Study of the decays $\psi(3686)\rightarrow\gamma\chi_{cJ}\rightarrow\gamma\bar{p}K^{*+}\Lambda+c.c.$ and $\psi(3686)\rightarrow\bar{p}K^{*+}\Lambda+c.c.$
M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, M., Alekseev, A. Amoroso, F. F. An, Q. An, Y. Bai, O. Bakina, R. Baldini Ferroli,, Y. Ban, K. Begzsuren, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, F., Bianchi, J Biernat, J. Bloms, I. Boyko, R. A. Briere

TL;DR
This study measures the first observations of specific decay modes of the $ ext{psi}(3686)$ particle involving baryons and mesons, providing precise branching fractions based on a large dataset from BESIII.
Contribution
The paper reports the first measurement of branching fractions for $ ext{psi}(3686)$ decays into $ar{p}K^{*+}\Lambda$ and $ ext{chi}_{cJ} ightarrowar{p}K^{*+}\Lambda$, expanding knowledge of charmonium decay channels.
Findings
Branching fractions for $ ext{chi}_{cJ}$ decays measured.
First observation of these decay modes.
Precise values with statistical and systematic uncertainties.
Abstract
Based on the data sample of events collected with the BESIII detector at BEPCII, we present a study of the decays and . The branching fractions of (=0, 1, 2) are measured to be , , and , respectively, where the first uncertainties are statistical and the second systematic. The branching fraction of is measured to be . All these decay modes are observed for the first time.
| Source | ||||
|---|---|---|---|---|
| MDC Tracking | 4.0 | 4.0 | 4.0 | 4.0 |
| PID efficiency | 4.0 | 4.0 | 4.0 | 4.0 |
| Photon detection | 3.0 | 3.0 | 3.0 | 2.0 |
| mass window | 0.1 | 0.1 | 0.1 | 0.1 |
| Kinematic fit | 0.1 | 0.5 | 0.2 | 1.4 |
| Fit range | 5.9 | 2.1 | 2.0 | 3.0 |
| Signal shape | 4.9 | 3.8 | 4.1 | 3.4 |
| Background shape | 1.3 | 2.0 | 0.7 | 1.1 |
| Number of events | 0.7 | 0.7 | 0.7 | 0.7 |
| 0.8 | 0.8 | 0.8 | 0.8 | |
| 2.0 | 2.5 | 2.1 | – | |
| Total | 10.3 | 8.5 | 8.2 | 7.8 |
| Decay channel | Branching fraction | |
|---|---|---|
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsParticle physics theoretical and experimental studies · Quantum Chromodynamics and Particle Interactions
Study of the decays and
M. Ablikim1, M. N. Achasov10,d, P. Adlarson59, S. Ahmed15, M. Albrecht4, M. Alekseev58A,58C, A. Amoroso58A,58C, F. F. An1, Q. An55,43, Y. Bai42, O. Bakina27, R. Baldini Ferroli23A, Y. Ban35, K. Begzsuren25, J. V. Bennett5, N. Berger26, M. Bertani23A, D. Bettoni24A, F. Bianchi58A,58C, J Biernat59, J. Bloms52, I. Boyko27, R. A. Briere5, H. Cai60, X. Cai1,43, A. Calcaterra23A, G. F. Cao1,47, N. Cao1,47, S. A. Cetin46B, J. Chai58C, J. F. Chang1,43, W. L. Chang1,47, G. Chelkov27,b,c, D. Y. Chen6, G. Chen1, H. S. Chen1,47, J. C. Chen1, M. L. Chen1,43, S. J. Chen33, Y. B. Chen1,43, W. Cheng58C, G. Cibinetto24A, F. Cossio58C, X. F. Cui34, H. L. Dai1,43, J. P. Dai38,h, X. C. Dai1,47, A. Dbeyssi15, D. Dedovich27, Z. Y. Deng1, A. Denig26, I. Denysenko27, M. Destefanis58A,58C, F. De Mori58A,58C, Y. Ding31, C. Dong34, J. Dong1,43, L. Y. Dong1,47, M. Y. Dong1,43,47, Z. L. Dou33, S. X. Du63, J. Z. Fan45, J. Fang1,43, S. S. Fang1,47, Y. Fang1, R. Farinelli24A,24B, L. Fava58B,58C, F. Feldbauer4, G. Felici23A, C. Q. Feng55,43, M. Fritsch4, C. D. Fu1, Y. Fu1, Q. Gao1, X. L. Gao55,43, Y. Gao56, Y. Gao45, Y. G. Gao6, Z. Gao55,43, B. Garillon26, I. Garzia24A, E. M. Gersabeck50, A. Gilman51, K. Goetzen11, L. Gong34, W. X. Gong1,43, W. Gradl26, M. Greco58A,58C, L. M. Gu33, M. H. Gu1,43, S. Gu2, Y. T. Gu13, A. Q. Guo22, L. B. Guo32, R. P. Guo36, Y. P. Guo26, A. Guskov27, S. Han60, X. Q. Hao16, F. A. Harris48, K. L. He1,47, F. H. Heinsius4, T. Held4, Y. K. Heng1,43,47, Y. R. Hou47, Z. L. Hou1, H. M. Hu1,47, J. F. Hu38,h, T. Hu1,43,47, Y. Hu1, G. S. Huang55,43, J. S. Huang16, X. T. Huang37, X. Z. Huang33, N. Huesken52, T. Hussain57, W. Ikegami Andersson59, W. Imoehl22, M. Irshad55,43, Q. Ji1, Q. P. Ji16, X. B. Ji1,47, X. L. Ji1,43, H. L. Jiang37, X. S. Jiang1,43,47, X. Y. Jiang34, J. B. Jiao37, Z. Jiao18, D. P. Jin1,43,47, S. Jin33, Y. Jin49, T. Johansson59, N. Kalantar-Nayestanaki29, X. S. Kang31, R. Kappert29, M. Kavatsyuk29, B. C. Ke1, I. K. Keshk4, T. Khan55,43, A. Khoukaz52, P. Kiese26, R. Kiuchi1, R. Kliemt11, L. Koch28, O. B. Kolcu46B,f, B. Kopf4, M. Kuemmel4, M. Kuessner4, A. Kupsc59, M. Kurth1, M. G. Kurth1,47, W. Kühn28, J. S. Lange28, P. Larin15, L. Lavezzi58C, H. Leithoff26, T. Lenz26, C. Li59, Cheng Li55,43, D. M. Li63, F. Li1,43, F. Y. Li35, G. Li1, H. B. Li1,47, H. J. Li9,j, J. C. Li1, J. W. Li41, Ke Li1, L. K. Li1, Lei Li3, P. L. Li55,43, P. R. Li30, Q. Y. Li37, W. D. Li1,47, W. G. Li1, X. H. Li55,43, X. L. Li37, X. N. Li1,43, X. Q. Li34, Z. B. Li44, Z. Y. Li44, H. Liang1,47, H. Liang55,43, Y. F. Liang40, Y. T. Liang28, G. R. Liao12, L. Z. Liao1,47, J. Libby21, C. X. Lin44, D. X. Lin15, Y. J. Lin13, B. Liu38,h, B. J. Liu1, C. X. Liu1, D. Liu55,43, D. Y. Liu38,h, F. H. Liu39, Fang Liu1, Feng Liu6, H. B. Liu13, H. M. Liu1,47, Huanhuan Liu1, Huihui Liu17, J. B. Liu55,43, J. Y. Liu1,47, K. Y. Liu31, Ke Liu6, Q. Liu47, S. B. Liu55,43, T. Liu1,47, X. Liu30, X. Y. Liu1,47, Y. B. Liu34, Z. A. Liu1,43,47, Zhiqing Liu37, Y. F. Long35, X. C. Lou1,43,47, H. J. Lu18, J. D. Lu1,47, J. G. Lu1,43, Y. Lu1, Y. P. Lu1,43, C. L. Luo32, M. X. Luo62, P. W. Luo44, T. Luo9,j, X. L. Luo1,43, S. Lusso58C, X. R. Lyu47, F. C. Ma31, H. L. Ma1, L. L. Ma37, M. M. Ma1,47, Q. M. Ma1, X. N. Ma34, X. X. Ma1,47, X. Y. Ma1,43, Y. M. Ma37, F. E. Maas15, M. Maggiora58A,58C, S. Maldaner26, S. Malde53, Q. A. Malik57, A. Mangoni23B, Y. J. Mao35, Z. P. Mao1, S. Marcello58A,58C, Z. X. Meng49, J. G. Messchendorp29, G. Mezzadri24A, J. Min1,43, T. J. Min33, R. E. Mitchell22, X. H. Mo1,43,47, Y. J. Mo6, C. Morales Morales15, N. Yu. Muchnoi10,d, H. Muramatsu51, A. Mustafa4, S. Nakhoul11,g, Y. Nefedov27, F. Nerling11,g, I. B. Nikolaev10,d, Z. Ning1,43, S. Nisar8,k, S. L. Niu1,43, S. L. Olsen47, Q. Ouyang1,43,47, S. Pacetti23B, Y. Pan55,43, M. Papenbrock59, P. Patteri23A, M. Pelizaeus4, H. P. Peng55,43, K. Peters11,g, J. Pettersson59, J. L. Ping32, R. G. Ping1,47, A. Pitka4, R. Poling51, V. Prasad55,43, M. Qi33, T. Y. Qi2, S. Qian1,43, C. F. Qiao47, N. Qin60, X. P. Qin13, X. S. Qin4, Z. H. Qin1,43, J. F. Qiu1, S. Q. Qu34, K. H. Rashid57,i, K. Ravindran21, C. F. Redmer26, M. Richter4, M. Ripka26, A. Rivetti58C, V. Rodin29, M. Rolo58C, G. Rong1,47, Ch. Rosner15, M. Rump52, A. Sarantsev27,e, M. Savri24B, K. Schoenning59, W. Shan19, X. Y. Shan55,43, M. Shao55,43, C. P. Shen2, P. X. Shen34, X. Y. Shen1,47, H. Y. Sheng1, X. Shi1,43, X. D Shi55,43, J. J. Song37, Q. Q. Song55,43, X. Y. Song1, S. Sosio58A,58C, C. Sowa4, S. Spataro58A,58C, F. F. Sui37, G. X. Sun1, J. F. Sun16, L. Sun60, S. S. Sun1,47, X. H. Sun1, Y. J. Sun55,43, Y. K Sun55,43, Y. Z. Sun1, Z. J. Sun1,43, Z. T. Sun1, Y. T Tan55,43, C. J. Tang40, G. Y. Tang1, X. Tang1, V. Thoren59, B. Tsednee25, I. Uman46D, B. Wang1, B. L. Wang47, C. W. Wang33, D. Y. Wang35, H. H. Wang37, K. Wang1,43, L. L. Wang1, L. S. Wang1, M. Wang37, M. Z. Wang35, Meng Wang1,47, P. L. Wang1, R. M. Wang61, W. P. Wang55,43, X. Wang35, X. F. Wang1, X. L. Wang9,j, Y. Wang44, Y. Wang55,43, Y. F. Wang1,43,47, Z. Wang1,43, Z. G. Wang1,43, Z. Y. Wang1, Zongyuan Wang1,47, T. Weber4, D. H. Wei12, P. Weidenkaff26, H. W. Wen32, S. P. Wen1, U. Wiedner4, G. Wilkinson53, M. Wolke59, L. H. Wu1, L. J. Wu1,47, Z. Wu1,43, L. Xia55,43, Y. Xia20, S. Y. Xiao1, Y. J. Xiao1,47, Z. J. Xiao32, Y. G. Xie1,43, Y. H. Xie6, T. Y. Xing1,47, X. A. Xiong1,47, Q. L. Xiu1,43, G. F. Xu1, J. J. Xu33, L. Xu1, Q. J. Xu14, W. Xu1,47, X. P. Xu41, F. Yan56, L. Yan58A,58C, W. B. Yan55,43, W. C. Yan2, Y. H. Yan20, H. J. Yang38,h, H. X. Yang1, L. Yang60, R. X. Yang55,43, S. L. Yang1,47, Y. H. Yang33, Y. X. Yang12, Yifan Yang1,47, Z. Q. Yang20, M. Ye1,43, M. H. Ye7, J. H. Yin1, Z. Y. You44, B. X. Yu1,43,47, C. X. Yu34, J. S. Yu20, C. Z. Yuan1,47, X. Q. Yuan35, Y. Yuan1, A. Yuncu46B,a, A. A. Zafar57, Y. Zeng20, B. X. Zhang1, B. Y. Zhang1,43, C. C. Zhang1, D. H. Zhang1, H. H. Zhang44, H. Y. Zhang1,43, J. Zhang1,47, J. L. Zhang61, J. Q. Zhang4, J. W. Zhang1,43,47, J. Y. Zhang1, J. Z. Zhang1,47, K. Zhang1,47, L. Zhang45, S. F. Zhang33, T. J. Zhang38,h, X. Y. Zhang37, Y. Zhang55,43, Y. H. Zhang1,43, Y. T. Zhang55,43, Yang Zhang1, Yao Zhang1, Yi Zhang9,j, Yu Zhang47, Z. H. Zhang6, Z. P. Zhang55, Z. Y. Zhang60, G. Zhao1, J. W. Zhao1,43, J. Y. Zhao1,47, J. Z. Zhao1,43, Lei Zhao55,43, Ling Zhao1, M. G. Zhao34, Q. Zhao1, S. J. Zhao63, T. C. Zhao1, Y. B. Zhao1,43, Z. G. Zhao55,43, A. Zhemchugov27,b, B. Zheng56, J. P. Zheng1,43, Y. Zheng35, Y. H. Zheng47, B. Zhong32, L. Zhou1,43, L. P. Zhou1,47, Q. Zhou1,47, X. Zhou60, X. K. Zhou47, X. R. Zhou55,43, Xiaoyu Zhou20, Xu Zhou20, A. N. Zhu1,47, J. Zhu34, J. Zhu44, K. Zhu1, K. J. Zhu1,43,47, S. H. Zhu54, W. J. Zhu34, X. L. Zhu45, Y. C. Zhu55,43, Y. S. Zhu1,47, Z. A. Zhu1,47, J. Zhuang1,43, B. S. Zou1, J. H. Zou1
(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 Beijing Institute of Petrochemical Technology, Beijing 102617, People’s Republic of China
4 Bochum Ruhr-University, D-44780 Bochum, Germany
5 Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
6 Central China Normal University, Wuhan 430079, People’s Republic of China
7 China Center of Advanced Science and Technology, Beijing 100190, People’s Republic of China
8 COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
9 Fudan University, Shanghai 200443, People’s Republic of 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, People’s Republic of China
13 Guangxi University, Nanning 530004, People’s Republic of China
14 Hangzhou Normal University, Hangzhou 310036, People’s Republic of China
15 Helmholtz Institute Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
16 Henan Normal University, Xinxiang 453007, People’s Republic of China
17 Henan University of Science and Technology, Luoyang 471003, People’s Republic of China
18 Huangshan College, Huangshan 245000, People’s Republic of China
19 Hunan Normal University, Changsha 410081, People’s Republic of China
20 Hunan University, Changsha 410082, People’s Republic of 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 and 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 Physics and Technology, Peace Ave. 54B, Ulaanbaatar 13330, Mongolia
26 Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
27 Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
28 Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
29 KVI-CART, University of Groningen, NL-9747 AA Groningen, The Netherlands
30 Lanzhou University, Lanzhou 730000, People’s Republic of China
31 Liaoning University, Shenyang 110036, People’s Republic of China
32 Nanjing Normal University, Nanjing 210023, People’s Republic of China
33 Nanjing University, Nanjing 210093, People’s Republic of China
34 Nankai University, Tianjin 300071, People’s Republic of China
35 Peking University, Beijing 100871, People’s Republic of China
36 Shandong Normal University, Jinan 250014, People’s Republic of China
37 Shandong University, Jinan 250100, People’s Republic of China
38 Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
39 Shanxi University, Taiyuan 030006, People’s Republic of China
40 Sichuan University, Chengdu 610064, People’s Republic of China
41 Soochow University, Suzhou 215006, People’s Republic of China
42 Southeast University, Nanjing 211100, People’s Republic of China
43 State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People’s Republic of China
44 Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
45 Tsinghua University, Beijing 100084, People’s Republic of China
46 (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
47 University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
48 University of Hawaii, Honolulu, Hawaii 96822, USA
49 University of Jinan, Jinan 250022, People’s Republic of China
50 University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
51 University of Minnesota, Minneapolis, Minnesota 55455, USA
52 University of Muenster, Wilhelm-Klemm-Str. 9, 48149 Muenster, Germany
53 University of Oxford, Keble Rd, Oxford, UK OX13RH
54 University of Science and Technology Liaoning, Anshan 114051, People’s Republic of China
55 University of Science and Technology of China, Hefei 230026, People’s Republic of China
56 University of South China, Hengyang 421001, People’s Republic of China
57 University of the Punjab, Lahore-54590, Pakistan
58 (A)University of Turin, I-10125, Turin, Italy; (B)University of Eastern Piedmont, I-15121, Alessandria, Italy; (C)INFN, I-10125, Turin, Italy
59 Uppsala University, Box 516, SE-75120 Uppsala, Sweden
60 Wuhan University, Wuhan 430072, People’s Republic of China
61 Xinyang Normal University, Xinyang 464000, People’s Republic of China
62 Zhejiang University, Hangzhou 310027, People’s Republic of China
63 Zhengzhou University, Zhengzhou 450001, People’s Republic of 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 Functional Electronics Laboratory, Tomsk State University, Tomsk, 634050, Russia
d Also at the Novosibirsk State University, Novosibirsk, 630090, Russia
e Also at the NRC ”Kurchatov Institute”, PNPI, 188300, Gatchina, Russia
f Also at Istanbul Arel University, 34295 Istanbul, Turkey
g Also at Goethe University Frankfurt, 60323 Frankfurt am Main, Germany
h 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
i Also at Government College Women University, Sialkot - 51310. Punjab, Pakistan.
j 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
k Also at Harvard University, Department of Physics, Cambridge, MA, 02138, USA
Abstract
Based on the data sample of events collected with the BESIII detector at BEPCII, we present a study of the decays and . The branching fractions of (=0, 1, 2) are measured to be , , and , respectively, where the first uncertainties are statistical and the second systematic. The branching fraction of is measured to be . All these decay modes are observed for the first time.
pacs:
I Introduction
The quark model provides a good description of both the ground states and some excited states of baryons. However, several resonances that are predicted by this model have not yet been observed, and hence there is an intense experimental effort underway to find these missing states Klempt and Richard (2010). The baryon coupling in conventional production channels (e.g. -nucleon) can be quite small, but the coupling between baryons and decays via gluons could be larger (e.g. or decays). For this reason, charmonium decay is a promising process to study excited nucleons and hyperons Zou (2001).
The BES Collaboration has reported a study of and decays Ablikim et al. (2004), in which a threshold enhancement in the mass spectrum was observed. Throughout this paper, the inclusion of charge conjugate channels is implied. The BESIII Collaboration also reported a study of Ablikim et al. (2013a), where a near threshold enhancement in the mass spectrum of was observed in decay. This enhancement may be interpreted as a quasibound dibaryon state, or as an enhancement due to final-state interaction, or simply as an interference effect of high-mass and states Ablikim et al. (2013a). The study of the resonant structures in the similar decay modes and may help in the understanding of the threshold structure.
Until now, no experimental results exist concerning the decays and . In this analysis, the branching fractions (BFs) of ( = 0, 1, 2) and are measured for the first time with a data sample of events Ablikim et al. (2018). Moreover, possible substructures in invariant mass spectra of , , and are investigated.
II BESIII DETECTOR AND MONTE CARLO SIMULATION
The Beijing Electron Positron Collider II (BEPCII) is a double-ring collider running at center-of-mass energy ranging from 2.0 to . The BESIII detector Ablikim et al. (2010) at BEPCII, with a geometrical acceptance of of the solid angle, operates in a magnetic filed of 1.0 T provided by a superconducting solenoid magnet. The detector is composed of a helium-based main drift chamber (MDC), a plastic-scintillator time-of-flight (TOF) system, a CsI(Tl) electromagnetic calorimeter (EMC) and a resistive plate chambers (RPC)-based muon chamber (MUC). The spatial resolution of the MDC is better than 130 m, the charged track momentum resolution is at 1 GeV/, and the energy-loss () resolution is better than for electrons from Bhabha events. The time resolution of the TOF is 80 ps (110 ps) in the barrel (endcaps. The energy resolution of the EMC at 1.0 GeV is () in the barrel (endcaps). The position resolution in the MUC is better than 2 cm.
Simulated Monte Carlo (MC) events are used to determine the detection efficiency, optimize selection criteria and estimate the level of contamination from background processes. The geant4-based Agostinelli et al. (2003) simulation package boost includes a geometric and material description of the BESIII detector, detector response, and digitization models, and also tracks the running conditions and performance of the detector. The production of events is simulated with kkmc Jadach et al. (2001), where the known decay modes are generated by evtgen Lange (2001); Ping (2008) with their BFs taken from the Particle Date Group (PDG) Patrignani et al. (2018), and the remaining unknown decays are generated by lundcharm Chen et al. (2000). Exclusive MC samples of and are generated to determine detection efficiencies. In the signal MC simulation, the angular distribution of the decay has the form with =1, , 1/13 for 0, 1, 2, respectively, where is the photon polar angle Karl et al. (1976). The weak decay of is generated with a model that includes parity violation. Other relevant decays are generated with besevtgen Ping (2008) with a uniform distribution in phase space.
III Analysis of
III.1 Event selection
The process is reconstructed with , , and . Events are required to have at least two positive and two negative charged tracks. For each charged track, the polar angle in the MDC must satisfy . The combined TOF and information is used to form particle identification (PID) confidence levels for pion, kaon and proton hypotheses. Each track is assigned to the particle hypothesis with the highest confidence level. The identified and candidates are further required to have their point of closest approach to the interaction point (IP) within 1 cm in the plane perpendicular to beam direction and within 10 cm in the plane of the beam direction. A common vertex constraint is applied to all pairs assumed to arise from a decay, and the production of the candidates is constrained to be at the interaction point. Only information is used for the PID of and candidates in decays, because many of these particles do not reach the TOF on account of their low momentum.
Photon candidates are required to have energy deposition greater than 25 MeV in the barrel EMC () and 50 MeV in the end cap EMC (). To exclude showers from charged tracks, the angle between the direction of the photon and the nearest charged track is required to be greater than . In addition, the angle between the direction of the photon and anti-proton is required to be greater than to suppress background from anti-proton annihilation in the detector. The measured EMC time is required to be within 0 and 700 ns of start time of the event to suppress electronic noise and any energy deposition unrelated to the event.
To improve the mass resolution, the selected photons, anti-proton, kaon, and candidate are subjected to a five-constraint (5C) kinematic fit under the hypothesis of with the invariant mass of the two photons being constrained to the mass. The of the 5C fit is required to be less than 70. For events with more than one combination satisfying this requirement, only the combination with the smallest is accepted. To veto background events from and , an alternative 5C (4C) kinematic fit is performed under the hypotheses of (). We further require the confidence level of the kinematic fit for the assignment to be larger than those for the and hypotheses.
The invariant mass distribution is shown in Fig. 1(a), where an obvious structure can be seen. The candidates are selected by requiring , where is the nominal mass of the meson Patrignani et al. (2018). The sidebands, also indicated in Fig. 1(a), are chosen to be and . Figure 1(b) shows the distribution, from which candidates are selected by requiring , where is the nominal mass Patrignani et al. (2018). Background events from , are rejected by requiring , where is the nominal mass Patrignani et al. (2018). To remove the background from the cascade decay , , the additional selection requirement GeV/ is applied.
After applying these requirements, signals are clearly seen in the invariant mass spectrum of , as shown in Fig. 2. The mass windows used to select the , , candidates correspond to about three times the width convolved with the mass resolution, which are 3.35-3.48, 3.49-3.53, and 3.53-3.59 GeV/, respectively. The invariant mass spectra of the , , and combinations and the corresponding Dalitz plots are shown in Fig. 3 for each state. No significant substructure is seen in the Dalitz plots of distributions. In order to search for the near-threshold structure of observed in Ref. Ablikim et al. (2013a) in the decay , fits are performed on where the structure is described by a weighted Breit-Wigner resonance with parameters fixed to those reported in Ref. Ablikim et al. (2013a). These fits return a statistical significance for the structure of 2.1, 2.5, and 1.9 for the , , and states, respectively.
III.2 Background study
Using an inclusive MC sample of events, the background from fake is found together with fake . So, the background can be categorized into the following four types: (1) events with a genuine and a fake (, non-); (2) events with a genuine and a fake (, non-); (3) events with fake and candidates (non-, non-); (4) events containing a genuine and a genuine (, ). The contributions from the first three categories can be estimated by performing a two-dimensional (2-D) fit to the distribution of versus . The fourth type of background events come mainly from the processes , , and . The first two of these contributions are negligible, on account of the low BF of radiative and decays. The level of contamination coming from the other two modes is assessed by applying the selection to samples of exclusive MC events. For the normalization procedure, the BF of is estimated to be less than , which implies negligible background of less than one event from this source. The normalized number of background events is estimated to be 11.73.5, 5.12.3, 4.82.6 for (=0, 1, 2), where the relative BFs used to calculate these yields are estimated from dedicated studies with the same data sample.
To investigate possible background from continuum processes, the same selection criteria are applied to a data sample of 2.93 fb*-1* Ablikim et al. (2016) collected at GeV. After normalizing to the integrated luminosity of the data sample, 20.14.1 events survive and no peak is found in the mass spectrum of . As a cross check the selection is also performed on a data sample of 44.5 pb*-1* collected at GeV. Only one event survives, which corresponds to 14 events when normalized to the integrated luminosity of the data sample, and is consistent with the result of the first study. In the BF measurement any continuum contribution is included in the other sources of non-peaking background and the total is estimated by the 2-D fit described below.
III.3 Branching fraction measurement of
The distribution of versus is shown in Fig. 4. An unbinned extended maximum-likelihood 2-D fit is performed on this distribution to determine the number of (, ) events. The composite probability density function (PDF) is constructed as follows:
[TABLE]
Here, , , , and are the numbers of (, ) signal events, (, non-), (, non-), and (non-, non-) background events, respectively.
The shape of the resonance, , is described by a -wave Breit-Wigner (BW) function Ablikim et al. (2013b) convolved with a double-Gaussian function () that accounts for detector resolution, the parameters of which are determined from MC simulation. The definition of is
[TABLE]
where , is the invariant mass of the pair, and are the mass and width Patrignani et al. (2018), is the momentum in the rest frame, is the value at , and is the relative orbital angular momentum of .
The background distribution of the fake contribution, , is described by truncated polynomial function Ablikim et al. (2013b), where is the threshold mass for and , , are free parameters.
The shape of the signal is described by
[TABLE]
Here is an E1 radiative-transition factor and is a damping factor Anashin et al. (2011), where is the energy of the radiative photon in the rest frame and . In the relativistic BW function , the mass and width of the are fixed to the PDG Patrignani et al. (2018) values. The Blatt-Weisskopf barrier factor Chung (1998) is a function of , which is the momentum of either the radiative photon or the in the rest frame, is the value at , where is the invariant mass of the combination. Finally, is a modified Gaussian function parameterizing the instrumental mass resolution, taking the form Chekanov et al. (2005)
[TABLE]
where the parameters are determined from MC simulation.
The shape of fake candidates, , is described by an ARGUS Albrecht et al. (1990) function.
The fit yields (, ) events with a statistical significance of 7.2, (, ) events with a statistical significance of 11.6, and (, ) events with a statistical significance of 15.2. The statistical significance is determined from the change of the log-likelihood value and the degrees of freedom in the fit when performed with and without a signal component. The 2-D histogram sampled from the composite PDF and the projections of the fit on the and distributions are shown in Fig. 4.
The BF of is calculated by
[TABLE]
where is the number of signal event returned from the 2-D fit and , , are the numbers of (, ), (, ), (, ) peaking background events, respectively, which is reported in Sec. III.2; is the number of events Ablikim et al. (2018), and are detection efficiencies which are determined from MC simulation and found to be , , and for the , , and signals, respectively. The BFs , , , and are taken from Ref. Patrignani et al. (2018). The BFs of are measured to be for the mode, for the mode, and for the mode, where the uncertainties are statistical only.
IV Study of
IV.1 Event Selection
Events are selected containing at least two photons, one , one , and one candidate, identified using the same criteria as employed in the analysis. The selected particles are subjected to a 5C kinematic fit under the hypothesis of , with the invariant mass of the two photons constrained to the mass. The of the 5C fit is required to be less than 100. For events with more than one combination meeting this requirement, only the combination with the smallest is retained for further analysis. To veto backgrounds from and , an alternative 5C (4C) kinematic fit is performed under the () hypothesis. We further require that the confidence level of the kinematic fit for the assignment is larger than those of the and hypotheses.
The distribution of versus is shown in Fig. 5(a), where and signals are visible. The candidates are selected by requiring and candidates are selected by requiring . The sidebands are defined to be and . The distribution of for events within the signal region is shown in Fig. 5(b). The mass spectra of , , , and Dalitz plot after the application of all selection criteria are shown in Fig. 6. A near-threshold structure in the is fitted with a 1.7 signficance, using the the same parameterization as in the analysis.
IV.2 Background study
Using an inclusive MC sample of events, the background from fake is found together with fake . The sources of background can be categorized into two types: peaking background events with genuine mesons in the final state and non-peaking background events with fake candidates. The non-peaking background can be estimated from a fit to the spectrum. The major peaking backgrounds are found to be: (=0, 1, 2) and . Corresponding exclusive MC samples are generated for further studies. The selection criteria are applied to these exclusive MC samples and the number of surviving events are normalized by the BFs of the relevant decay processes. The normalized number of background events is 5.21.1 and the expected numbers of (=0, 1, 2) background decays are 1.90.3, 4.50.5 and 8.81.0, respectively.
A data sample of 2.93 fb*-1* Ablikim et al. (2016) collected at is used to investigate possible background from continuum processes. After normalizing to the integrated luminosity of the data sample, 164.19.5 events survive and a clear peak is found in the mass spectrum. This background yield is cross-checked by repeating the procedure on the data sample of 44.5 pb*-1* Ablikim et al. (2013c) collected at GeV, and a compatible result of 20761 events is obtained, after normalization.
IV.3 Branching fraction measurement of
An unbinned maximum likelihood fit is performed to the distribution of (Fig. 7) to extract the number of signal events. The signal shape is described by a -wave BW function convolved with a double-Gaussian function, and the background shape is described by a truncated polynomial function. The definitions of these functions are the same as those introduced in Sec. III.3. The fit result is shown in Fig. 7.
The BF of is calculated according to
[TABLE]
where is number of signal events obtained from the fit, is the number of peaking background events reported in Sec. IV.2, and is the detection efficiency, , estimated from MC simulation. The is measured to be , where the uncertainty is statistical only.
V Systematic uncertainties
Systematic uncertainties on the BF measurements arise from a variety of sources:
Tracking efficiency. The uncertainty due to data-MC difference in the tracking efficiency is 1% for each charged track coming from a primary vertex according to a study of and events. For each track from , the uncertainty is also 1% from analysis of events Ablikim et al. (2013a).
PID efficiency. The candidates require tracks to be identified as , , , or . The PID efficiency have been investigated using control samples of and Ablikim et al. (2011, 2012). The uncertainty is assigned to be 1% per charged track.
Photon detection efficiency. The photon detection efficiency was studied in the analysis of decays Ablikim et al. (2011). The difference in the detection efficiency between the data and MC simulation is taken as the systematic uncertainty from this source, and is assigned for each photon.
* Mass window.* The systematic uncertainty from the requirement on the signal region is estimated by smearing the invariant mass in the signal MC sample with a Gaussian function to compensate for the resolution difference between data and MC simulation. The smearing parameters are determined by fitting the distribution in data with the MC shape convolved with a Gaussian function. The difference in the detection efficiency as determined from signal MC sample with and without the extra smearing is taken as the systematic uncertainty.
Kinematic fit. The systematic uncertainty due to kinematic fitting is estimated by correcting the helix parameters of charged tracks according the method described in Ref. Ablikim et al. (2013d). The differences in the detection efficiency between the MC samples with and without this correction are taken as the uncertainties, which are , , and for (=0, 1, 2) and for .
Fit range. To estimate the systematic uncertainty due to fit range, several alternative fits in different ranges are performed. The resulting largest difference in the BF is assigned as the systematic uncertainty.
Signal shape. To estimate the uncertainty due to the choice of signal shape, the and signal line shapes are replaced by alternative fits using MC shapes and the resulting differences in the BFs are assigned as systematic uncertainties.
Background shape. In the measurements of and , the background shape is described by an ARGUS function and the background shape is described by a second-order truncated polynomial function. To estimate the systematic uncertainty due to choice of background shape, an alternative fit is performed in which the ARGUS function is replaced with a second-order Chebychev polynomial function and the signal is described with a third-order truncated polynomial. The change in the measured BF is assigned as the corresponding systematic uncertainty.
Others. The uncertainty due to the number of events is Ablikim et al. (2018). The systematic uncertainties associated with the intermediate-decay BFs of and are taken from the PDG Patrignani et al. (2018).
The above systematic uncertainties are summarized in Table 1. The total systematic uncertainty is calculated by assuming the individual components to be independent, and adding their magnitude in quadrature.
VI Results And Summary
The processes and are observed for the first time, using events collected with the BESIII detector. Measurements of the and are performed, for which the results are listed in Table 2. For the processes of (=0, 1, 2) and , no significant substructure is observed in the invariant-mass spectra of and . The mass spectrum is also compatible with the absence of substructure, although fits for possible excesses in the threshold region return results of around two sigma significance in each of the four cases. The new measurements provide more information for understanding the mechanisms of charmonium decays.
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 Basic Research Program of China under Contract No. 2015CB856700; National Natural Science Foundation of China (NSFC) under Contracts Nos. 11335008, 11425524, 11625523, 11635010, 11735014; 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 Contracts Nos. U1532257, U1532258, U1732263; CAS Key Research Program of Frontier Sciences under Contracts Nos. QYZDJ-SSW-SLH003, QYZDJ-SSW-SLH040; 100 Talents Program of CAS; INPAC and Shanghai Key Laboratory for Particle Physics and Cosmology; German Research Foundation DFG under Contract No. Collaborative Research Center CRC 1044, FOR 2359; Istituto Nazionale di Fisica Nucleare, Italy; Koninklijke Nederlandse Akademie van Wetenschappen (KNAW) under Contract No. 530-4CDP03; Ministry of Development of Turkey under Contract No. DPT2006K-120470; National Science and Technology fund; The Knut and Alice Wallenberg Foundation (Sweden) under Contract No. 2016.0157; The Royal Society, UK under Contract No. DH160214; The Swedish Research Council; U. S. Department of Energy under Contracts Nos. DE-FG02-05ER41374, DE-SC-0010118, DE-SC-0012069; University of Groningen (RuG) and the Helmholtzzentrum fuer Schwerionenforschung GmbH (GSI), Darmstadt
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1Klempt and Richard (2010) E. Klempt and J. M. Richard, Rev. Mod. Phys 82 , 1095 (2010).
- 2Zou (2001) B. S. Zou, Nucl. Phys. A 684 , 330 (2001).
- 3Ablikim et al . (2004) M. Ablikim et al . (BES Collaboration), Phys. Rev. Lett. 93 , 112002 (2004).
- 4Ablikim et al . (2013 a) M. Ablikim et al . (BESIII Collaboration), Phys. Rev. D 87 , 012007 (2013 a).
- 5Ablikim et al . (2018) M. Ablikim et al . (BESIII Collaboration), Chin. Phys. C 42 , 023001 (2018).
- 6Ablikim et al . (2010) M. Ablikim et al . (BESIII Collaboration), Nucl. Instrum. Methods Phys. Res., Sect. A 614 , 345 (2010).
- 7Agostinelli et al . (2003) S. Agostinelli et al . (GEANT 4 Collaboration), Nucl. Instrum. Methods Phys. Res., Sect. A 506 , 250 (2003).
- 8Jadach et al. (2001) S. Jadach, B. Ward, and Z. Was, Phys. Rev. D 63 , 113009 (2001).
