Cross section measurements of $e^{+}e^{-} \to K^{+}K^{-}K^{+}K^{-} $ and $ \phi K^{+}K^{-}$ at center-of-mass energies from 2.10 to 3.08 GeV
BESIII Collaboration: 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, I. Balossino Balossino, Y. Ban, K. Begzsuren, J., V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi

TL;DR
This study measures the cross sections of specific electron-positron annihilation processes involving kaons at energies from 2.10 to 3.08 GeV, revealing an enhancement near 2.232 GeV close to the Lambda-antLambda threshold.
Contribution
First measurement of these cross sections in this energy range, identifying an enhancement near 2.232 GeV and comparing energy dependence with related processes.
Findings
Observation of an enhancement at 2.232 GeV near Lambda-antLambda threshold
Different energy dependence compared to e+e- → φ π+π−
Cross section measurements for e+e- → K+K−K+K− and φK+K−
Abstract
We measure the Born cross sections of the process at center-of-mass (c.m.) energies, , between 2.100 and 3.080 GeV. The data were collected using the BESIII detector at the BEPCII collider. An enhancement at GeV is observed, very close to the production threshold. A similar enhancement at the same c.m. energy is observed in the cross section. The energy dependence of the and cross sections differs significantly from that of .
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Cross section measurements of and at center-of-mass energies from 2.10 to 3.08 GeV
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, I. Balossino Balossino24A, 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, M. Himmelreich11,g, 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, 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, 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, L. Y. Liu13, 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, C. F. Redmer26, M. Richter4, 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, Z. H. 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
We measure the Born cross sections of the process at center-of-mass (c.m.) energies, , between 2.100 and 3.080 GeV. The data were collected using the BESIII detector at the BEPCII collider. An enhancement at GeV is observed, very close to the production threshold. A similar enhancement at the same c.m. energy is observed in the cross section. The energy dependence of the and cross sections differs significantly from that of .
pacs:
13.25.Gv, 12.38.Qk, 14.20.Gk, 14.40.Cs
I Introduction
The resonance, denoted previously as , was first observed by BABAR in the process Y2175BABAR11 via initial-state radiation (ISR) and was confirmed by Belle Y2175BELLE . BES Y2175BESII and BESIII Y2175BESIII ; Y2175BESIII2019 also observed the in the invariant-mass spectrum. The discovery of bound states is of interest for the understanding of the strangeonium spectrum, which is less well understood than for example the hidden-charm states (). The CLEO Collaboration found the first evidence for Y4260 above the -production threshold. A similar process, , potentially allows the study of strangeonium-like vector states above the -production threshold.
Many theoretical interpretations have been proposed for the , such as a hybrid Y2175hybrid , a state Y2175ss2D , a tetraquark state Y2175tetraquark1 ; Y2175tetraquark2 , a bound state Y2175lambda ; Y2175lambda2 , or a three-meson system X2170 . The hybrid can decay to , with a cascade Others , whereby may make a significant contribution. However, none of the theoretical models has so far been able to describe all experimental observations in all aspects. Searching for new decay modes and measuring the line shapes of their production cross sections will be very helpful for interpreting the internal structure of the resonance.
The BABAR Collaboration measured the cross sections and observed an enhancement around 2.3 GeV Y2175BABAR1 ; Y2175BABAR2 . In addition, the BES Collaboration observed the , and in the invariant-mass distribution of pairs in events in which the other pair has an invariant mass close to the nominal mass JpsiToPhiKK . An enhancement at GeV was seen in the line shape of the process Y2175BABAR2 , but due to poor statistics, no strong conclusion could be drawn from the data. Torres et al. have performed a Faddeev calculation for the three-meson system and obtained a peak around 2.150 GeV/ X2170 . These observations stimulate experimentalists to study the energy dependence for the production of the and final states.
Using a data sample corresponding to an integrated luminosity of 650 collected at center-of-mass (c.m.) energies from 2.0 GeV to 3.08 GeV LuminosityFinal , we present in this paper the results of a study of the reaction and its dominant intermediate process .
II Detector and data samples
The BESIII detector is a magnetic spectrometer BESIII located at the Beijing Electron Positron Collider (BEPCII) BEPCII . 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.
The optimization of event-selection criteria, the determination of detection efficiencies and the estimates of potential backgrounds are performed based on Monte Carlo (MC) simulations taking the various aspects of the experimental setup into account. The geant4-based Geant4 MC simulation software, which includes the geometric and material description of the BESIII detector, the detector response and digitization models, and the detector running conditions and performances, is used to generate the MC samples.
For the background study, the process is simulated by the MC event generator conexc ConExc , while the decays are generated by evtgen EVENTGEN1 ; BESEVENTGEN2 for known decay modes with branching fractions set to Particle Data Group (PDG) world-average values PDG and by luarlw LUARLW for the remaining unknown decays. MC samples of and processes are generated by babayaga 3.5 Babayaga . The signal MC samples from the phase-space models (PHSP) of and are generated at c.m. energies corresponding to the experimental values, where the line shape of the production cross section of the two processes is taken from the BABAR experiment Y2175BABAR2 and the signal detection efficiency is obtained by weighting the MC-generated PHSP sample to data according to the observed invariant-mass distribution.
III Event Selection and background analysis
III.1
Candidate events are required to have three or four charged tracks. Charged tracks are reconstructed from hits in the MDC within the polar angle range and are required to pass the interaction point within 10 cm along the beam direction and within 1 cm in the plane perpendicular to the beam. For each charged track, the TOF and the information are combined to form particle identification (PID) confidence levels (C.L.) for the , , and hypotheses. The particle type with the highest C.L. is assigned to each track. At least three kaons are required to be identified. The primary vertex of the event is reconstructed by three kaons. For events with four identified kaons, the combination with the smallest chi-square of the vertex fit is retained.
Figure 1 shows the momentum distribution of the three identified kaons for = 2.125 GeV after applying the above-mentioned selection criteria. The peak on the right-side of the spectrum stems from reducible QED background, dominated by the processes and . To suppress this background, the momenta of the identified particles are required to be less than 80% of the mean momentum of the colliding beams ().
III.2
For with , the final state is . The selection criteria for three or four kaons are the same as described in the previous subsection. In addition to the primary-vertex fit of the three kaons, a one-constraint (1C) kinematic fit is performed under the hypothesis that the missing mass corresponds to the kaon mass. For events with four reconstructed and identified kaons, the combination with the smallest chi-square of the 1C kinematic fit () is retained and required to be less than 20. In the following, the momentum is that obtained from the 1C kinematic fit and is used in invariant-mass calculations.
The open histogram in Fig. 2 shows the invariant-mass distribution for all pairs for the selected events (four entries per event) for data taken at GeV. The hatched histogram in the same figure corresponds to the distribution of the pair with a mass closest to the nominal mass. A prominent peak near the mass is seen in both histograms and indicates that the channel dominates the final states.
IV Signal yields
The signal yields of are obtained from unbinned maximum-likelihood fits to the recoil-mass () data. The signal is described by the line shape obtained from the MC simulation convolved with a Gaussian function, where the Gaussian function describes the difference in resolution between data and MC simulation. The background shape is parametrized by a second-order Chebyshev polynomial function. The parameters of the Gaussian function and the Chebyshev polynomial function are left free in the fit. The corresponding fit result for data taken at GeV is shown in Fig. 3.
To determine the signal yields of the process, an unbinned maximum-likelihood fit is performed to the spectra. The probability density function of the spectra for the is obtained from a -wave Breit-Wigner function convolved with a Gaussian function that accounts for the detector resolution. The -wave Breit-Wigner function is defined as
[TABLE]
[TABLE]
[TABLE]
[TABLE]
where is the nominal mass as specified by the PDG, is the momentum of the kaon in the rest frame of the system, is the momentum of the kaon at the nominal mass of the , and is the width of the . The angular momentum () is assumed to equal one, which is the lowest allowed given the parent and daughter spins, is the Blatt-Weisskopf form factor, and is the radius of the centrifugal barrier, whose value is taken to be 3 GeV/c-1 Blatt-Wdisskopf .
The background shape is described by an ARGUS function ArgusFunction . The parameters of the Gaussian function and the ARGUS function are left free in the fit. The corresponding fit result for data taken at GeV is shown in Fig. 4.
The same event selection criteria and fit procedure are applied to the other 19 data samples taken at different c.m. energies. The number of events for these samples are listed in Tables 1 and 2.
V Selection efficiency
V.1
The detection efficiency is obtained by MC simulations of the channel using PHSP. It is found that data deviate strongly from the PHSP MC distributions, as demonstrated by the histograms in Fig. 5, which show the non- pair invariant-mass distributions. Here, candidates are selected in the signal region and background from the side-band region shown in Fig. 4. The background in Fig. 5 is the distribution of the invariant mass of the remaining pair in the side-band event, and the data points are the invariant mass of the remaining pair of the candidates minus the background. To obtain a more accurate detection efficiency, the MC-generated events are weighted according to the observed (non- pair) invariant-mass distribution, where the weight factor is the ratio of the mass distribution between data and PHSP MC. The weighted PHSP MC distribution is consistent with the background-subtracted data, as shown by the solid histogram in Fig. 5. The detection efficiencies determined by using the weighted MC data and by using the PHSP MC data do not differ significantly. Therefore, the average detection efficiency does not strongly depend on the invariant mass.
V.2
The detection efficiency is determined using both the weighted PHSP MC and PHSP MC. The combined detection efficiency is given by
[TABLE]
where and denote the detection efficiency and the signal yields of the th mode, respectively. is the total signal yield obtained by fitting the recoil-mass data, is the signal yield, , and is the weighted detection efficiency for the final state. Figure 6 shows a comparison of the normalized momentum spectra of the kaon between the data and the weighted MC result for GeV.
VI Determination of the Born cross section
The Born cross section is calculated by
[TABLE]
where is the number of observed signal events, is the integrated luminosity, stands for , and is the ISR correction factor, which is obtained by a QED calculation ISR and by taking the line shape of the Born cross section measured by the BABAR experiment into account. The vacuum polarization factor is taken from a QED calculation with an accuracy of 0.5 VP , and is the detection efficiency. The branching fraction of the intermediate process (49.2 0.5) PDG is taken into account in the determination of the cross section of .
Both and are obtained from MC simulations of the signal reaction for each c.m. energy. In the conexc generator, the cross section for the ISR process () is parametrized using
[TABLE]
where is the effective c.m. energy of the final state with , depends on the energy of the radiated photon according to , is the radiator function and describes the vacuum polarization (VP) effect. The latter includes contributions from leptons and quarks. The detection efficiency and the radiative-correction factor depend on the input cross section, and are determined by an iterative procedure, in which the line shape of the cross section from BABAR is used initially, and the updated Born cross section is obtained according to the simulation. We repeat the procedure until the measured Born cross section does not change by more than 0.5.
The values of , , and are listed in Table 1, together with the measured cross section at each energy point. Figures 7 (a) and 7 (b) show the line shapes of cross sections for and , respectively.
VII SYSTEMATIC UNCERTAINTY
Several sources of systematic uncertainties are considered in the measurement of the Born cross sections. These include the luminosity measurements, the differences between the data and the MC simulation for the tracking efficiency, PID efficiency, kinematic fit, the fit procedure, the MC simulation of the ISR-correction factor and the vacuum-polarization factor, as well as uncertainties in the branching fractions of the decays of intermediate states.
(a) Luminosity: The integrated luminosity of the data samples used in this analysis are measured using large-angle Bhabha scattering events, and the corresponding uncertainties are estimated to be LuminosityFinal .
(b) Tracking efficiency: The uncertainty of the tracking efficiency is investigated using a control sample of the process Liudong . The difference in tracking efficiency between data and the MC simulation is estimated to be 1 per track. Hence, is taken as the systematic uncertainty for the three selected kaons.
(c) PID efficiency: To estimate the uncertainty in the PID efficiency, we study PID efficiencies with the same control samples as those used in the tracking efficiency. The average difference in PID efficiency between data and the MC simulation is found to be 1 per charged track. Therefore, is taken as the systematic uncertainty for the three selected kaons.
(d) Kinematic fit: The uncertainty associated with the kinematic fits comes from the inconsistency of the track helix parameters between data and the MC simulation. The helix parameters for the charged tracks of MC samples are corrected to eliminate the inconsistency, as described in Ref. Aixiaocong , and the agreement of distributions between data and the MC simulation is significantly improved. We take the differences of the selection efficiencies with and without the correction as the systematic uncertainties.
(e) Fit procedure: A fit to mass spectrum of the recoiling kaon is performed to determine the signal yields of the process, and the two kaon invariant mass is fitted to determine the number of events. The following three aspects are considered when evaluating the systematic uncertainty associated with the fit procedure.
(1) Fit range: The spectrum of the recoiling kaon is fitted by varying the range from (0.3, 0.7) GeV/ to (0.31, 0.69) GeV/. The spectrum is fitted in the region from 0.98 to 1.15 GeV/. An alternative fit range, from 0.98 to 1.20 GeV/, is considered. The differences between the yields are treated as the systematic uncertainty from the fit range.
(2) Signal shape: The signal shape of the mass spectrum of the recoiling kaon is described by a shape obtained from a MC simulation convolved with a Gaussian function. The uncertainty related to this line shape is estimated with an alternative fit using the same line-shape function, but fixing the width of the Gaussian function to a value differing by one standard deviation from the width obtained in the nominal fit. The signal shape of the is described by a -wave Breit-Wigner function convolved with a Gaussian function. An alternative fit with a MC shape convolved with a Gaussian function is performed. The difference in yield between the various fits is considered as the systematic uncertainty from the signal shape.
(3) Background shape: The background shape of the mass spectrum for the recoiling kaon is described as a second-order Chebyshev polynomial function. A fit with a first-order Chebyshev polynomial function for the background shape is used to estimate its uncertainty. The background shape for -mass distribution is described by an ARGUS function. The fit with a function of , where, and are the lower and upper edges of the mass distribution, is used to estimate this uncertainty.
(f) ISR factor: The cross section is measured by iterating until converges, and the difference between the last two iterations is taken as the systematic uncertainty associated with the ISR-correction factor.
(g) VP factor: The uncertainty on the calculation of the VP factor is 0.5 VP .
(h) Branching fraction: The experimental uncertainties in the branching fraction for the process are taken from the PDG PDG .
(i) Weighted detection efficiency: The detection efficiencies obtained in different processes are combined using the previously-described method. The combined uncertainty is calculated by accounting for the statistical variation, by one standard deviation, of the signal yields.
To obtain a reliable detection efficiency of , the PHSP MC sample 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, which are produced by sampling the signal yield and its statistical uncertainty of the data in each bin, are used to estimate the detection efficiencies.
(j) MC statistics: The uncertainty is estimated by the number of the generated events, whereby the weighting factor has been taken into account.
(k) Other systematic uncertainties: Other sources of systematic uncertainties include the trigger efficiency, the determination of the start time of an event, and the modeling of the final-state radiation in the simulation. The total systematic uncertainty due to these sources is estimated to be less than . To be conservative, we take 1.0 as its systematic uncertainty.
Assuming all of the above systematic uncertainties, shown in Tables 3 and 4, are independent, the total systematic uncertainties are obtained by adding the individual uncertainties in quadrature.
VIII Summary and Discussion
In summary, using data collected with the BESIII detector taken at twenty c.m. energies from 2.100 to 3.080 GeV, we present measurements of the processes and and we obtain the corresponding Born cross sections. The Born cross sections of the process are in good agreement with the results by BABAR, but with improved precision. The Born cross sections for the channel are measured for the first time at twenty energy points. Both data sets reveal anomalously high cross sections at GeV.
A previous analysis on a much smaller dataset JpsiToPhiKK has demonstrated that the final state exhibits resonant substructure. It is difficult to disentangle these contributions from other final states, and we make no attempt to do so.
By examining the cross section as a function of c.m. energy, an enhancement at = 2.232 GeV, i.e. near the production threshold, is observed. The cross section of is also found to be anomalously high at the threshold LambdaAntiLambdaXiaorongZhou . In the case of charged baryons one would expect a Coulomb enhancement factor, which, however, is absent in the of the electrically-neutral . It has been suggested that a narrow resonance, very close to the threshold, might provide an explanation FormFactorOfLambda . BABAR has observed an enhancement at 2.175 GeV and a sharp peak at 2.3 GeV, corresponding to final states with invariant masses smaller than 1.06 GeV/ and within a mass interval of 1.061.2 GeV/, respectively. The intriguing resonance X2170 has a relatively wide width and it is very close to the kinematical threshold, but not close enough to be related to the observed anomaly. Alternatively, the enhancement at 2.232 GeV could be explained by an interference effect of different resonances. More data in the vicinity would be helpful to understand the anomaly.
IX acknowledgments
The BESIII collaboration thanks the staff of BEPCII and the IHEP computing center and the supercomputing center of USTC 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. 11625523, 11635010, 11735014, 11425524, 11335008, 11375170, 11475164, 11475169, 11605196, 11605198, 11705192; National Natural Science Foundation of China (NSFC) under Contract No. 11835012; the Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program; Joint Large-Scale Scientific Facility Funds of the NSFC and CAS under Contracts Nos. U1532257, U1532258, U1732263, U1832207, U1532102, U1732263, U1832103; 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 Swedish Research Council; U. S. Department of Energy under Contracts Nos. DE-FG02-05ER41374, DE-SC-0010118, DE-SC-0012069, DE-SC-0010504; University of Groningen (RuG) and the Helmholtzzentrum fuer Schwerionenforschung GmbH (GSI), Darmstadt
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