Observation of $\psi(3686)\to p\bar{p}\phi$
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, H.Cai, X.Cai, A.Calcaterra

TL;DR
This paper reports the first observation of the decay process $\psi(3686) o par{p}\phi$ with a measured branching fraction, and finds no evidence of a threshold enhancement previously observed in similar channels.
Contribution
It presents the first measurement of the branching fraction for $\psi(3686) o par{p}\phi$ and sets an upper limit on the related threshold enhancement decay.
Findings
Branching fraction of $\\psi(3686)\to p\bar{p}\phi$ measured as $(6.06\pm0.38\pm0.48)\times10^{-6}$
No threshold enhancement observed in $\\psi(3686)\to p\bar{p}\phi$
Upper limit of $1.82\times10^{-7}$ on $\\psi(3686)\to X(p\bar{p})\phi$
Abstract
Using a data sample of events collected with the BESIII detector, we present a first observation of , and we measure its branching fraction to be stat.syst.. In contrast to the earlier discovery of a threshold enhancement in the -mass spectrum of the channel , denoted as , we do not find a similar enhancement in . An upper limit of at the confidence level on the branching fraction of is obtained.
| Sources | ||
|---|---|---|
| MDC tracking | 3.0 | 3.0 |
| PID efficiency | 3.0 | 3.0 |
| 1C kinematic fit | 3.4 | 3.4 |
| veto | 1.1 | 1.1 |
| Mass spectrum fit | 5.5 | — |
| Weighting procedure | 1.0 | — |
| 1.0 | 1.0 | |
| Number of events | 0.6 | 0.6 |
| Total | 8.0 | 5.7 |
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Observation of
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. Gao45, Y. Gao56, 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, Z. L. Huang31, 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 Liu26, 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, C. F. Redmer26, M. Richter4, M. Ripka26, A. Rivetti58C, V. Rodin29, M. Rolo58C, G. Rong1,47, Ch. Rosner15, M. Rump52, A. Sarantsev27,e, M. Savrié24B, 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. Wang55,43, Y. Wang44, 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, 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
Using a data sample of events collected with the BESIII detector, we present a first observation of , and we measure its branching fraction to be stat.syst.. In contrast to the earlier discovery of a threshold enhancement in the -mass spectrum of the channel , denoted as , we do not find a similar enhancement in . An upper limit of at the confidence level on the branching fraction of is obtained.
pacs:
13.66.Bc, 14.40.Be
I INTRODUCTION
An intriguing enhancement near the -mass threshold, referred to as the , was discovered by BES in the channel cite01 and subsequently confirmed by CLEO cite02 and BESIII cite03 . A more recent partial-wave amplitude analysis of cite04 supports the existence of the structure and concludes to a spin-parity assignment of . There is no experimental evidence of such an enhancement in radiative cite05 decay nor in the decay cite06 . It is tempting to associate this enhancement with the , a resonance that was recently confirmed by BESIII cite09 after it was first observed in decay cite10 . Whether or not the -mass threshold enhancement and the are related to the same source still needs further study. As a result, lots of theoretical speculations have been proposed to interpret the nature of this structure, including the quasibound nuclear baryonium cite11 ; cite12 , a multiquark resonance cite13 or an effect caused by final-state interaction (FSI) cite14 ; cite15 near the proton-antiproton production threshold.
Most recently, BESIII reported the study of cite20 and no evidence of a near-threshold enhancement in the -mass spectrum was found. Moreover, no significant signatures of resonances in the or mass spectra were observed. For the decay of , BES reported an upper limit on the branching fraction of at the confidence level (C.L.) citeBESI . The latest measurement came from CLEO cite21 , who reported an upper limit on the branching fraction of at the C.L.. These experimental observations, together with similar results found in different decays, give rise to a discussion on the nature of the threshold effect and stimulate theoretical developments.
In this work, we report on the data analysis of the charmonium decay . The data have been obtained with the BESIII detector at the BEPCII storage ring at which a total of events cite22 were produced in electron-positron annihilations. The aim of this work is to search for a near-threshold enhancement in the -mass spectrum and to search for resonances that might hint to the existence of pentaquarks with hidden strangeness. Moreover, we measured the branching fraction of the process which allows us to inspect the ‘ rule’ proposed in 1975 cite23 . The rule is based on perturbative quantum chromodynamics (QCD) calculations, in which the ratio of the branching fractions of and into the same final hadronic state is given by
[TABLE]
II DETECTOR AND MONTE CARLO SIMULATION
The BESIII detector is a magnetic spectrometer Ablikim:2009aa located at the Beijing Electron Positron Collider (BEPCII) Yu:IPAC2016-TUYA01 . The cylindrical core of the BESIII detector 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. The solenoid is supported by an octagonal flux-return yoke with resistive plate counter muon identifier modules interleaved with steel. The acceptance of charged particles and photons is 93% over solid angle. The charged-particle momentum resolution at is , and the resolution is for the electrons from Bhabha scattering. The EMC measures photon energies with a resolution of () at GeV in the barrel (end cap) region. The time resolution of the TOF barrel part is 68 ps, while that of the end cap part is 110 ps.
Simulated samples produced with the geant4-based geant4 Monte Carlo (MC) package which includes the geometric description of the BESIII detector and the detector response, are used to determine the detection efficiency and to estimate the backgrounds. The simulation includes the beam energy spread and the initial-state radiation (ISR) in the annihilations modelled with the generator kkmc ref:kkmc . The inclusive MC sample consists of the production of the resonance, and the continuum processes incorporated in kkmc. The known decay modes are modelled with evtgen ref:evtgen using branching fractions taken from the Particle Data Group (PDG) pdg , and the remaining unknown decays from the charmonium states with lundcharm ref:lundcharm . The final-state radiation (FSR) from charged final-state particles is incorporated with the photos package photos . The background is studied using a sample of inclusive MC events. The analysis is performed in the framework of the BESIII offline software system (BOSS) ref:boss incorporating the detector calibration, event reconstruction and data storage.
III DATA ANALYSIS
III.1 Event selection and background analysis
The reaction is identified with the subsequently decaying into resulting in a final state of four charged tracks, namely . The charged tracks must have been detected in the active region of the MDC, corresponding to , where is the polar angle of the charged track with respect to the beam direction. Moreover, the tracks are required to pass within 10 cm of the interaction point in the beam direction and within 1 cm in the plane perpendicular to the beam. Two of the charged tracks are identified as a proton and an antiproton by using combined TOF and information. To improve the detection efficiency, the events with at least one are selected for further analysis. Thus, the candidate events are required to have three or four charged tracks. A one-constraint (1C) kinematic fit is subsequently performed under the hypothesis of , where or is treated as a missing particle with the nominal mass of a kaon. For the events with both kaons detected, two 1C kinematic fits are performed assuming a missing or . The one with the least is retained. To suppress background events, the is required to be less than 10.
The potential backgrounds are investigated using the inclusive MC sample. Besides the irreducible backgrounds from the non-resonant decay , the reducible backgrounds are dominated by the processes involving intermediate states. To suppress the above backgrounds, all other charged tracks except for the selected proton, antiproton and kaon candidates are assumed to be pions, and events are excluded if any combination of or has an invariant mass lying in the range MeV/. There are also some background events found originating from the process with . A MC sample is generated to describe its shape, and the number of background events of is expected to be , which is estimated by a fit to the measured invariant-mass spectrum. The signal shape of the is modeled with a Breit Wigner (BW) function, and the background is described with a second-order Chebychev polynomial function. Only the background from the continuum process was found to have a peaking structure underneath the -signal region. This contribution from this background is studied using the off-resonance samples taken at GeV, and its absolute magnitude is determined according to the formula , where is the number of events which remained in the off-resonance samples after applying the same event selections that are used to identify . , and refer to the integrated luminosities ( pb*-1* cite22 , pb*-1* N3773 , the cross sections and the detection efficiencies of the data samples taken at the two corresponding center-of-mass energies, respectively. Figure 1 shows the invariant-mass spectrum after applying all the selection criteria mentioned above. Note that a clear signal corresponding to the decay is visible in the spectrum. Figure 2 shows the Dalitz plot of for the events with a invariant-mass that falls within the -mass region (1.005 GeV/ 1.035 GeV/). The data show no evident resonance structures. Figure 3 shows its projections on the and invariant-mass distributions. These distributions show that the data are well described by a phase-space distribution of the signal channel together with the continuum background and non-peaking background.
III.2 Measurement of
The -signal yields are obtained from an extended unbinned maximum-likelihood fit to the invariant-mass spectrum in the range of GeV/. In the fit, the signal component is modeled by the MC-simulated signal shape convoluted with a Gaussian function to account for the difference in the mass resolution between data and MC simulation. The MC sample, , is generated according to a phase-space assumption. The background contribution from the continuum process is obtained as discussed above and its shape and yield are fixed in the fit. The other background events are parameterized by a modified ARGUS function cite32 . The parameters of the Gaussian function and the ARGUS function are left free in the fit. The fit, shown in Fig. 1, yields signal events. The statistical significance is found to be 21 , which is determined from the change in in the fits of mass spectrum with and without assuming the presence of a signal while considering the change in degrees of freedom of the fits.
The branching fraction of is calculated with,
[TABLE]
where is the number of the observed signal events which comes from the fit. is the total number of events. The branching fraction of , , is taken from the PDG pdg . is the detection efficiency. To obtain a reliable detection efficiency, the MC sample of , distributed according to a phase-space assumption, is weighted to match the distribution of the background-subtracted data with the mass distribution of , and the average detection efficiency is determined to be 56.4%. The branching fraction, , is measured to be , where the uncertainties are the statistical and systematic uncertainty, respectively. The systematic uncertainties will be discussed in detail in the following section.
III.3 Systematic uncertainties
The systematic uncertainties that affect the branching-fraction measurement can be divided into two categories. The first category is given by the uncertainties in the track reconstruction, the particle identification (PID), 1C kinematic fit, and veto efficiency. The other category comprises the uncertainties which originate from the fit of the mass spectrum, the weighting procedure, the cited branching fraction of the decay of the intermediate state, and the total number of events.
The difference in the efficiencies of the track reconstruction for between MC and data is studied using a clean sample of and found to be less than 1.0% per track. For the , the systematic uncertainty is studied using a clean control sample of . 1.0% per tracking is taken as the systematic uncertainty for the tracking efficiency ywccite33 .
The PID efficiency of is also studied from the same data sample of . The results indicate that the PID efficiency for data agrees with the MC simulation within 1%. The PID efficiency for the kaon is measured in the clean channel . It is found that the difference between the PID efficiency of data and MC is less than 1% for each kaon. In this analysis, three charged tracks are required to be identified as a proton, an anti-proton and a kaon. Hence, 3% is taken as the systematic uncertainty associated with the PID.
With a clean control sample of , the systematic uncertainty of the 1C kinematic fit is estimated to be 3.4% by calculating the difference of ratio of signal yields with cut and without 1C kinematic fit between MC simulation and data.
To veto the background events, MeV/ is required. An alternative choice of MeV/ is used to remeasure the branching fraction. A difference of 1.1% is found and taken as the corresponding systematic uncertainty.
The -signal yields are obtained by fitting the invariant-mass spectrum. Systematic uncertainties related to the fit have been estimated by using different signal and background shapes, alternative fit ranges, and by taking into consideration an additional resonant structure. To estimate the uncertainty from the modeling of the -signal shape, an alternative fit with an acceptance-corrected BW function to describe the -signal has been performed. To estimate the uncertainty due to the background shape, a function of is used instead of the modified ARGUS function, where, and are the lower and upper edges of the mass distribution, respectively, and and are free parameters. In the invariant-mass distribution, we observed a small bump around 1 GeV/. Although this structure might be due to statistical fluctuations, we considered the possibility of an additional resonance. We, therefore, fitted the distribution with an extra BW function convolved with a Gaussian function. The change of signal yield in the different fit is taken as the corresponding systematic uncertainty. The quadratic sum of the four individual uncertainties is taken as the systematic uncertainty related with the mass spectrum fit, and it is found to be 5.5%.
To obtain a reliable detection efficiency, the MC sample modeled using a phase-space distribution is weighted to match the distribution of the background-subtracted data. To consider the effect on the statistical fluctuations of the signal yield in the data, a set of toy-MC samples are used to estimate the detection efficiencies. With the reweighting, a maximum deviation in detection efficiencies of 1.0% is found and quoted as the corresponding systematic uncertainty.
The branching fraction uncertainty of the intermediate decay , 1.0%, is taken from the PDG and the uncertainty of the number of events is 0.6% cite22 .
In Table 1, a summary is shown of all contributions to the systematic uncertainties on the branching fraction measurements. The total systematic uncertainty is given by the quadratic sum of the individual contributions, assuming all sources to be independent.
III.4 Upper limit of mass threshold enhancement
Figure 4 depicts the invariant-mass distribution for the events with a invariant mass that falls within the mass region (1.005 GeV/ 1.035 GeV/), where no evident enhancement near the -mass threshold is visible. It is found that the events from the phase-space process together with other background components provide a good description of the data, which is shown in Fig. 4. Therefore, an upper limit for the production rate can be measured. For , we divide invariant-mass spectrum into 9 bins in the region of [1.876, 2.056] GeV/. With the same procedure as described above, the number of the events in each bin can be obtained by fitting to the corresponding -mass spectrum. Subsequently, the non--background-subtracted distribution is obtained as shown in Fig. 5, where the errors are statistical only, and is the nominal mass of proton pdg .
The spin () and parity () of have been determined by an amplitude analysis of decay and resulted in cite04 . In our analysis, we parametrize the signal by an efficiency-weighted -wave BW function,
[TABLE]
where is the invariant mass, the parameter accounts for the effect of the FSI, is the momentum of the proton in the rest frame, is the momentum of in the rest frame, is the relative orbital angular momentum of the system, and are the mass and width of , respectively, which are fixed to those in Ref. cite04 . is the mass-dependent detection efficiency which is obtained from MC simulations of . We ignore possible interference effects of the resonance with non-resonant background contributions.
To determine the upper limit on the size of the enhancement, a series of binned least- fits are performed to the background-subtracted -mass spectrum with the expected signal. Fit-related uncertainties are included by considering the following three aspects: (a) the signal is described by excluding the FSI factor with or taking into account the Jülich FSI value as described in Ref. cite15 ; (b) the non-resonant background is represented by the shape obtained from the MC simulation or parameterized by a function of (, and are free parameters); and (c) the fit is performed in the range of [0.00, 0.18] GeV/ or [0.00, 0.20] GeV/. Therefore, there are eight alternative fit scenarios. In the variations, the fit taking into account the FSI, with the background parameterized by the function of in the range [0.0, 0.18] GeV/, gives the maximum number of candidates, 20.6, at the 90% C.L.. The corresponding fitting plot is shown in Fig. 5, and the upper limit on the branching fraction is determined by,
[TABLE]
where is the maximum number of events. To be conservative, the multiplicative uncertainties listed in Table 1 are considered by convoluting the normalised distribution with a Gaussian function. The detection efficiency, , is obtained from MC simulations, and is determined to be 58.9%. The upper limit on the branching fraction of at the 90% C.L. is calculated to be .
IV SUMMARY
Using a sample of events accumulated with the BESIII detector, we present a study of the decay . The branching fraction of is measured for the first time and it is found to be stat.syst.. With the previously published branching-fraction measurement of cite20 , the ratio is determined to be . With the same approach as given in Ref. ppeta , we also present the ratio by taking the phase spaces of into account. The phase-space ratio of them is determined to be . By taking this into consideration, the value becomes , which indicates that the ‘ rule’ is violated significantly. No evidence for an enhancement near the -mass threshold is found and the upper limit on the branching fraction of is determined to be at the 90% C.L..
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, 11565006; 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. U1332201, 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; 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 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
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