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

Tables(6)

Get Citation
M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. Gao, Y. Gao, Y. G. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, H Hüsken, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. K. Li, Lei Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Z. Y. Li, H. Liang, H. Liang, H. Liang, Y. F. Liang, Y. T. Liang, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, T. Y. Qi, S. Qian, W.-B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, P. P. Su, F. F. Sui, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. Q. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, Shulei Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou and J. H. Zou. Study of BESIII Trigger Efficiencies with the 2018 J/ψ Data[J]. Chinese Physics C. doi: 10.1088/1674-1137/abcfab
M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. Gao, Y. Gao, Y. G. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, H Hüsken, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. K. Li, Lei Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Z. Y. Li, H. Liang, H. Liang, H. Liang, Y. F. Liang, Y. T. Liang, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, T. Y. Qi, S. Qian, W.-B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, P. P. Su, F. F. Sui, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. Q. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, Shulei Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou and J. H. Zou. Study of BESIII Trigger Efficiencies with the 2018 J/ψ Data[J]. Chinese Physics C.  doi: 10.1088/1674-1137/abcfab shu
Milestone
Received: 2020-09-29
Article Metric

Article Views(124)
PDF Downloads(17)
Cited by(0)
Policy on re-use
To reuse of Open Access content published by CPC, for content published under the terms of the Creative Commons Attribution 3.0 license (“CC CY”), the users don’t need to request permission to copy, distribute and display the final published version of the article and to create derivative works, subject to appropriate attribution.
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Email This Article

Title:
Email:

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

  • 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

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.

    HTML

    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

      Table 1.  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

      Table 2.  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

      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

      Table 3.  Trigger menu for 2018 $J/\psi$ data taking.

    • 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

      Table 4.  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.

    • 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} $.

    • 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%.

    • 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

      Table 5.  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} $

      Table 6.  Global trigger efficiencies (in %) (Note: The relative uncertainties of the items with no uncertainties given are less than 0.01%).

    • 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.

    • 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.

Reference (13)

目录

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return