Observation of $\psi(3686) \to p \bar{p} \eta^{\prime}$ and improved measurement of $J/\psi \to p \bar{p} \eta^{\prime}$
M. Ablikim, M. N. Achasov, S. Ahmed, M. Albrecht, M. Alekseev, A., Amoroso, F. F. An, Q. An, J. Z. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli,, Y. Ban, K. Begzsuren, D. W. Bennett, J. V. Bennett, N. Berger, M. Bertani, D., Bettoni, F. Bianchi, E. Boger, I. Boyko, R. A. Briere

TL;DR
This paper reports the first observation of the decay process $(3686) p ar{p} ta^{}$ with high significance and provides improved measurements of the branching fractions for $J//(3686)$ decays, along with the $ta-ta^{}$ mixing angle.
Contribution
First observation of $(3686) p ar{p} ta^{}$ decay and improved measurement of $J/$ decay branching fractions, including determination of the $ta-ta^{}$ mixing angle.
Findings
Branching fraction $B((3686) p ar{p} ta^{}) = (1.10 \u00b1 0.10 0.08) imes 10^{-5}$
Branching fraction $B(J/ p ar{p} ta^{}) = (1.26 \u00b1 0.02 0.07) imes 10^{-4}$
Determined $ta-ta^{}$ mixing angles of approximately $-24^\u00b0$ with uncertainties.
Abstract
We observe the process for the first time, with a statistical significance higher than 10, and measure the branching fraction of with an improved accuracy compared to earlier studies. The measurements are based on and events collected by the BESIII detector operating at the BEPCII. The branching fractions are determined to be and , where the first uncertainties are statistical and the second ones systematic. Additionally, the mixing angle is determined to be based on , and …
| Category | (%) | () | (%) | () | ||
|---|---|---|---|---|---|---|
| 22.6 | 25.5 | |||||
| 18.7 | 14.3 | |||||
| Simultaneous fit | – | – | – | – | ||
| Source | I | II | III | IV |
|---|---|---|---|---|
| Tracking | 2.7 | 2.7 | 2.8 | 2.8 |
| Photon | 1.0 | 2.0 | 1.0 | 2.0 |
| reconstruction | – | 1.0 | – | 1.0 |
| PID | 2.3 | 2.3 | 2.5 | 2.5 |
| Kinematic fit | 1.9 | 2.4 | 1.7 | 2.3 |
| Mass window | 4.9 | 1.8 | – | – |
| Branching fraction | 1.7 | 1.7 | 1.7 | 1.7 |
| Number of events | 0.7 | 0.6 | ||
| Fit range | 1.4 | 0.6 | ||
| Signal shape | 3.9 | 1.2 | ||
| Background shape | 2.7 | 1.3 | ||
| Physics model | 1.5 | 3.4 | ||
| Sum | 7.2 | 5.4 | ||
| Ratio | ||
|---|---|---|
| (%) | ||
| 0.5 | 0.2 | |
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Observation of and improved measurement of
M. Ablikim1, M. N. Achasov10,d, S. Ahmed15, M. Albrecht4, M. Alekseev55A,55C, A. Amoroso55A,55C, F. F. An1, Q. An52,42, J. Z. Bai1, Y. Bai41, O. Bakina27, R. Baldini Ferroli23A, Y. Ban35, K. Begzsuren25, D. W. Bennett22, J. V. Bennett5, N. Berger26, M. Bertani23A, D. Bettoni24A, F. Bianchi55A,55C, E. Boger27,b, I. Boyko27, R. A. Briere5, H. Cai57, X. Cai1,42, O. Cakir45A, A. Calcaterra23A, G. F. Cao1,46, S. A. Cetin45B, J. Chai55C, J. F. Chang1,42, G. Chelkov27,b,c, G. Chen1, H. S. Chen1,46, J. C. Chen1, M. L. Chen1,42, P. L. Chen53, S. J. Chen33, X. R. Chen30, Y. B. Chen1,42, W. Cheng55C, X. K. Chu35, G. Cibinetto24A, F. Cossio55C, H. L. Dai1,42, J. P. Dai37,h, A. Dbeyssi15, D. Dedovich27, Z. Y. Deng1, A. Denig26, I. Denysenko27, M. Destefanis55A,55C, F. De Mori55A,55C, Y. Ding31, C. Dong34, J. Dong1,42, L. Y. Dong1,46, M. Y. Dong1,42,46, Z. L. Dou33, S. X. Du60, P. F. Duan1, J. Fang1,42, S. S. Fang1,46, Y. Fang1, R. Farinelli24A,24B, L. Fava55B,55C, S. Fegan26, F. Feldbauer4, G. Felici23A, C. Q. Feng52,42, E. Fioravanti24A, M. Fritsch4, C. D. Fu1, Q. Gao1, X. L. Gao52,42, Y. Gao44, Y. G. Gao6, Z. Gao52,42, B. Garillon26, I. Garzia24A, A. Gilman49, K. Goetzen11, L. Gong34, W. X. Gong1,42, W. Gradl26, M. Greco55A,55C, L. M. Gu33, M. H. Gu1,42, Y. T. Gu13, A. Q. Guo1, L. B. Guo32, R. P. Guo1,46, Y. P. Guo26, A. Guskov27, Z. Haddadi29, S. Han57, X. Q. Hao16, F. A. Harris47, K. L. He1,46, X. Q. He51, F. H. Heinsius4, T. Held4, Y. K. Heng1,42,46, Z. L. Hou1, H. M. Hu1,46, J. F. Hu37,h, T. Hu1,42,46, Y. Hu1, G. S. Huang52,42, J. S. Huang16, X. T. Huang36, X. Z. Huang33, Z. L. Huang31, T. Hussain54, W. Ikegami Andersson56, M, Irshad52,42, Q. Ji1, Q. P. Ji16, X. B. Ji1,46, X. L. Ji1,42, X. S. Jiang1,42,46, X. Y. Jiang34, J. B. Jiao36, Z. Jiao18, D. P. Jin1,42,46, S. Jin1,46, Y. Jin48, T. Johansson56, A. Julin49, N. Kalantar-Nayestanaki29, X. S. Kang34, M. Kavatsyuk29, B. C. Ke1, I. K. Keshk4, T. Khan52,42, A. Khoukaz50, P. Kiese26, R. Kiuchi1, R. Kliemt11, L. Koch28, O. B. Kolcu45B,f, B. Kopf4, M. Kornicer47, M. Kuemmel4, M. Kuessner4, A. Kupsc56, M. Kurth1, W. Kühn28, J. S. Lange28, P. Larin15, L. Lavezzi55C, S. Leiber4, H. Leithoff26, C. Li56, Cheng Li52,42, D. M. Li60, F. Li1,42, F. Y. Li35, G. Li1, H. B. Li1,46, H. J. Li1,46, J. C. Li1, J. W. Li40, K. J. Li43, Kang Li14, Ke Li1, Lei Li3, P. L. Li52,42, P. R. Li46,7, Q. Y. Li36, T. Li36, W. D. Li1,46, W. G. Li1, X. L. Li36, X. N. Li1,42, X. Q. Li34, Z. B. Li43, H. Liang52,42, Y. F. Liang39, Y. T. Liang28, G. R. Liao12, L. Z. Liao1,46, J. Libby21, C. X. Lin43, D. X. Lin15, B. Liu37,h, B. J. Liu1, C. X. Liu1, D. Liu52,42, D. Y. Liu37,h, F. H. Liu38, Fang Liu1, Feng Liu6, H. B. Liu13, H. L Liu41, H. M. Liu1,46, Huanhuan Liu1, Huihui Liu17, J. B. Liu52,42, J. Y. Liu1,46, K. Liu44, K. Y. Liu31, Ke Liu6, L. D. Liu35, Q. Liu46, S. B. Liu52,42, X. Liu30, Y. B. Liu34, Z. A. Liu1,42,46, Zhiqing Liu26, Y. F. Long35, X. C. Lou1,42,46, H. J. Lu18, J. G. Lu1,42, Y. Lu1, Y. P. Lu1,42, C. L. Luo32, M. X. Luo59, T. Luo9,j, X. L. Luo1,42, S. Lusso55C, X. R. Lyu46, F. C. Ma31, H. L. Ma1, L. L. Ma36, M. M. Ma1,46, Q. M. Ma1, T. Ma1, X. N. Ma34, X. Y. Ma1,42, Y. M. Ma36, F. E. Maas15, M. Maggiora55A,55C, S. Maldaner26, Q. A. Malik54, A. Mangoni23B, Y. J. Mao35, Z. P. Mao1, S. Marcello55A,55C, Z. X. Meng48, J. G. Messchendorp29, G. Mezzadri24B, J. Min1,42, T. J. Min33, R. E. Mitchell22, X. H. Mo1,42,46, Y. J. Mo6, C. Morales Morales15, N. Yu. Muchnoi10,d, H. Muramatsu49, A. Mustafa4, Y. Nefedov27, F. Nerling11, I. B. Nikolaev10,d, Z. Ning1,42, S. Nisar8, S. L. Niu1,42, X. Y. Niu1,46, S. L. Olsen46, Q. Ouyang1,42,46, S. Pacetti23B, Y. Pan52,42, M. Papenbrock56, P. Patteri23A, M. Pelizaeus4, J. Pellegrino55A,55C, H. P. Peng52,42, Z. Y. Peng13, K. Peters11,g, J. Pettersson56, J. L. Ping32, R. G. Ping1,46, A. Pitka4, R. Poling49, V. Prasad52,42, H. R. Qi2, M. Qi33, T. Y. Qi2, S. Qian1,42, C. F. Qiao46, N. Qin57, X. S. Qin4, Z. H. Qin1,42, J. F. Qiu1, S. Q. Qu34, K. H. Rashid54,i, C. F. Redmer26, M. Richter4, M. Ripka26, A. Rivetti55C, M. Rolo55C, G. Rong1,46, Ch. Rosner15, A. Sarantsev27,e, M. Savrié24B, K. Schoenning56, W. Shan19, X. Y. Shan52,42, M. Shao52,42, C. P. Shen2, P. X. Shen34, X. Y. Shen1,46, H. Y. Sheng1, X. Shi1,42, J. J. Song36, W. M. Song36, X. Y. Song1, S. Sosio55A,55C, C. Sowa4, S. Spataro55A,55C, G. X. Sun1, J. F. Sun16, L. Sun57, S. S. Sun1,46, X. H. Sun1, Y. J. Sun52,42, Y. K Sun52,42, Y. Z. Sun1, Z. J. Sun1,42, Z. T. Sun1, Y. T Tan52,42, C. J. Tang39, G. Y. Tang1, X. Tang1, I. Tapan45C, M. Tiemens29, B. Tsednee25, I. Uman45D, B. Wang1, B. L. Wang46, C. W. Wang33, D. Wang35, D. Y. Wang35, Dan Wang46, K. Wang1,42, L. L. Wang1, L. S. Wang1, M. Wang36, Meng Wang1,46, P. Wang1, P. L. Wang1, W. P. Wang52,42, X. F. Wang44, Y. Wang52,42, Y. F. Wang1,42,46, Z. Wang1,42, Z. G. Wang1,42, Z. Y. Wang1, Zongyuan Wang1,46, T. Weber4, D. H. Wei12, P. Weidenkaff26, S. P. Wen1, U. Wiedner4, M. Wolke56, L. H. Wu1, L. J. Wu1,46, Z. Wu1,42, L. Xia52,42, X. Xia36, Y. Xia20, D. Xiao1, Y. J. Xiao1,46, Z. J. Xiao32, Y. G. Xie1,42, Y. H. Xie6, X. A. Xiong1,46, Q. L. Xiu1,42, G. F. Xu1, J. J. Xu1,46, L. Xu1, Q. J. Xu14, Q. N. Xu46, X. P. Xu40, F. Yan53, L. Yan55A,55C, W. B. Yan52,42, W. C. Yan2, Y. H. Yan20, H. J. Yang37,h, H. X. Yang1, L. Yang57, R. X. Yang52,42, Y. H. Yang33, Y. X. Yang12, Yifan Yang1,46, Z. Q. Yang20, M. Ye1,42, M. H. Ye7, J. H. Yin1, Z. Y. You43, B. X. Yu1,42,46, C. X. Yu34, J. S. Yu30, J. S. Yu20, C. Z. Yuan1,46, Y. Yuan1, A. Yuncu45B,a, A. A. Zafar54, Y. Zeng20, B. X. Zhang1, B. Y. Zhang1,42, C. C. Zhang1, D. H. Zhang1, H. H. Zhang43, H. Y. Zhang1,42, J. Zhang1,46, J. L. Zhang58, J. Q. Zhang4, J. W. Zhang1,42,46, J. Y. Zhang1, J. Z. Zhang1,46, K. Zhang1,46, L. Zhang44, S. F. Zhang33, T. J. Zhang37,h, X. Y. Zhang36, Y. Zhang52,42, Y. H. Zhang1,42, Y. T. Zhang52,42, Yang Zhang1, Yao Zhang1, Yu Zhang46, Z. H. Zhang6, Z. P. Zhang52, Z. Y. Zhang57, G. Zhao1, J. W. Zhao1,42, J. Y. Zhao1,46, J. Z. Zhao1,42, Lei Zhao52,42, Ling Zhao1, M. G. Zhao34, Q. Zhao1, S. J. Zhao60, T. C. Zhao1, Y. B. Zhao1,42, Z. G. Zhao52,42, A. Zhemchugov27,b, B. Zheng53, J. P. Zheng1,42, W. J. Zheng36, Y. H. Zheng46, B. Zhong32, L. Zhou1,42, Q. Zhou1,46, X. Zhou57, X. K. Zhou52,42, X. R. Zhou52,42, X. Y. Zhou1, Xiaoyu Zhou20, Xu Zhou20, A. N. Zhu1,46, J. Zhu34, J. Zhu43, K. Zhu1, K. J. Zhu1,42,46, S. Zhu1, S. H. Zhu51, X. L. Zhu44, Y. C. Zhu52,42, Y. S. Zhu1,46, Z. A. Zhu1,46, J. Zhuang1,42, 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 Institute of Information Technology, Lahore, 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 University, Jinan 250100, People’s Republic of China
37 Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
38 Shanxi University, Taiyuan 030006, People’s Republic of China
39 Sichuan University, Chengdu 610064, People’s Republic of China
40 Soochow University, Suzhou 215006, People’s Republic of China
41 Southeast University, Nanjing 211100, People’s Republic of China
42 State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People’s Republic of China
43 Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
44 Tsinghua University, Beijing 100084, People’s Republic of China
45 (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
46 University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
47 University of Hawaii, Honolulu, Hawaii 96822, USA
48 University of Jinan, Jinan 250022, People’s Republic of China
49 University of Minnesota, Minneapolis, Minnesota 55455, USA
50 University of Muenster, Wilhelm-Klemm-Str. 9, 48149 Muenster, Germany
51 University of Science and Technology Liaoning, Anshan 114051, People’s Republic of China
52 University of Science and Technology of China, Hefei 230026, People’s Republic of China
53 University of South China, Hengyang 421001, People’s Republic of China
54 University of the Punjab, Lahore-54590, Pakistan
55 (A)University of Turin, I-10125, Turin, Italy; (B)University of Eastern Piedmont, I-15121, Alessandria, Italy; (C)INFN, I-10125, Turin, Italy
56 Uppsala University, Box 516, SE-75120 Uppsala, Sweden
57 Wuhan University, Wuhan 430072, People’s Republic of China
58 Xinyang Normal University, Xinyang 464000, People’s Republic of China
59 Zhejiang University, Hangzhou 310027, People’s Republic of China
60 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 Government College Women University, Sialkot - 51310. Punjab, Pakistan.
j Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics, Fudan University, Shanghai 200443, People’s Republic of China
Abstract
We observe the process for the first time, with a statistical significance higher than 10, and measure the branching fraction of with an improved accuracy compared to earlier studies. The measurements are based on and events collected by the BESIII detector operating at the BEPCII. The branching fractions are determined to be and , where the first uncertainties are statistical and the second ones systematic. Additionally, the mixing angle is determined to be based on , and based on , respectively.
pacs:
13.25.Gv, 12.38.Qk, 14.40.Pq, 14.40Be
I INTRODUCTION
Quantum Chromodynamics (QCD), the theory describing the strong interaction, has been tested thoroughly at high energy. However, in the medium energy region, theoretical calculations based on first principles are still unreliable since the non-perturbative contribution is significant and calculations have to rely on models. Experimental measurements in this energy region are helpful to validate or falsify models, constrain parameters, and inspire new calculations. Charmonium states are on the boundary between perturbative and non-perturbative regimes in QCD, therefore, their decays, especially the hadronic decays, provide ideal inputs to study the QCD. The availability of very large samples of vector charmonia, produced via electron-positron annihilation, such as and , makes experimental studies of rare processes and decay channels with complicated intermediate structures possible.
Among these hadronic decays, scenarios of (in the following, denotes either or ) decaying into baryon pairs have been understood via annihilation into three gluons or a virtual photon psi_to_BBbar . But its natural extension, the three-body decays, , where represents a pseudoscalar meson such as , , or , still need more studies since intermediate states contribute significantly here. Specific models based on nucleon and pole diagrams have been proposed to deal with these problems soft_pion_theorem ; nucleon_pole ; nucleon_resonance . However, recent studies have focused on the final states and , and not so much on , partially due to the limited experimental measurements.
The study of the process , as well as the branching fraction of , can also be used to determine the mixing angle . The mixing angle, which was proposed in quark model SU(3) flavor symmetry soft_pion_theorem , is expected to be based on a QCD inspired calculation soft_pion_theorem or based on the quark-line rule (QLR) quark-line-rule .
In addition, using the process , we are able to test the “12% rule”. The ratio of the branching fractions of and can be written in terms of their total and leptonic widths under the assumption that the charmonium systems are non-relativistic and decay to hadrons predominantly via point-like annihilation into three gluons 12_rule_01 ; Augustin:1974xw : rhopi_puzzle_mrkii . This relation was extended to exclusive processes later, ignoring other factors associated with each exclusive mode such as multiplicity and phase space factors. Although the “12% rule” has been confirmed experimentally for many decay modes, severe violation has been found in several channels rhopi_puzzle_mrkii . Many theoretical explanations rho_pi_rev have been proposed to explain the violation of the “12% rule”, but none is satisfactory.
The baryonic three-body decay was first observed by MARKI with branching fraction in 1978 jpsi_ppbetap_mrki and confirmed by MARKII with branching fraction in 1984 jpsi_ppbetap_mrkii . Later, using events, BESII performed a further measurement of the branching fraction of with jpsi_ppbetap_besii . The process has not been observed so far.
At present, two large samples of events psip_num and events jpsi_num have been collected with the BESIII detector. Using these large data sets, we present the first observation of and an improved measurement of the branching fraction of . In this analysis, the candidates are reconstructed via their decays and .
II BESIII DETECTOR AND DATA SAMPLES
The BESIII detector, described in detail in Ref. detail_bepcii , has a geometrical acceptance of 93% of 4 solid angle. It can be subdivided into four main sub-detectors. A helium-based multi-layer drift chamber (MDC) determines the momentum of charged particles, traveling through a 1 T (for sample 0.9 T in 2012) magnetic field, with a resolution 0.5% at 1 GeV/, as well as the ionization energy loss (d/d) with a resolution better than 6.0% for electrons from Bhabha scattering. A time-of-flight system (TOF) made of plastic scintillators with a time resolution of 80 ps (110 ps) in the barrel (end caps) is used for particle identification (PID). An electromagnetic calorimeter (EMC) consisting of 6240 CsI(Tl) crystals measures the energies of photons with a resolution of 2.5% (5.0%) in the barrel (end caps) at 1 GeV, and their positions with a resolution of 6 mm (9 mm) in the barrel (end caps). A muon counter (MUC) based on resistive plate chambers with 2 cm position resolution provides information for muon identification.
A geant4-based geant4_01 ; geant4_02 detector simulation package is used to model the detector response. Inclusive Monte Carlo (MC) samples, including and events, are used for background studies. The production of the and resonances is simulated using the event generator kkmc kkmc_01 ; kkmc_02 , and their decays are simulated by evtgen evtgen for those with a known branching fraction obtained from the Particle Data Group (PDG) pdg_2014 and by the lundcharm model lundcharm for unmeasured ones. Signal MC samples are generated to determine the detection efficiency and to optimize selection criteria. The , , and are generated according to phase space (PHSP) distributions, while according to the model-dependent amplitudes determined in Ref. diy_test3 . Data samples taken at center-of-mass energies and GeV with integrated luminosities of pb*-1* and pb*-1*, respectively, are used to estimate continuum backgrounds.
III EVENT SELECTIONS AND BACKGROUND ANALYSIS
Charged tracks are reconstructed from hits in the MDC. For each track, the polar angle must satisfy and the point of closest approach to the interaction point must be within cm in the plane perpendicular to the beam and cm along the beam direction. The TOF and d/d information is combined to calculate PID likelihoods for the pion and proton hypotheses, and the PID hypothesis with the largest likelihood is assigned to the track.
Photons are reconstructed from isolated electromagnetic showers in the EMC. The angle between the directions of any cluster and its nearest charged track must be larger than 10 or 30 degrees to pion or (anti-)proton tracks, respectively. The efficiency and energy resolution are improved by including the energy deposited in nearby TOF counters. A photon candidate must deposit at least 25 MeV (50 MeV) in the barrel (end caps) region, corresponding to an angular coverage of (). The timing information obtained from the EMC is required to be ns to suppress electronic noise and beam backgrounds unrelated to the event.
Signal candidates must have four charged tracks identified as , , and , as well as at least one (two) photon(s) for the mode. The events with MeV/ are accepted for further analysis, where is the invariant mass of or , respectively. To improve the resolution and to suppress backgrounds, a kinematic fit to all final state particles with a constraint on the initial four-momentum is performed. In addition, for the mode, the invariant mass of the two photons is constrained to the nominal mass of . The of the kinematic fit for each decay mode is required to be less than an optimized value obtained by maximizing the figure of merit , where is the number of signal events from a signal MC sample normalized to the preliminary measurements and is the number of background events in the signal region obtained from inclusive MC samples. When there are more photon candidates than required in an event, we loop over all possible combinations and keep the one with the smallest kinematic fit . After the kinematic fit, the signal region is defined as MeV/, while the sideband regions are defined as MeV/ and MeV/.
To remove background events, we apply the following requirements:
- •
For with , we veto ( = 0, 1, 2) decays by requiring MeV/, MeV/ and MeV/, and veto decays by requiring MeV/.
- •
For with , we veto decays by requiring MeV/, and veto decays by requiring MeV/.
Here, , , and are the recoil mass of , , and , while and are the nominal and masses pdg_2014 , respectively. The mass window for each requirement is determined based on the exclusive MC simulation.
The backgrounds from and decays are studied with inclusive MC samples. For with , even after the mass window requirements, the main remaining background is the decay with , which has the same final state as the signal process. A study of MC simulated events shows that the distribution from is smooth. Therefore, its contribution can be easily determined in a fit. For the other three decay modes, with , with and , there are no dominant background processes, but many decay channels with a small contribution each. The backgrounds from the continuum process are studied with data samples taken at and GeV. The background level is found to be very low, and the background events do not peak in the signal region.
The and distributions of the events that pass all selection criteria are shown in Fig. 1. Peaks originating from decays are observed. Figure 2 shows the Dalitz plots of the events in the signal region, and Figs. 3 and 4 show the invariant mass projections, where the side band backgrounds have been subtracted. Based on these plots, no obvious intermediate structures in invariant mass of , , or are observed.
IV SIGNAL YIELDS AND BRANCHING FRACTIONS
To determine the branching fractions, simultaneous unbinned maximum likelihood fits to the and invariant mass spectra are performed for the data and for the data. The signal shape is represented by the MC-simulated mass distribution, convolved with a Gaussian function with free mean and width to account for the mass and resolution difference between data and MC simulation. The background is parameterized as a second-order Chebyshev polynomial with free parameters. In the simultaneous fit, the ratio of the number of events to that of events is fixed to , where and are the global efficiencies for each decay mode. Due to differences in tracking and PID efficiencies between data and MC simulation for protons and anti-protons, the MC-determined global efficiencies are corrected by multiplying factors 1.030 (1.038) and 0.980 (0.984) for tracking and PID, respectively, for (). These correction factors are ratios of efficiencies between data and MC simulation obtained by studying the control samples , where the efficiencies are weighted according to the distributions of transverse momentum (for tracking) or momentum (for PID) of protons and anti-protons.
The results of the fits are listed in Table 1 and shown in Fig. 1. The goodness of the fit is for with , for with , for with , and for with . The resolution difference between data and MC simulation is 1 MeV in each decay mode. The branching fractions are determined to be
[TABLE]
Here the first uncertainties are statistical and the second ones systematic, as discussed in Sec. V. As a cross check, we also fit these channels separately, and Table 1 lists the signal yields, the selection efficiencies, and the branching fractions obtained for each decay mode. The branching fractions obtained from the simultaneous and separate fits are consistent with each other.
V SYSTEMATIC UNCERTAINTIES
The systematic uncertainties mainly come from the MDC tracking, photon and reconstruction, PID, kinematic fit, mass windows, branching fractions of the decay modes used to reconstruct the , the number of decays, fitting procedure, and the physics model used to determine the efficiency. All the contributions are given in Table 2. The overall systematic uncertainties are obtained by adding all systematic uncertainties, taking the correlations into account.
The uncertainty in the MDC tracking efficiency for each pion is estimated with the control sample , and a 1.0% systematic uncertainty per pion is obtained tracking_pion . This gives a total of 2.0% for each decay mode. The tracking efficiencies of protons and anti-protons are studied with the control sample . The MC efficiencies for the signal processes are corrected using the results from the control samples, and the uncertainties of the tracking differences between data and MC simulation are taken as the systematic uncertainties, which are 0.7% (1.0%) per proton (anti-proton) for the decays, and 0.9% (1.0%) per proton (anti-proton) for the decays. Assuming the uncertainties of proton and anti-proton are totally correlated, the tracking uncertainty of a proton–anti-proton pair is 1.7% (1.9%) for the () data sample. The tracking efficiencies of pion and proton are independent, and the total tracking uncertainty is determined to be 2.7% (2.8%) for the () samples.
The uncertainty in the photon reconstruction is studied by using the control sample , and a 1.0% systematic uncertainty is estimated for each photon photon_rec . The uncertainty of the reconstruction from final state is 1.0% per , as determined from a high purity control sample of eta-rec .
The uncertainty in the PID efficiency for pions is estimated to be 1.0% per pion pid_pion , and the total PID uncertainty for two pions is 2.0% for each decay mode. The efficiencies of the proton and the anti-proton identification are studied with the control samples . The MC efficiencies for the signal processes are corrected using the results from the control samples, and the uncertainties of the corrections are taken as the systematic uncertainties, which are 0.5% (0.6%) per proton (anti-proton) for the , and 0.6% (0.8%) per proton (anti-proton) for the samples. Assuming the uncertainties of proton and anti-proton are totally correlated, the PID uncertainty of a proton and anti-proton pair is calculated to be 1.1%(1.4%) for the () data samples. The PID efficiencies of pion and proton are independent, and the total PID uncertainty is determined to be 2.3% (2.5%) for the () samples.
The uncertainty associated with the kinematic fit is estimated by comparing the efficiencies with or without a helix parameter correction applied to simulated data bib23 . Control samples and bib24 are used to obtain the correction to the track helix parameters. The uncertainties due to the kinematic fit are determined to be 1.9%, 2.4%, 1.7%, and 2.3%, for with , and with , with , and with , respectively.
The uncertainty due to the mass windows used to veto background events originates from the differences in the mass resolutions between data and MC simulation. We repeat the analysis by enlarging or reducing the mass window. The largest difference is used as an estimate of the corresponding systematic uncertainty. The signal region and sideband regions are not used to veto the background events, so they have no effect on the branching fraction determination. The uncertainties due to different mass windows are considered to be independent, so we add them in quadrature. For the decay with (), the uncertainty is 4.9% (1.8%). The uncertainty for the mass-window selection for is found negligible.
The systematic uncertainties due to the branching fractions of the subsequent and decays are 1.7% for decays and pdg_2014 . The numbers of and events have been estimated via inclusive hadronic events with relative uncertainties of 0.7% psip_num and 0.6% jpsi_num , respectively.
The fit range, signal shape, and background shape are considered as the sources of the systematic uncertainty related with the fit procedure. In the nominal fit, the mass range is GeV/, and we repeat the fit by changing the range by 10 MeV/. The largest change in the final result is taken as the uncertainty due to the fit range, which is 1.4% and 0.6% for and , respectively. For the signal shape, we change the nominal shape to a double-Gaussian or a Breit-Wigner function convolved with a Gaussian function, and the largest difference from the nominal result is taken as the uncertainty of the signal shape, which is 3.9% and 1.2% for and , respectively. We replace the background shape with a first-order Chebyshev or second-order polynomial function, the largest differences from the nominal result, 2.7% and 1.3% for and , respectively, are taken as systematic uncertainties.
The signal MC sample is generated assuming pure phase space distribution, in which possible intermediate states and non-flat angular distributions are ignored. Although no strong structure is visible in the Dalitz plots shown in Fig. 2, the phase space MC does not provide a very good description of the data, as shown in Fig. 3 and Fig. 4, which results in a large systematic uncertainty, especially for the decay modes. For , since the statistics are limited, we weight each MC-generated phase space event by the distribution, and a difference of 1.5% in the efficiency between the nominal and weighted MC samples is taken as the uncertainty. For , we re-generate signal MC events based on body3 Ablikim:2014dqd , a data-driven MC generator, and a difference of 3.4% in the efficiencies is taken as the uncertainty.
VI SUMMARY AND DISCUSSION
Based on decays, we observe for the first time , and measure its branching fraction to be . Based on decays, we obtain the most accurate measurement so far of .
With the measurement of pdg_2014 , we determine the ratio of decay widths . It is larger than the nucleon pole contribution by two orders of magnitude according to Ref. nucleon_pole . This implies the validity of the pole hypothesis. However, from the invariant mass distributions of and in Fig. 4, no distinctive structure is observed, which indicates that very broad intermediate states or other decay mechanisms are needed to explain the large ratio. Similarly, using the results in Ref. psip_to_NN , we determine the ratio , where common uncertainties have been cancelled. This ratio will helpful for future studies of the nucleon and pole contributions in baryonic decays.
Combining our result with the branching fractions of reported in Ref. pdg_2014 and following the procedure described in Ref. soft_pion_theorem , we determine an mixing angle of for the decays and for the decays. We observe that the two values are very similar, even though the uncertainties are in both cases very large. This might indicate a universal behavior of the mixing angle as expected. These results are consistent with the QCD-inspired calculations soft_pion_theorem , and based on the quark-line rule quark-line-rule .
Table 3 shows the details for the ratios of branching fractions, three-body phase space factors, and determined matrix elements. The ratios of the matrix elements are consistent with the theoretical prediction that falls within the range according to Ref. soft_pion_theorem .
Our results for the branching fractions of and result in the ratio , where the common uncertainties have been canceled. Even though the ratio is in reasonabe agreement with 12%, we note that the kinematics of the two processes are very different, and the “12% rule” may be too naive in this case. The phase space ratio is , if any possible intermediate structure is ignored. Furthermore, the Dalitz plots of and decays, shown in Fig. 2, indicate that many events in decays, possibly via intermediate states with or mass greater than 2.13 GeV/, are not kinematically possible in decays. Taken these factors into account, the value is suppressed a lot, implying that the “12% rule” is violated significantly.
VII 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 Contracts Nos. 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 Swedish Research Council; U. S. Department of Energy under Contracts Nos. DE-FG02-05ER41374, DE-SC-0010118, DE-SC-0010504, DE-SC-0012069; University of Groningen (RuG) and the Helmholtzzentrum fuer Schwerionenforschung GmbH (GSI), Darmstadt.
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