challenge in the efficiency determination is to reduce any bias to a minimum. Thus we use the two test runs triggered by independent trigger channels (Table 4) to determine the trigger efficiencies. It should be noted that since they cannot be used by themselves for the trigger efficiency study, the efficiencies of conditions/channels (Tables 5 and 6) related to “NClus.GE.2” and “Etot_M” are investigated from run 56199, and “NBTOF.GE.2” and “NLTrk.GE.2” are investigated from run 56200, respectively.
GTL Condition Bhabha Dimuon 2-prong 4-prong
Barrel Endcap Barrel Endcap
EMC 0 NClus.GE.1 100.00 100.00$^{+0.00}_{-0.41}$ 99.93$\pm$0.01 94.74$^{+4.35}_{-11.09}$ 99.64$\pm$0.01 99.97
1 NClus.GE.2 98.69$\pm$0.03 98.20$^{+0.62}_{-0.87}$ 95.14$\pm$0.08 84.21$^{+8.47}_{-13.01}$ 98.01$^{+0.03}_{-0.02}$ 99.63$^{+0.01}_{-0.02}$
7 BEtot_H 100.00 0.17$\pm$0.02 0.68$\pm$0.03 4.81$^{+2.06}_{-3.12}$ 89.88$\pm$0.04 93.25 $^{+0.03}_{-0.04}$
9 Etot_L 100.00 100.00$^{+0.00}_{-0.41}$ 99.82$\pm$0.01 100.00$^{+0.00}_{-9.24}$ 99.63$\pm$0.01 99.99
10 Etot_M 100.00 100.00$^{+0.00}_{-0.41}$ 10.25$\pm$0.11 0.00$^{+0.09}_{-0.00}$ 97.01$\pm$0.03 99.44$\pm$0.02
12 NBClus.GE.1 100.00 0.99$\pm$0.01 99.93$\pm$0.01 0.00$^{+0.09}_{-0.00}$ 99.34$\pm$0.01 99.90$\pm$0.01
13 NEClus.GE.1 0.94$\pm$0.02 100.00$^{+0.00}_{-0.41}$ 1.68$^{+0.04}_{-0.05}$ 94.74$^{+4.35}_{-11.09}$ 36.93$\pm$0.06 41.85$\pm$0.07

TOF 17 BTOF_BB 98.81$\pm$0.01 0.62$^{+0.02}_{-0.03}$ 99.98$\pm$0.01 0.00$^{+0.02}_{-0.00}$ 57.21$\pm$0.06 83.21$\pm$0.05
19 NETOF.GE.1 61.98$\pm$0.09 99.90$^{+0.00}_{-0.01}$ 60.08$\pm$0.17 100.00$^{+0.00}_{-2.14}$ 74.69$^{+0.05}_{-0.06}$ 77.87$\pm$0.06
20 NBTOF.GE.2 99.69$^{+0.01}_{-0.02}$ 3.69$\pm$0.06 99.89$^{+0.04}_{-0.06}$ 7.06$^{+2.76}_{-3.99}$ 87.81$^{+0.05}_{-0.06}$ 99.04$\pm$0.02
21 NBTOF.GE.1 100.00 41.89$\pm$0.14 100.00 36.47$^{+5.60}_{-5.95}$ 99.63$\pm$0.01 99.96

MDC 38 STrk_BB 99.93$^{+0.00}_{-0.01}$ 99.95$\pm$0.01 99.95$\pm$0.01 100.00$^{+0.00}_{-1.75}$ 46.62$\pm$0.06 83.01$^{+0.05}_{-0.06}$
42 LTrk_BB 99.91$^{+0.00}_{-0.01}$ 6.96$^{+0.07}_{-0.08}$ 99.95$^{+0.01}_{-0.02}$ 11.54$^{+4.03}_{-3.19}$ 37.34$\pm$0.06 76.21$\pm$0.06
44 NLTrk.GE.2 99.90$^{+0.00}_{-0.01} $ 21.74$\pm$0.12 99.87$^{+0.05}_{-0.06}$ 18.82$^{+5.22}_{-4.39}$ 93.68$\pm$0.05 99.86$\pm$0.02
45 NLTrk.GE.1 100.00 38.92$^{+0.13}_{-0.14}$ 100.00 30.59$^{+5.80}_{-5.30}$ 99.67$\pm$0.01 99.98


Table5.Trigger condition efficiencies (in %) (Note: The relative uncertainties of the items with no uncertainties indicated are less than 0.01%).

Channel Bhabha Dimuon 2-prong 4-prong
Barrel Endcap Barrel Endcap
CH01 0.65$ \pm $0.02 99.10$ ^{+0.43}_{-0.70} $ 0.63$ \pm $0.03 99.04$ ^{+0.96}_{-11.09} $ 15.88$ \pm $0.04 31.30$ ^{+0.03}_{-0.05} $
CH02 99.60$ \pm $ 0.02 0.03$ \pm $0.01 99.76$ ^{+0.06}_{-0.08} $ 1.18$ ^{+0.85}_{-0.78} $ 84.88$ \pm $0.06 98.97$ \pm $0.02
CH04 99.73$ \pm $ 0.01 0.06$ \pm $0.01 99.92$ \pm $0.01 0.00$ ^{+0.02}_{-0.00} $ 29.15$ \pm $0.05 67.36$ \pm $0.07
CH05 100.00 17.45$ \pm $0.11 99.82$ \pm $0.01 9.41$ ^{+2.32}_{-1.69} $ 99.04$ \pm $0.01 99.94
CH06 99.90$ \pm $0.01 0.15$ ^{+0.01}_{-0.02} $ 99.87$ ^{+0.04}_{-0.06} $ 2.35$ ^{+1.02}_{-0.72} $ 93.22$ ^{+0.05}_{-0.06} $ 99.78$ \pm $0.01
CH09 100.00 0.17$ \pm $0.01 0.68$ \pm $0.03 5.88$ ^{+2.79}_{-1.52} $ 89.85$ \pm $0.04 93.23$ \pm $0.04
CH12 98.69$ \pm $0.03 98.20$ ^{+0.62}_{-0.87} $ 9.79$ \pm $0.12 0.00$ ^{+0.09}_{-0.00} $ 96.42$ ^{+0.04}_{-0.03} $ 99.22$ \pm $0.02

Barrel Charged 100.00$ ^{+0.00}_{-0.02} $ 17.45$ ^{+6.61}_{-6.91} $ 99.95$ ^{+0.05}_{-0.10} $ 9.41$ ^{+8.25}_{-7.06} $ 99.04$ \pm $0.19 99.94$ ^{+0.06}_{-0.11} $
Endcap Charged 0.65$ \pm $0.02 99.10$ ^{+0.43}_{-0.70} $ 0.63$ \pm $0.03 99.04$ ^{+0.96}_{-11.09} $ 15.88$ \pm $0.04 31.30$ ^{+0.03}_{-0.05} $
Neutral 100.00$ ^{+0.00}_{-0.03} $ 98.20$ ^{+1.80}_{-5.84} $ 9.81$ \pm $0.45 5.88$ ^{+2.79}_{-1.52} $ 96.71$ ^{+0.06}_{-0.05} $ 99.32$ \pm $0.05

Total 100.00 99.99$ ^{+0.01}_{-0.04} $ 99.96$ ^{+0.04}_{-0.09} $ 99.33$ ^{+0.67}_{-9.46} $ 99.97$ \pm $0.01 100.00$ ^{+0.00}_{-0.01} $


Table6.Global trigger efficiencies (in %) (Note: The relative uncertainties of the items with no uncertainties given are less than 0.01%).

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A.Determination of trigger efficiencies
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A.Determination of trigger efficiencies

The trigger efficiency for each trigger condition/trigger channel ($ \varepsilon_{\rm{cond}}{\rm{./ch}} $) can be calculated using
${\varepsilon _{{\rm{cond}}{\rm{./ch}}}} = \frac{{N\rm(sel,\;trig.condition/channel)}}{{{N_{{\rm{sel}}}}}}\;,$
where “N” stands for the number of events, the label “sel” for events passing the physics selection, and “trig.condition/channel” for events in which the trigger condition/channel under study is active. The efficiencies of the trigger conditions which have been used for the 2018 $ J/\psi $ data taking are listed in Table 5. The Clopper-Pearson method [12, 13] has been used to estimate the confidence interval at the confidence level of $ 1-\alpha = 0.6827 (1\sigma) $. It should be noted that the number of prongs for hadronic events refers to the number of charged tracks in the full detector, not only in the barrel or endcap.
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B.Determination of trigger channel efficiencies
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B.Determination of trigger channel efficiencies

The efficiency of the trigger channels can be determined similar to the efficiency of the trigger conditions if a fully independent trigger channel exists. Otherwise, a mathematical combination of the condition efficiencies has to be performed. By considering the three almost independent groups of channels shown in Table 3, we can obtain the trigger channel efficiencies for 2018 $ J/\psi $ data taking as follows:
$ \varepsilon_{\rm{final}} = g_{1}+g_{2}+g_{3}-(g_{1}g_{2}+g_{1}g_{3}+g_{2}g_{3})+ g_{1}g_{2}g_{3}, $
where $ g_{n} $ is the efficiency of the $n^{\rm th}$ group of trigger channels.
The logical relationship between trigger channels (Table 3) is “or”, and in each trigger channel, the relationship between trigger conditions is “and”, so the efficiencies for the groups of trigger channels are the sum of all efficiencies of the channels in question with the overlap of the channels subtracted. The efficiencies of the groups of trigger channels can be calculated as:
$ \begin{array}{l} g_{1} = c_1 ,\quad g_{2} = A-B+C-D ,\quad g_{3} = E-F \end{array} $
and,
$ \begin{aligned}[b] A =& c_2+c_4+c_5+c_6 \\ B =& c_2\cdot P(4|2)+c_2\cdot P(5|2)+c_2\cdot P(6|2)+c_4\cdot P(5|4)\\&+c_6\cdot P(4|6)+c_6\cdot P(5|6) \\ C =& c_2\cdot P(4,5|2)+c_2\cdot P(4,6|2)+c_2\cdot P(5,6|2)+c_6\cdot P(4,5|6)\\ D =& c_2\cdot P(4,5,6|2), \quad E = c_9+c_{12} ,\quad F = c_9\cdot P(12|9), \end{aligned} $
where A and E are the sum of trigger channel efficiencies in the group, B, D and F are the overlap efficiencies for double-counting parts in A and E, C is the efficiency double-counted in B and D, $ c_{n} $ is the efficiency of the $n^{\rm th}$ channel, and $ P(n,\ldots|m) $ is a conditional probability, $ i.e. $ how many events of condition $ (n,\ldots) $ are involved in condition m, which is the overlap/correlations if the trigger channels are not independent of each other in the same group.
Using the combination methods outlined above, the overall efficiencies of the trigger channels and global trigger efficiencies are given in Table 6.
V.SUMMARY
The BESIII trigger system is a fundamental tool for the successful collection of data for physics analyses. With a dedicated data sample collected at the $ J/\psi $ peak, the trigger efficiencies for various physics channels were determined, and found to be close to 100% for most physics cases with small uncertainties. This conclusion is similar to that found by the trigger study for the 2009 run [4], showing that there has been no significant degradation in almost a decade of running. As the trigger menu studied here has been used for all data taking since 2012, the results of this study apply to all respective data samples. For most physics channels, the efficiency of the full trigger menu approaches 100% and can be neglected in physics analyses.
ACKNOWLEDGEMENTS
The BESIII collaboration thanks the staff of BEPCII and the IHEP Computing Center for their strong support.
相关话题/Study BESIII trigger