Measurements of electromagnetic form factors in the time-like region using the untagged initial-state radiation technique
M. Ablikim1, M. N. Achasov4,b, P. Adlarson75, O. Afedulidis3, X. C. Ai80, R. Aliberti35, A. Amoroso74A,74C, Q. An71,58, Y. Bai57, O. Bakina36, I. Balossino29A, Y. Ban46,g, H.-R. Bao63, V. Batozskaya1,44, K. Begzsuren32, N. Berger35, M. Berlowski44, M. Bertani28A, D. Bettoni29A, F. Bianchi74A,74C, E. Bianco74A,74C, A. Bortone74A,74C, I. Boyko36, R. A. Briere5, A. Brueggemann68, H. Cai76, X. Cai1,58, A. Calcaterra28A, G. F. Cao1,63, N. Cao1,63, S. A. Cetin62A, J. F. Chang1,58, W. L. Chang1,63, G. R. Che43, G. Chelkov36,a, C. Chen43, C. H. Chen9, Chao Chen55, G. Chen1, H. S. Chen1,63, M. L. Chen1,58,63, S. J. Chen42, S. L. Chen45, S. M. Chen61, T. Chen1,63, X. R. Chen31,63, X. T. Chen1,63, Y. B. Chen1,58, Y. Q. Chen34, Z. J. Chen25,h, Z. Y. Chen1,63, S. K. Choi10A, X. Chu43, G. Cibinetto29A, F. Cossio74C, J. J. Cui50, H. L. Dai1,58, J. P. Dai78, A. Dbeyssi18, R. E. de Boer3, D. Dedovich36, C. Q. Deng72, Z. Y. Deng1, A. Denig35, I. Denysenko36, M. Destefanis74A,74C, F. De Mori74A,74C, B. Ding66,1, X. X. Ding46,g, Y. Ding34, Y. Ding40, J. Dong1,58, L. Y. Dong1,63, M. Y. Dong1,58,63, X. Dong76, M. C. Du1, S. X. Du80, Z. H. Duan42, P. Egorov36,a, Y. H. Fan45, J. Fang1,58, J. Fang59, S. S. Fang1,63, W. X. Fang1, Y. Fang1, Y. Q. Fang1,58, R. Farinelli29A, L. Fava74B,74C, F. Feldbauer3, G. Felici28A, C. Q. Feng71,58, J. H. Feng59, Y. T. Feng71,58, K. Fischer69, M. Fritsch3, C. D. Fu1, J. L. Fu63, Y. W. Fu1, H. Gao63, Y. N. Gao46,g, Yang Gao71,58, S. Garbolino74C, I. Garzia29A,29B, L. Ge80, P. T. Ge76, Z. W. Ge42, C. Geng59, E. M. Gersabeck67, A. Gilman69, K. Goetzen13, L. Gong40, W. X. Gong1,58, W. Gradl35, S. Gramigna29A,29B, M. Greco74A,74C, M. H. Gu1,58, Y. T. Gu15, C. Y. Guan1,63, Z. L. Guan22, A. Q. Guo31,63, L. B. Guo41, M. J. Guo50, R. P. Guo49, Y. P. Guo12,f, A. Guskov36,a, J. Gutierrez27, K. L. Han63, T. T. Han1, X. Q. Hao19, F. A. Harris65, K. K. He55, K. L. He1,63, F. H. Heinsius3, C. H. Heinz35, Y. K. Heng1,58,63, C. Herold60, T. Holtmann3, P. C. Hong12,f, G. Y. Hou1,63, X. T. Hou1,63, Y. R. Hou63, Z. L. Hou1, B. Y. Hu59, H. M. Hu1,63, J. F. Hu56,i, T. Hu1,58,63, Y. Hu1, G. S. Huang71,58, K. X. Huang59, L. Q. Huang31,63, X. T. Huang50, Y. P. Huang1, T. Hussain73, F. Hölzken3, N Hüsken27,35, N. in der Wiesche68, M. Irshad71,58, J. Jackson27, S. Janchiv32, J. H. Jeong10A, Q. Ji1, Q. P. Ji19, W. Ji1,63, X. B. Ji1,63, X. L. Ji1,58, Y. Y. Ji50, X. Q. Jia50, Z. K. Jia71,58, D. Jiang1,63, H. B. Jiang76, P. C. Jiang46,g, S. S. Jiang39, T. J. Jiang16, X. S. Jiang1,58,63, Y. Jiang63, J. B. Jiao50, J. K. Jiao34, Z. Jiao23, S. Jin42, Y. Jin66, M. Q. Jing1,63, X. M. Jing63, T. Johansson75, S. Kabana33, N. Kalantar-Nayestanaki64, X. L. Kang9, X. S. Kang40, M. Kavatsyuk64, B. C. Ke80, V. Khachatryan27, A. Khoukaz68, R. Kiuchi1, O. B. Kolcu62A, B. Kopf3, M. Kuessner3, X. Kui1,63, N. Kumar26, A. Kupsc44,75, W. Kühn37, J. J. Lane67, P. Larin18, L. Lavezzi74A,74C, T. T. Lei71,58, Z. H. Lei71,58, H. Leithoff35, M. Lellmann35, T. Lenz35, C. Li47, C. Li43, C. H. Li39, Cheng Li71,58, D. M. Li80, F. Li1,58, G. Li1, H. Li71,58, H. B. Li1,63, H. J. Li19, H. N. Li56,i, Hui Li43, J. R. Li61, J. S. Li59, Ke Li1, L. J Li1,63, L. K. Li1, Lei Li48, M. H. Li43, P. R. Li38,k, Q. M. Li1,63, Q. X. Li50, R. Li17,31, S. X. Li12, T. Li50, W. D. Li1,63, W. G. Li1, X. Li1,63, X. H. Li71,58, X. L. Li50, Xiaoyu Li1,63, Y. G. Li46,g, Z. J. Li59, Z. X. Li15, C. Liang42, H. Liang71,58, H. Liang1,63, Y. F. Liang54, Y. T. Liang31,63, G. R. Liao14, L. Z. Liao50, Y. P. Liao1,63, J. Libby26, A. Limphirat60, D. X. Lin31,63, T. Lin1, B. J. Liu1, B. X. Liu76, C. Liu34, C. X. Liu1, F. H. Liu53, Fang Liu1, Feng Liu6, G. M. Liu56,i, H. Liu38,j,k, H. B. Liu15, H. M. Liu1,63, Huanhuan Liu1, Huihui Liu21, J. B. Liu71,58, J. Y. Liu1,63, K. Liu38,j,k, K. Y. Liu40, Ke Liu22, L. Liu71,58, L. C. Liu43, Lu Liu43, M. H. Liu12,f, P. L. Liu1, Q. Liu63, S. B. Liu71,58, T. Liu12,f, W. K. Liu43, W. M. Liu71,58, X. Liu38,j,k, X. Liu39, Y. Liu38,j,k, Y. Liu80, Y. B. Liu43, Z. A. Liu1,58,63, Z. D. Liu9, Z. Q. Liu50, X. C. Lou1,58,63, F. X. Lu59, H. J. Lu23, J. G. Lu1,58, X. L. Lu1, Y. Lu7, Y. P. Lu1,58, Z. H. Lu1,63, C. L. Luo41, M. X. Luo79, T. Luo12,f, X. L. Luo1,58, X. R. Lyu63, Y. F. Lyu43, F. C. Ma40, H. Ma78, H. L. Ma1, J. L. Ma1,63, L. L. Ma50, M. M. Ma1,63, Q. M. Ma1, R. Q. Ma1,63, X. T. Ma1,63, X. Y. Ma1,58, Y. Ma46,g, Y. M. Ma31, F. E. Maas18, M. Maggiora74A,74C, S. Malde69, A. Mangoni28B, Y. J. Mao46,g, Z. P. Mao1, S. Marcello74A,74C, Z. X. Meng66, J. G. Messchendorp13,64, G. Mezzadri29A, H. Miao1,63, T. J. Min42, R. E. Mitchell27, X. H. Mo1,58,63, B. Moses27, N. Yu. Muchnoi4,b, J. Muskalla35, Y. Nefedov36, F. Nerling18,d, I. B. Nikolaev4,b, Z. Ning1,58, S. Nisar11,l, Q. L. Niu38,j,k, W. D. Niu55, Y. Niu 50, S. L. Olsen63, Q. Ouyang1,58,63, S. Pacetti28B,28C, X. Pan55, Y. Pan57, A. Pathak34, P. Patteri28A, Y. P. Pei71,58, M. Pelizaeus3, H. P. Peng71,58, Y. Y. Peng38,j,k, K. Peters13,d, J. L. Ping41, R. G. Ping1,63, S. Plura35, V. Prasad33, F. Z. Qi1, H. Qi71,58, H. R. Qi61, M. Qi42, T. Y. Qi12,f, S. Qian1,58, W. B. Qian63, C. F. Qiao63, X. K. Qiao80, J. J. Qin72, L. Q. Qin14, X. S. Qin50, Z. H. Qin1,58, J. F. Qiu1, S. Q. Qu61, Z. H. Qu72, C. F. Redmer35, K. J. Ren39, A. Rivetti74C, M. Rolo74C, G. Rong1,63, Ch. Rosner18, S. N. Ruan43, N. Salone44, A. Sarantsev36,c, Y. Schelhaas35, K. Schoenning75, M. Scodeggio29A, K. Y. Shan12,f, W. Shan24, X. Y. Shan71,58, Z. J Shang38,j,k, J. F. Shangguan55, L. G. Shao1,63, M. Shao71,58, C. P. Shen12,f, H. F. Shen1,8, W. H. Shen63, X. Y. Shen1,63, B. A. Shi63, H. C. Shi71,58, J. L. Shi12, J. Y. Shi1, Q. Q. Shi55, R. S. Shi1,63, S. Y. Shi72, X. Shi1,58, J. J. Song19, T. Z. Song59, W. M. Song34,1, Y. J. Song12, Y. X. Song46,g,m, S. Sosio74A,74C, S. Spataro74A,74C, F. Stieler35, Y. J. Su63, G. B. Sun76, G. X. Sun1, H. Sun63, H. K. Sun1, J. F. Sun19, K. Sun61, L. Sun76, S. S. Sun1,63, T. Sun51,e, W. Y. Sun34, Y. Sun9, Y. J. Sun71,58, Y. Z. Sun1, Z. Q. Sun1,63, Z. T. Sun50, C. J. Tang54, G. Y. Tang1, J. Tang59, Y. A. Tang76, L. Y. Tao72, Q. T. Tao25,h, M. Tat69, J. X. Teng71,58, V. Thoren75, W. H. Tian59, Y. Tian31,63, Z. F. Tian76, I. Uman62B, Y. Wan55, S. J. Wang 50, B. Wang1, B. L. Wang63, Bo Wang71,58, D. Y. Wang46,g, F. Wang72, H. J. Wang38,j,k, J. P. Wang 50, K. Wang1,58, L. L. Wang1, M. Wang50, Meng Wang1,63, N. Y. Wang63, S. Wang38,j,k, S. Wang12,f, T. Wang12,f, T. J. Wang43, W. Wang59, W. Wang72, W. P. Wang71,58, X. Wang46,g, X. F. Wang38,j,k, X. J. Wang39, X. L. Wang12,f, X. N. Wang1, Y. Wang61, Y. D. Wang45, Y. F. Wang1,58,63, Y. L. Wang19, Y. N. Wang45, Y. Q. Wang1, Yaqian Wang17, Yi Wang61, Z. Wang1,58, Z. L. Wang72, Z. Y. Wang1,63, Ziyi Wang63, D. Wei70, D. H. Wei14, F. Weidner68, S. P. Wen1, Y. R. Wen39, U. Wiedner3, G. Wilkinson69, M. Wolke75, L. Wollenberg3, C. Wu39, J. F. Wu1,8, L. H. Wu1, L. J. Wu1,63, X. Wu12,f, X. H. Wu34, Y. Wu71, Y. H. Wu55, Y. J. Wu31, Z. Wu1,58, L. Xia71,58, X. M. Xian39, B. H. Xiang1,63, T. Xiang46,g, D. Xiao38,j,k, G. Y. Xiao42, X. Xiao59, S. Y. Xiao1, Y. L. Xiao12,f, Z. J. Xiao41, C. Xie42, X. H. Xie46,g, Y. Xie50, Y. G. Xie1,58, Y. H. Xie6, Z. P. Xie71,58, T. Y. Xing1,63, C. F. Xu1,63, C. J. Xu59, G. F. Xu1, H. Y. Xu66, Q. J. Xu16, Q. N. Xu30, W. Xu1, W. L. Xu66, X. P. Xu55, Y. C. Xu77, Z. P. Xu42, Z. S. Xu63, F. Yan12,f, L. Yan12,f, W. B. Yan71,58, W. C. Yan80, X. Q. Yan1, H. J. Yang51,e, H. L. Yang34, H. X. Yang1, Tao Yang1, Y. Yang12,f, Y. F. Yang43, Y. X. Yang1,63, Yifan Yang1,63, Z. W. Yang38,j,k, Z. P. Yao50, M. Ye1,58, M. H. Ye8, J. H. Yin1, Z. Y. You59, B. X. Yu1,58,63, C. X. Yu43, G. Yu1,63, J. S. Yu25,h, T. Yu72, X. D. Yu46,g, Y. C. Yu80, C. Z. Yuan1,63, J. Yuan34, L. Yuan2, S. C. Yuan1, Y. Yuan1,63, Z. Y. Yuan59, C. X. Yue39, A. A. Zafar73, F. R. Zeng50, S. H. Zeng72, X. Zeng12,f, Y. Zeng25,h, Y. J. Zeng59, Y. J. Zeng1,63, X. Y. Zhai34, Y. C. Zhai50, Y. H. Zhan59, A. Q. Zhang1,63, B. L. Zhang1,63, B. X. Zhang1, D. H. Zhang43, G. Y. Zhang19, H. Zhang71, H. C. Zhang1,58,63, H. H. Zhang59, H. H. Zhang34, H. Q. Zhang1,58,63, H. Y. Zhang1,58, J. Zhang80, J. Zhang59, J. J. Zhang52, J. L. Zhang20, J. Q. Zhang41, J. W. Zhang1,58,63, J. X. Zhang38,j,k, J. Y. Zhang1, J. Z. Zhang1,63, Jianyu Zhang63, L. M. Zhang61, Lei Zhang42, P. Zhang1,63, Q. Y. Zhang39,80, R. Y Zhang38,j,k, Shuihan Zhang1,63, Shulei Zhang25,h, X. D. Zhang45, X. M. Zhang1, X. Y. Zhang50, Y. Zhang72, Y. T. Zhang80, Y. H. Zhang1,58, Y. M. Zhang39, Yan Zhang71,58, Yao Zhang1, Z. D. Zhang1, Z. H. Zhang1, Z. L. Zhang34, Z. Y. Zhang76, Z. Y. Zhang43, G. Zhao1, J. Y. Zhao1,63, J. Z. Zhao1,58, Lei Zhao71,58, Ling Zhao1, M. G. Zhao43, R. P. Zhao63, S. J. Zhao80, Y. B. Zhao1,58, Y. X. Zhao31,63, Z. G. Zhao71,58, A. Zhemchugov36,a, B. Zheng72, J. P. Zheng1,58, W. J. Zheng1,63, Y. H. Zheng63, B. Zhong41, X. Zhong59, H. Zhou50, J. Y. Zhou34, L. P. Zhou1,63, X. Zhou76, X. K. Zhou6, X. R. Zhou71,58, X. Y. Zhou39, Y. Z. Zhou12,f, J. Zhu43, K. Zhu1, K. J. Zhu1,58,63, L. Zhu34, L. X. Zhu63, S. H. Zhu70, S. Q. Zhu42, T. J. Zhu12,f, W. J. Zhu12,f, Y. C. Zhu71,58, Z. A. Zhu1,63, J. H. Zou1, J. Zu71,58
(BESIII Collaboration)
1 Institute of High Energy Physics, Beijing 100049, People’s Republic of China
2 Beihang University, Beijing 100191, People’s Republic of China
3 Bochum Ruhr-University, D-44780 Bochum, Germany
4 Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
5 Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
6 Central China Normal University, Wuhan 430079, People’s Republic of China
7 Central South University, Changsha 410083, People’s Republic of China
8 China Center of Advanced Science and Technology, Beijing 100190, People’s Republic of China
9 China University of Geosciences, Wuhan 430074, People’s Republic of China
10 Chung-Ang University, Seoul, 06974, Republic of Korea
11 COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
12 Fudan University, Shanghai 200433, People’s Republic of China
13 GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
14 Guangxi Normal University, Guilin 541004, People’s Republic of China
15 Guangxi University, Nanning 530004, People’s Republic of China
16 Hangzhou Normal University, Hangzhou 310036, People’s Republic of China
17 Hebei University, Baoding 071002, People’s Republic of China
18 Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
19 Henan Normal University, Xinxiang 453007, People’s Republic of China
20 Henan University, Kaifeng 475004, People’s Republic of China
21 Henan University of Science and Technology, Luoyang 471003, People’s Republic of China
22 Henan University of Technology, Zhengzhou 450001, People’s Republic of China
23 Huangshan College, Huangshan 245000, People’s Republic of China
24 Hunan Normal University, Changsha 410081, People’s Republic of China
25 Hunan University, Changsha 410082, People’s Republic of China
26 Indian Institute of Technology Madras, Chennai 600036, India
27 Indiana University, Bloomington, Indiana 47405, USA
28 INFN Laboratori Nazionali di Frascati , (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
29 INFN Sezione di Ferrara, (A)INFN Sezione di Ferrara, I-44122, Ferrara, Italy; (B)University of Ferrara, I-44122, Ferrara, Italy
30 Inner Mongolia University, Hohhot 010021, People’s Republic of China
31 Institute of Modern Physics, Lanzhou 730000, People’s Republic of China
32 Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
33 Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
34 Jilin University, Changchun 130012, People’s Republic of China
35 Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
36 Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
37 Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
38 Lanzhou University, Lanzhou 730000, People’s Republic of China
39 Liaoning Normal University, Dalian 116029, People’s Republic of China
40 Liaoning University, Shenyang 110036, People’s Republic of China
41 Nanjing Normal University, Nanjing 210023, People’s Republic of China
42 Nanjing University, Nanjing 210093, People’s Republic of China
43 Nankai University, Tianjin 300071, People’s Republic of China
44 National Centre for Nuclear Research, Warsaw 02-093, Poland
45 North China Electric Power University, Beijing 102206, People’s Republic of China
46 Peking University, Beijing 100871, People’s Republic of China
47 Qufu Normal University, Qufu 273165, People’s Republic of China
48 Renmin University of China, Beijing 100872, People’s Republic of China
49 Shandong Normal University, Jinan 250014, People’s Republic of China
50 Shandong University, Jinan 250100, People’s Republic of China
51 Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
52 Shanxi Normal University, Linfen 041004, People’s Republic of China
53 Shanxi University, Taiyuan 030006, People’s Republic of China
54 Sichuan University, Chengdu 610064, People’s Republic of China
55 Soochow University, Suzhou 215006, People’s Republic of China
56 South China Normal University, Guangzhou 510006, People’s Republic of China
57 Southeast University, Nanjing 211100, People’s Republic of China
58 State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People’s Republic of China
59 Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
60 Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
61 Tsinghua University, Beijing 100084, People’s Republic of China
62 Turkish Accelerator Center Particle Factory Group, (A)Istinye University, 34010, Istanbul, Turkey; (B)Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
63 University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
64 University of Groningen, NL-9747 AA Groningen, The Netherlands
65 University of Hawaii, Honolulu, Hawaii 96822, USA
66 University of Jinan, Jinan 250022, People’s Republic of China
67 University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
68 University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
69 University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
70 University of Science and Technology Liaoning, Anshan 114051, People’s Republic of China
71 University of Science and Technology of China, Hefei 230026, People’s Republic of China
72 University of South China, Hengyang 421001, People’s Republic of China
73 University of the Punjab, Lahore-54590, Pakistan
74 University of Turin and INFN, (A)University of Turin, I-10125, Turin, Italy; (B)University of Eastern Piedmont, I-15121, Alessandria, Italy; (C)INFN, I-10125, Turin, Italy
75 Uppsala University, Box 516, SE-75120 Uppsala, Sweden
76 Wuhan University, Wuhan 430072, People’s Republic of China
77 Yantai University, Yantai 264005, People’s Republic of China
78 Yunnan University, Kunming 650500, People’s Republic of China
79 Zhejiang University, Hangzhou 310027, People’s Republic of China
80 Zhengzhou University, Zhengzhou 450001, People’s Republic of China
a Also at the Moscow Institute of Physics and Technology, Moscow 141700, Russia
b Also at the Novosibirsk State University, Novosibirsk, 630090, Russia
c Also at the NRC ”Kurchatov Institute”, PNPI, 188300, Gatchina, Russia
d Also at Goethe University Frankfurt, 60323 Frankfurt am Main, Germany
e 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, People’s Republic of China
f Also at Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics, Fudan University, Shanghai 200443, People’s Republic of China
g Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, People’s Republic of China
h Also at School of Physics and Electronics, Hunan University, Changsha 410082, China
i Also at Guangdong Provincial Key Laboratory of Nuclear Science, Institute of Quantum Matter, South China Normal University, Guangzhou 510006, China
j Also at MOE Frontiers Science Center for Rare Isotopes, Lanzhou University, Lanzhou 730000, People’s Republic of China
k Also at Lanzhou Center for Theoretical Physics, Lanzhou University, Lanzhou 730000, People’s Republic of China
l Also at the Department of Mathematical Sciences, IBA, Karachi 75270, Pakistan
m Also at Ecole Polytechnique Federale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
Abstract
The process is studied from threshold up to 3.04 GeV/ via the initial-state radiation technique using data with an integrated luminosity of 12.0 fb-1, collected at center-of-mass energies between 3.773 and 4.258 GeV with the BESIII detector at the BEPCII collider.
The pair production cross sections and the effective form factors of are measured in eleven invariant mass intervals from threshold to 3.04 GeV/.
The results are consistent with the previous results from Belle and BESIII. Furthermore, the branching fractions of the decays and are determined and the obtained results are consistent with the previous results of BESIII.
I Introduction
The inner structure of baryons can be parameterized using electromagnetic form factors (EMFFs). For baryons with spin 1/2, assuming a vector-like current, there are two EMFFs, the magnetic and the electric form factors. Experimentally, these can be accessed in the space-like region by electron-baryon elastic scattering and in the time-like region by baryon pair production in electron-positron annihilation Geng:2008mf ; Brodsky:1974vy ; Green:2014xba .
Despite the fact that much work has been done on the EM structures of protons in both the space-like and time-like regions Qattan:2004ht ; Puckett:2011xg ; CLEO:2005tiu ; BaBar:2013ves ; CMD-3:2015fvi ; BESIII:2019hdp , experimental information regarding the EMFFs of hyperons remains limited.
The cross section for the process via one-photon exchange, where denotes a hyperon with spin 1/2, can be expressed in terms of and Cabibbo:1961sz :
(1)
where is the square of the center-of-mass (c.m.) energy, is the fine-structure constant, is the velocity of the final hyperon, , and is the mass of the hyperon. The Coulomb correction factor Arbuzov:2011ff00 ; Arbuzov:2011ff , accounting for the electromagnetic interaction of charged pointlike fermion pairs in the final state, is 1.0 for pairs of neutral hyperons and with for pairs of charged hyperons. The effective form factor (FF) BESIII:2015axk defined by
(2)
is proportional to the square root of the hyperon pair production cross section.
The cross section of the process near its production threshold has been measured by the BESIII experiment BESIII:2020uqk using the scan method. A non-zero threshold cross section was observed with a hint of an enhancement at 2.5 GeV. However, due to limited statistics, an unambiguous conclusion cannot be drawn.
In this paper, a new measurement of the pair production cross sections and the effective form factors of from the production threshold up to the invariant mass of at 3.04 GeV with the BESIII detector located at the BEPCII collider is presented. The measurement uses the initial-state radiation (ISR) process , where is a hard photon emitted from the initial pair and thus changes the effective c.m. energy of the collision. The differential cross section for the ISR process is largest when is emitted almost parallel to the beam axis, where it cannot be detected by BESIII. To benefit from the increased cross section, an untagged ISR measurement is performed.
The differential cross section for the process, integrated over the momentum and the ISR photon polar angle, reads Kuraev:1985hb :
(3)
where is the cross section for the process, is the momentum transfer of the virtual photon, its square equal to the invariant mass squared of , , and denotes the energy of the ISR photon in the c.m. system.
The function Druzhinin:2011qd
(4)
describes the probability for the emission of an ISR photon with energy fraction , where and is the mass of the electron.
II BESIII detector and Monte Carlo simulation
The BESIII detector BESIII:2009fln records symmetric collisions provided by the BEPCII storage ring BEPCII , which operates in the c.m. energy range from 2.0 to 4.95 GeV, with a peak luminosity of achieved at 3.773 GeV. BESIII has collected large data samples in this energy region BESIII:2020nme . The cylindrical core of the BESIII detector covers 93% of the full solid angle and consists of a helium-based multilayer drift chamber (MDC), a plastic scintillator time-of-flight system (TOF), and a CsI(Tl) electromagnetic calorimeter (EMC), which are all enclosed in a superconducting solenoidal magnet providing a 1.0 T magnetic field Huang:2022wuo . The solenoid is supported by an octagonal flux-return yoke with resistive plate counter based muon identification modules interleaved with steel. The charged-particle momentum resolution at 1 GeV/ is 0.5%, and resolution of the specific ionization energy loss () in the MDC is 6% for electrons from Bhabha scattering. The EMC measures photon energies with a resolution of 2.5% (5%) at 1 GeV in the barrel (end cap) region. The time resolution in the TOF barrel region is 68 ps, while that in the end cap region used to be 110 ps. The end cap TOF system was upgraded in 2015 using multi-gap resistive plate chamber technology, providing a time resolution of 60 ps BESIII:27a ; BESIII:28a ; Cao:2020ibk , which benefits 59.6% of the data used in this analysis.
The data sets used in this analysis are collected at twelve c.m. energies between 3.773 and 4.258 GeV and correspond to a total integrated luminosity of 12.0 fb-1BESIII:2023ioy . The individual data sets and the respective luminosities are listed in Table 1.
A Geant4-based GEANT4:2002zbu Monte Carlo (MC) simulation package is used to determine the detection efficiency, optimize event selection criteria, and estimate background contributions. For the data processing and analysis, the BESIII Offline Software System Asner:2009zza framework is used. The MC simulated samples of the signal channel () are generated with the ConExc generator Ping:2013jka .
The ConExc generator considers ISR processes using the radiator function at next-to-leading order accuracy including the vacuum polarization.
The cross section line-shape used for the generation of the signal MC samples is taken from Ref. BESIII:2020uqk . The ISR production of vector charmonium states (, ) is generated with BesEvtGenPing:2008zz using the VECTORISR model VECISR1 ; VECISR2 . The angular distributions of the in and decays are modeled according to experimental data BESIII:2020fqg .
Inclusive MC samples at and GeV are used to investigate possible background contamination. They consist of inclusive hadronic processes (, ) modeled with the LUARLWLund at GeV and KKMCJadach:1999vf ; KKMC1 at GeV. The dominant background channel, , is generated exclusively using the phase space ConExc generator.
Table 1: The c.m. energies and the integrated luminosities of each data set BESIII:2023ioy .
GeV
pb
3.773
2931.80
4.128
401.50
4.157
408.70
4.178
3189.00
4.189
526.70
4.199
526.00
4.209
517.10
4.219
514.60
4.226
1091.74
4.236
530.30
4.244
538.10
4.258
825.74
III Event selection and background analysis
To select the candidates for , the decays of and are reconstructed, while the is not detected.
The number of charged tracks is required to be two with a net charge of zero. These tracks are reconstructed in the MDC and required to have a polar angle within 0.93, where is defined with respect to the z-axis, which is the symmetry axis of the MDC.
Furthermore, the distance of closest approach of each charged track to the interaction point is required within 2 cm in the plane perpendicular to the beam and within 10 cm in the direction along the z-axis.
The two selected tracks are identified as one proton and one anti-proton by requiring , where are the probabilities for a track to be assigned to a certain hadron type, based on the information measured by the MDC and the time measurement in the TOF.
Photon candidates are reconstructed from isolated showers in the EMC. Each photon candidate is required to have a minimum energy of 25 MeV in the EMC barrel region () or 50 MeV in the end cap region (). To suppress electronic noise and showers unrelated to the event, the difference between the EMC time and the event start time is required to be within (0, 700) ns. At least four good photon candidates are required for each event.
The candidates are reconstructed from pairs of photons with invariant masses such that MeV/, where is the known mass taken from the Particle Data Group (PDG) ParticleDataGroup:2022pth . An asymmetrical mass window is used because the photon energy deposited in the EMC has a long tail on the low energy side. A one-constraint (1C) kinematic fit is performed on the photon pairs, constraining their invariant masses to the nominal mass.
The of this kinematic fit is required to be less than 25 to remove fake candidates. At least two reconstructed candidates per event are further required, where two candidates in an event don’t share the same photons.
The and candidates are built from the proton, anti-proton, and neutral pion candidates.
From all possible combinations, the neutral pion candidates yielding the smallest value of are assigned to the baryon decay.
Here, is the nominal mass of the hyperon ParticleDataGroup:2022pth .
According to the fit to the spectrum with a double Gaussian function, the signal events are expected to be within a mass range of [1.16, 1.21] GeV.
Figure 1: Distribution of versus for the events satisfying the selection criteria from all data sets.
The red box denotes the signal region and the black ones indicate the sideband regions.
To further suppress potential background events, the requirements of the ISR photon polar angle radians or radians, and GeV are imposed.
Here, in the c.m. frame is the opening angle between the momentum of the recoil against the system () and the beam direction. , where is the energy of the recoil against the system.
Figure 1 shows the distribution of versus for all data sets combined.
The red box denotes the signal region, which is defined by the mass window discussed above. The black boxes denote the sideband regions used to study and subtract the non-resonant background. For events in the signal region, is plotted in Fig. 2, after improving the mass resolution by applying the correction , where , , and are the measured invariant masses of the four hadrons and the (anti-)proton pion pairs, respectively. Throughout this paper, refers to .
Potential background sources are investigated by analyzing the inclusive MC samples at 3.773 and 4.178 GeV with the generic event type analysis tool TopoAna Zhou:2020ksj .
After applying the above selection criteria, two background contributions are found to
be insufficiently suppressed: the non- channels and the process .
The non- background contributions are estimated with the sideband method from the distributions, since the corresponding distributions based on the inclusive MC samples after excluding the contributions of channels containing pairs do not exhibit significant structures.
The two-dimensional (2D) sideband regions, shown in Fig. 1, are provided in Table 2.
The number of the non- background events is obtained by , where runs over the four black boxes shown in Fig. 1.
Table 2: Two-dimensional sideband regions on and as shown in Fig. 1.
BGi
[GeV]
[GeV]
BG1
[1.10, 1.15]
[1.22, 1.27]
BG2
[1.22, 1.27]
[1.22, 1.27]
BG3
[1.10, 1.15]
[1.10, 1.15]
BG4
[1.22, 1.27]
[1.10, 1.15]
Figure 2: The distribution for the events satisfying the selection criteria. The black dots with error bars are data combined from all data sets.
Events of are easily mistaken for signal events if one of the photons of the s is undetected.
The background contribution to the selected events is estimated by a data-driven approach using the sideband method.
To estimate this contribution, a sample of the events is selected from data using a similar procedure as described for the ISR production of , but reconstructing an additional candidate instead of a missing photon.
The signal and sideband regions are chosen in the same way as described for the signal process (shown in Fig. 1). The number of events of this sample is calculated by , where and are the numbers of events from the signal and the sideband regions of the sample, respectively.
The contribution from remaining background () among the signal candidates is determined by:
(5)
where and are the detection efficiencies of selecting the and candidates, respectively, from the MC samples.
Figure 3 shows the distribution from threshold up to 3.04 GeV for the events selected from all data sets in Table 1. The red and blue histograms indicate the background contributions due to non- channels and , respectively.
IV Cross section of and effective FFs
The cross section for the process is calculated from the distribution for each data set by
(6)
where = ()% and = ()% are the branching fractions of and ParticleDataGroup:2022pth , respectively. is the integrated luminosity, as listed in Table 1.
The effective ISR luminosity is calculated by Eq. (4).
is the detection efficiency determined using the signal MC samples as a function of , and combined as the average value weighted by the corresponding effective ISR luminosity. The is obtained from the distribution of data after subtracting background. The signal yields are extracted by counting the number of observed events in the signal region as shown in Fig. 3.
Figure 3: The distribution for the selected candidates. The black dots with error bars are combined data from all energy points. The red and blue histograms represent the non- and background events, respectively.
The spectrum of is divided into eleven mass intervals between the production threshold and 3.04 GeV, taking into account the mass resolution, which is smaller than fifth of the bin size.
Thus, the spectrum is not unfolded for detector resolution effects.
The measured cross sections and the effective FFs calculated by Eqs. (1) and (2) are listed in Table 3. The and are the average detection efficiency of all data sets weighted by the effective ISR luminosity and the total effective ISR luminosity, respectively. For the intervals of [2.379, 2.44] and [2.92, 2.98] GeV where fewer than ten signals are found, the upper limits of the signal yield at 90% confidence level are calculated using the profile likelihood method Lundberg:2009iu .
Table 3: The cross sections () and the effective FFs () for the process at all data sets. is the total number of signal events. is the average detection efficiency of all data sets weighted by the effective ISR luminosity. is the total effective ISR luminosity.
For and , the first and second uncertainties are statistical and systematic, respectively; for , the uncertainties are statistical only. The values in brackets for , and correspond to the upper limits at 90% confidence level.
[GeV]
[pb-1]
[pb]
2.379-2.44
2.7(6.8)
0.91
15.13
745(190)
14.10.5(22.7)
2.44-2.50
164
2.07
15.77
1905020
18.22.41.0
2.50-2.56
306
3.69
16.82
1873719
16.61.70.8
2.56-2.62
286
5.33
17.96
1122411
12.31.30.6
2.62-2.68
266
6.49
19.22
79188
10.21.20.5
2.68-2.74
205
7.24
20.62
52144
8.11.10.3
2.74-2.80
165
7.85
22.16
36103
6.71.00.3
2.80-2.86
134
8.19
23.90
2682
5.50.90.2
2.86-2.92
195
8.62
25.83
3382
6.50.80.2
2.92-2.98
(7.7)
8.96
28.01
0.1(11.7)
0.1(3.9)
2.98-3.04
116
9.23
30.50
1581
4.41.10.1
V systematic uncertainties
Several sources of systematic uncertainty are considered in the cross section measurement, including the tracking and PID efficiencies of charged tracks, the efficiency correction, the mass window, the and requirements, the background estimation, the angular distribution, the luminosity, and the branching fractions of intermediate states. The individual contributions are discussed below.
1.
Tracking and PID efficiencies:
The tracking and PID efficiency differences between data and MC simulation for the proton and anti-proton have been studied in different bins of transverse momentum and polar angle from the control samples of and BESIII:2021wkr . The differences averaged over the transverse momentum and polar angle of or of the signal MC samples are taken as the correction factors to calculate the nominal efficiencies. The systematic uncertainty is obtained by summing their relative uncertainties in different bins quadratically and is assigned to be 1.6% for each interval.
2.
reconstruction:
Based on the control samples of and , the efficiency differences between data and MC simulation are determined as a function of the momentum, BESIII:2021wkr . The systematic uncertainty is obtained by weighting the relative uncertainties according to the momentum distribution in each mass bin,
(7)
where is the number of candidates in the -th bin and is the total number of candidates, both in the signal MC sample. The systematic uncertainties of the reconstruction and are both 1.65%. Therefore, the total systematic uncertainty due to the reconstruction for is 3.3%.
3.
mass window and requirement:
The uncertainties due to the mass window and the requirement are estimated by studying the decay. The difference in the mass window (the requirement) between data and MC simulation which is 1.0(1.4)%, is taken as the systematic uncertainty.
4.
requirement:
The uncertainty due to the requirement is estimated by studying decay. The difference in the requirement between data and MC simulation which is 2.8%, is taken as the systematic uncertainty.
5.
Background estimation:
To estimate the uncertainties on the number of the non- background events, the 2D sideband regions are changed from [1.10,1.15] and [1.22,1.27] GeV to [1.095,1.145] and [1.225,1.275] GeV.
The resulting differences to the nominal result are taken as the systematic uncertainties.
The uncertainties of the background events are estimated by also changing the 2D sideband regions in the event selection, and are included in each interval. The total uncertainty of the background estimation is determined by the average of the uncertainty of all intervals. Thus, the total systematic uncertainty on the background estimation for each mass interval is assigned as 2.5% at 3.773 GeV and 1.1% at the other energy points.
6.
Angular distribution:
In this analysis, the signal MC samples are generated according to an homogeneous and isotropic phase space population, and the angular distribution of the pair, the spin correlation between and , and the polarization of the () decay are not taken into account. To estimate the uncertainty due to these factors, the signal MC samples with an angular amplitude including these effects are generated. The parametrization of the angular amplitude is the same as that in Ref. BESIII:2020uqk , and the corresponding parameters are set to be 0.56 and 0.25 for the internals from the threshold to 2.68 GeV and from 2.68 to 3.04 GeV, respectively. The relative difference of the detection efficiency to that based on the phase space distribution is assigned as the uncertainty.
7.
Luminosity:
The integrated luminosity is measured by using large-angle Bhabha events with an uncertainty of 0.5% at 3.773 GeV BESIII:2015equ and 1.0% at 4.128-4.258 GeV BESIII:2023ioy ; BESIII:2020eyu ; BESIII:2015qfd . Besides, an additional uncertainty of 0.5% is taken from the radiator function Eq. (4) of Ref. Druzhinin:2011qd . Therefore, the total systematic uncertainty associated with the luminosity for each mass interval is 0.8% at 3.773 GeV and 1.2% at the other energy points.
8.
Quoted branching fractions:
The branching fractions of , and are quoted from the PDG ParticleDataGroup:2022pth . The total uncertainty associated with the quoted branching fractions is 1.2%.
In this analysis, the data sets taken at twelve c.m. energy points are used and they are separated into two groups.
The first group only includes the one at 3.773 GeV and the second group includes the data sets taken at 4.128-4.258 GeV.
The uncertainties of the second group are studied together or obtained from the result at GeV.
The systematic uncertainties of the combined groups are listed in Table 4 using the two mass intervals with largest statistics as examples.
Uncertainties of the two groups are combined as the average value weighted by the individual detection efficiencies
and effective ISR luminosities.
The weighted average formula is
with
(8)
where , , and with = 1, 2 are the weight factor, systematic uncertainty, and detection efficiency for the -th group, is the correlation parameter for the -th and -th group.
For the contributions to the systematic uncertainties due to background no correlation is assumed ( = 0), while full correlation is assumed ( = 1) for all other contributions.
Table 4: The relative systematic uncertainties (in %) in the measurements of the cross sections for in two intervals for the full data sample. The total uncertainty is obtained by adding all items in quadrature.
Source
2.50-2.56 [GeV]
2.56-2.62 [GeV
Tracking and PID
1.6
1.6
reconstruction
3.3
3.3
requirement
1.4
1.4
requirement
2.8
2.8
mass window
1.0
1.0
Background estimation
1.6
1.6
Angular distribution
8.5
8.1
Luminosity
0.9
0.9
1.2
1.2
Total
10.0
9.6
VI Branching fractions of and
As shown in Fig. 2, masses from the pair threshold up to 4.0 GeV can be studied, including the narrow charmonium vector resonances and .
Thus, it is possible to study the decays of these resonances into pairs of hyperons and to determine the branching fractions by using the data sets taken at and 4.178 GeV with the ISR method.
After integrating over the ISR photon polar angle, the cross section for ISR production of a narrow vector meson resonance decaying into the final state can be calculated by BESIII:1999res :
(9)
where and are the mass and electronic width of the vector meson . Here, are the and with keV and keV ParticleDataGroup:2022pth , respectively. is the branching fraction of .
is calculated using Eq. (4) with . If the cross section is measured, the branching fraction can be calculated by Eq. (9). The cross section can also be written as:
(10)
where is the number of events. The is the detection efficiency of determined from the signal MC samples. The MC samples are generated with angular distributions described as with for and for BESIII:2020fqg .
The remaining parameters in Eq. (10) are consistent with those defined above.
To extract , using as a shared parameter, a simultaneous fit to the distributions at and 4.178 GeV is performed. The MC simulated shape is used to describe the resonance and a linear function for the background and the continuum contribution.
The fit results are shown in Figs. 4(a) and 4(b) for and Figs. 4(c) and 4(d) for .
Figure 4: Simultaneous fit (black curve) with the MC simulated shape (red dashed curve) for the resonance of (a) and (b) or (c) and (d) and a linear function (blue dashed curve) for the background of the spectra at and GeV. The black dots with error bars are data.
The systematic uncertainties in the measurements of include tracking and PID efficiencies of charged tracks, reconstruction, the requirement, the requirement, the mass window, the luminosity, and the branching fractions of intermediate states. They are assigned in the same way as for the cross section measurement. In addition, the uncertainty due to the MC model is considered by changing the generator model for the decays of or from HELAMP to AngSamPing:2008zz .
The uncertainty of the fit region is determined by changing the fit region from [2.89, 3.29] GeV/ to a wider [2.79, 3.30] GeV/ and a narrower interval [2.94, 3.24] GeV/.
The uncertainty of the signal model is estimated by additionally convolving the signal shape with a Gaussian distribution to account for the possible differences between data and MC simulation. The uncertainty of the background model in the fit is estimated by changing the model from a linear function to a constant, which is found to be negligible. The systematic uncertainties of the measurements of the branching fractions of and are listed in Table 5.
Table 5: The relative systematic uncertainties (in %) in the measurements of the branching fractions of and . The total uncertainty is obtained by adding all items in quadrature.
Source
Tracking and PID
1.6
1.5
reconstruction
3.3
3.3
requirement
1.4
1.4
requirement
2.8
2.8
mass window
1.0
1.0
MC model
0.5
3.1
Luminosity
0.9
0.9
1.2
1.2
Fit range
1.7
0.8
Signal model of the fit
2.7
4.4
Total
6.0
7.4
The final results for with Eqs. (9) and (10) are listed in Table 6.
They are consistent with the previous results by BESIII with the data sets taken at the or resonance peak BESIII:2021wkr , showing the reliability of the method of determining the EMFFs.
Table 6: The branching fractions of and (in ), where the first and second uncertainties
are statistical and systematic, respectively.
The cross sections measured in Section IV are consistent with the previous results from BESIII BESIII:2020uqk and Belle Belle:2022dvb , as depicted in Fig. 5.
A search for a threshold effect is made by performing a least chi-square fit to the cross section in this measurement from the production threshold up to 3.04 GeV and the BESIII scan results BESIII:2020uqk with different functions. The systematic uncertainty is included in the fit with the correlated and uncorrelated parts considered separately.
The perturbative QCD-motivated (pQCD) Pacetti:2014jai energy power function is assumed to model the line-shape of production, and the formula is expressed as:
(11)
where is the normalization parameter, is the contribution of resonant states, is the QCD scale fixed to 0.3 GeV and all parameters and variables are consistent with those defined for Eq. (1). The fit result is shown as the solid blue line in Fig. 5 and the parameters are listed in Table 7, with the fit quality , where the number of degrees of freedom () is calculated by subtracting the number of free parameters in the fit from the total number of intervals. The bottom panel of Fig. 5 present the distributions defined by , where the and are the measured and fitted cross sections at each invariant mass interval, respectively, and corresponds to the error of the measured value which is counted as the quadratic sum of the statistical and systematic uncertainties.
Figure 5: Fit to the cross section of . The blue line is the fit result using the perturbative QCD-motivated energy power function, described with Eq. (11). The black curve represents the total fit result using Eq. (13). The individual contributions associated with Eq. (13) are indicated by the green curve (pQCD), red curve (Resonance) and purple dashed curve (interference between the pQCD function and the resonance). The vertical dashed line refers to the production threshold for . The fit quality is presented by distributions and depicted in the bottom panel. The inverted triangle symbol with red line represents its upper limit.
The Fano-type FF includes the interference between several resonances and the continuum contribution Fano:1961zz .
The amplitude of the resonance can be written in terms of Breit-Wigner parametrizations,
(12)
where and are the mass and width of the resonance, and are the corresponding electronic partial width and branching fraction, respectively.
Assuming the pQCD-motivated power function to describe the continuum contribution, the line-shape of the cross section for can be modeled by the coherent sum of Eqs. (11) and (12) to account for the possible interference of a vector meson and the continuum production:
(13)
Here, is a relative phase between the function and the pQCD energy power function, and is the two-body phase space factor.
The fit result assuming the line-shape as described in Eq. (13) is shown as the solid black line in Fig. 5 and the parameters are listed in Table 7, with the fit quality being 12.6/13.
Table 7: The parameters obtained from the fit to the cross section line-shape. The method 1 uses Eq. (11), while the method 2 uses Eq. (13).
Method
Parameter
Method1
[]
3.610.47
[GeV]
1.790.03
Method2
[]
2.182.16
[GeV]
1.850.17
0.450.26
[GeV]
2.530.04
[MeV]
88.6742.09
[rad]
1.421.02
According to the difference of between the results, the statistical significance for the model indicating the presence of a resonance state near 2.5 GeV is estimated to be 3.4, including both statistical and systematic uncertainties. Thereby, there may be resonant structures at 2.5 GeV.
Fig. 6 shows a comparison of the measured effective FFs with previous measurements of at BESIII BESIII:2020uqk and Belle Belle:2022dvb . A prediction for the non-resonant cross section of at the mass BaldiniFerroli:2019abd , based on an effective Lagrangian density, is consistent with our result when extrapolated to 3.097 GeV using Eq. (11).
Figure 6: Comparison of the effective FFs obtained in this work with the previous measurements of BESIII BESIII:2020uqk and Belle Belle:2022dvb . The inverted triangle symbol with red line represents its upper limit. The vertical dashed line refers to the production threshold for .
VIII Summary
Using the untagged ISR technique, where the radiative photon is not detected, the cross section of
is measured and the effective FF of is determined from threshold to 3.04 GeV.
A data set corresponding to a total integrated luminosity of 12.0 fb-1, collected at twelve c.m. energies with the BESIII detector at the BEPCII collider, is analyzed.
The results are consistent with the previous measurements from BESIII BESIII:2020uqk and Belle Belle:2022dvb .
It should be noted that the width of the lowest mass interval in this work is about 30.5 MeV above the threshold, and the value in the lowest invariant mass interval (2.379-2.44 GeV) is definitely closer to the BESIII scan results BESIII:2020uqk than to the Belle ISR measurement Belle:2022dvb . Our results also provide experimental inputs to test various theoretical models, such as potential and diquark correlation models Anselmino:1992vg ; Jaffe:2003sg ; Jaffe:2004ph .
Furthermore, combining the data sets taken at 3.773 and 4.178 GeV, the branching fractions of and are measured. The obtained results are consistent with the previous measurements of BESIII BESIII:2021wkr .
In the near future, BESIII will finish collecting data at 3.773 GeV with a total integrated luminosity of 20 fb-1BESIII:2020book , to allow a more precise ISR measurement.
IX acknowledgements
The BESIII Collaboration thanks the staff of BEPCII and the IHEP computing center for their strong support. This work is supported in part by National Key R&D Program of China under Contracts No. 2020YFA0406300 and No. 2020YFA0406400; National Natural Science Foundation of China (NSFC) under Contracts No. 11635010, No. 11735014, No. 11835012, No. 11935015, No. 11935016, No. 11935018, No. 11961141012, No. 12025502, No. 12035009, No. 12035013, No. 12061131003, No. 12192260, No. 12192261, No. 12192262, No. 12192263, No. 12192264, No. 12192265, No. 12221005, No. 12225509, No. 12235017, No. 12122509 and No. 12005311; the Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program; the CAS Center for Excellence in Particle Physics (CCEPP); Joint Large-Scale Scientific Facility Funds of the NSFC and CAS under Contract No. U1832207; CAS Key Research Program of Frontier Sciences under Contracts No. QYZDJ-SSW-SLH003 and No. QYZDJ-SSW-SLH040; 100 Talents Program of CAS; The Institute of Nuclear and Particle Physics (INPAC) and Shanghai Key Laboratory for Particle Physics and Cosmology; European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement under Contract No. 894790; German Research Foundation DFG under Contracts No. 455635585, Collaborative Research Center Grant No. CRC 1044, No. FOR5327 and No. GRK 2149; Istituto Nazionale di Fisica Nucleare, Italy; Ministry of Development of Turkey under Contract No. DPT2006K-120470; National Research Foundation of Korea under Contract No. NRF-2022R1A2C1092335; National Science and Technology fund of Mongolia; National Science Research and Innovation Fund (NSRF) via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation of Thailand under Contract No. B16F640076; Polish National Science Centre under Contract No. 2019/35/O/ST2/02907; The Swedish Research Council; and U. S. Department of Energy under Contract No. DE-FG02-05ER41374.