Amplitude analysis of $D_{s}^{+} \rightarrow \pi^{+}\pi^{0}\eta$ and first observation of the pure $W$-annihilation decays $D_{s}^{+} \rightarrow a_{0}(980)^{+}\pi^{0}$ and $D_{s}^{+} \rightarrow a_{0}(980)^{0}\pi^{+}$
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, Y. Ban, K. Begzsuren, J. V. Bennett, N. Berger, M. Bertani, D., Bettoni, F. Bianchi, J Biernat, J. Bloms, I. Boyko

TL;DR
This paper presents the first amplitude analysis of the decay $D_{s}^{+} ightarrow \,pi^{+}\,pi^{0}\,eta$, observing pure $W$-annihilation decays and measuring their branching fractions with improved precision, revealing larger decay rates than previously known.
Contribution
The study reports the first observation of pure $W$-annihilation decays $D_{s}^{+} ightarrow a_{0}(980)^{+}\,pi^{0}$ and $D_{s}^{+} ightarrow a_{0}(980)^{0}\,pi^{+}$, with measured branching fractions.
Findings
First amplitude analysis of $D_{s}^{+} ightarrow \,pi^{+}\,pi^{0}\,eta$
Observation of pure $W$-annihilation decays with larger branching fractions
Improved measurement of $D_{s}^{+} ightarrow \,pi^{+}\,pi^{0}\,eta$ branching fraction
Abstract
We present the first amplitude analysis of the decay . We use an collision data sample corresponding to an integrated luminosity of 3.19~ collected with the BESIII detector at a center-of-mass energy of GeV. We observe for the first time the pure -annihilation decays and . We measure the absolute branching fractions \%, which is larger than the branching fractions of other measured pure -annihilation decays by at least one order of magnitude. In addition, we measure the branching fraction of with significantly…
| Amplitude | (rad) | FFn |
|---|---|---|
| 0.0 (fixed) | ||
| Amplitude | Source | ||||||
| I | II | III | IV | V | Total | ||
| FF | 0.06 | 0.34 | 0.13 | 0.12 | 0.15 | 0.41 | |
| 1.97 | 0.18 | 0.03 | 0.17 | 1.99 | |||
| FF | 0.61 | 1.03 | 0.12 | 0.06 | 0.08 | 1.21 | |
| 0.41 | 0.07 | 0.28 | 0.09 | 0.51 | |||
| FF | 0.58 | 1.31 | 0.02 | 0.06 | 0.11 | 1.45 | |
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Amplitude analysis of
and first observation of the pure -annihilation decays and
M. Ablikim1, M. N. Achasov10,d, S. Ahmed15, M. Albrecht4, M. Alekseev56A,56C, A. Amoroso56A,56C, F. F. An1, Q. An53,43, J. Z. Bai1, Y. Bai42, O. Bakina27, R. Baldini Ferroli23A, Y. Ban35, K. Begzsuren25, J. V. Bennett5, N. Berger26, M. Bertani23A, D. Bettoni24A, F. Bianchi56A,56C, E. Boger27,b, I. Boyko27, R. A. Briere5, H. Cai58, X. Cai1,43, A. Calcaterra23A, G. F. Cao1,47, N. Cao1,47, S. A. Cetin46B, J. Chai56C, J. F. Chang1,43, G. Chelkov27,b,c, G. Chen1, H. S. Chen1,47, J. C. Chen1, M. L. Chen1,43, S. J. Chen33, X. R. Chen30, Y. B. Chen1,43, W. Cheng56C, X. K. Chu35, G. Cibinetto24A, F. Cossio56C, X. F. Cui34, H. L. Dai1,43, J. P. Dai38,h, A. Dbeyssi15, D. Dedovich27, Z. Y. Deng1, A. Denig26, I. Denysenko27, M. Destefanis56A,56C, F. De Mori56A,56C, Y. Ding31, C. Dong34, J. Dong1,43, L. Y. Dong1,47, M. Y. Dong1,43,47, S. X. Du61, J. Fang1,43, S. S. Fang1,47, Y. Fang1, R. Farinelli24A,24B, L. Fava56B,56C, F. Feldbauer4, G. Felici23A, C. Q. Feng53,43, M. Fritsch4, C. D. Fu1, Q. Gao1, X. L. Gao53,43, Y. Gao45, Y. Gao54, Y. G. Gao6, Z. Gao53,43, B. Garillon26, I. Garzia24A, A. Gilman50, K. Goetzen11, L. Gong34, W. X. Gong1,43, W. Gradl26, M. Greco56A,56C, M. H. Gu1,43, Y. T. Gu13, A. Q. Guo1, R. P. Guo1,47, Y. P. Guo26, A. Guskov27, S. Han58, X. Q. Hao16, F. A. Harris48, K. L. He1,47, X. Q. He52, 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. Huang53,43, J. S. Huang16, X. T. Huang37, Z. L. Huang31, T. Hussain55, W. Ikegami Andersson57, W. Imoehl22, M, Irshad53,43, Q. Ji1, Q. P. Ji16, X. B. Ji1,47, X. L. Ji1,43, X. S. Jiang1,43,47, X. Y. Jiang34, J. B. Jiao37, Z. Jiao18, D. P. Jin1,43,47, S. Jin1,47, Y. Jin49, T. Johansson57, N. Kalantar-Nayestanaki29, X. S. Kang34, R. Kappert29, M. Kavatsyuk29, B. C. Ke1, I. K. Keshk4, T. Khan53,43, A. Khoukaz51, P. Kiese26, R. Kiuchi1, R. Kliemt11, L. Koch28, O. B. Kolcu46B,f, B. Kopf4, M. Kuemmel4, M. Kuessner4, A. Kupsc57, M. Kurth1, M. G. Kurth1,47, W. Kühn28, J. S. Lange28, P. Larin15, L. Lavezzi56C, H. Leithoff26, C. Li57, Cheng Li53,43, D. M. Li61, F. Li1,43, F. Y. Li35, G. Li1, H. B. Li1,47, H. J. Li1,47, J. C. Li1, J. W. Li41, Jin Li36, K. J. Li44, Kang Li14, Ke Li1, L. K. Li1, Lei Li3, P. L. Li53,43, P. R. Li47,7, Q. Y. Li37, W. D. Li1,47, W. G. Li1, X. L. Li37, X. N. Li1,43, X. Q. Li34, Z. B. Li44, H. Liang53,43, H. Liang1,47, Y. F. Liang40, Y. T. Liang28, G. R. Liao12, L. Z. Liao1,47, J. Libby21, C. X. Lin44, D. X. Lin15, B. Liu38,h, B. J. Liu1, C. X. Liu1, D. Liu53,43, D. Y. Liu38,h, F. H. Liu39, Fang Liu1, Feng Liu6, H. B. Liu13, H. M. Liu1,47, Huanhuan Liu1, Huihui Liu17, J. B. Liu53,43, J. Y. Liu1,47, K. Y. Liu31, Ke Liu6, L. D. Liu35, Q. Liu47, S. B. Liu53,43, 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. G. Lu1,43, Y. Lu1, Y. P. Lu1,43, C. L. Luo32, M. X. Luo60, T. Luo9,j, X. L. Luo1,43, S. Lusso56C, X. R. Lyu47, F. C. Ma31, H. L. Ma1, L. L. Ma37, M. M. Ma1,47, Q. M. Ma1, T. Ma1, X. N. Ma34, X. Y. Ma1,43, Y. M. Ma37, F. E. Maas15, M. Maggiora56A,56C, S. Maldaner26, Q. A. Malik55, A. Mangoni23B, Y. J. Mao35, Z. P. Mao1, S. Marcello56A,56C, Z. X. Meng49, J. G. Messchendorp29, G. Mezzadri24B, J. Min1,43, R. E. Mitchell22, X. H. Mo1,43,47, Y. J. Mo6, C. Morales Morales15, N. Yu. Muchnoi10,d, H. Muramatsu50, A. Mustafa4, Y. Nefedov27, F. Nerling11, I. B. Nikolaev10,d, Z. Ning1,43, S. Nisar8, S. L. Niu1,43, X. Y. Niu1,47, S. L. Olsen36,k, Q. Ouyang1,43,47, S. Pacetti23B, Y. Pan53,43, M. Papenbrock57, P. Patteri23A, M. Pelizaeus4, J. Pellegrino56A,56C, H. P. Peng53,43, K. Peters11,g, J. Pettersson57, J. L. Ping32, R. G. Ping1,47, A. Pitka4, R. Poling50, V. Prasad53,43, M. Qi33, T. .Y. Qi2, S. Qian1,43, C. F. Qiao47, N. Qin58, X. S. Qin4, Z. H. Qin1,43, J. F. Qiu1, S. Q. Qu34, K. H. Rashid55,i, C. F. Redmer26, M. Richter4, M. Ripka26, A. Rivetti56C, V. Rodin29, M. Rolo56C, G. Rong1,47, Ch. Rosner15, A. Sarantsev27,e, M. Savrié24B, K. Schoenning57, W. Shan19, X. Y. Shan53,43, M. Shao53,43, C. P. Shen2, P. X. Shen34, X. Y. Shen1,47, H. Y. Sheng1, X. Shi1,43, J. J. Song37, X. Y. Song1, S. Sosio56A,56C, C. Sowa4, S. Spataro56A,56C, G. X. Sun1, J. F. Sun16, L. Sun58, S. S. Sun1,47, X. H. Sun1, Y. J. Sun53,43, Y. K Sun53,43, Y. Z. Sun1, Z. J. Sun1,43, Z. T. Sun22, Y. T Tan53,43, C. J. Tang40, G. Y. Tang1, X. Tang1, B. Tsednee25, I. Uman46D, B. Wang1, D. Wang35, D. Y. Wang35, K. Wang1,43, L. L. Wang1, L. S. Wang1, M. Wang37, Meng Wang1,47, P. Wang1, P. L. Wang1, W. P. Wang53,43, X. L. Wang9,j, Y. Wang53,43, 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, S. P. Wen1, U. Wiedner4, M. Wolke57, L. H. Wu1, L. J. Wu1,47, Z. Wu1,43, L. Xia53,43, Y. Xia20, S. Y. Xiao1, Y. J. Xiao1,47, Z. J. Xiao32, Y. G. Xie1,43, Y. H. Xie6, X. A. Xiong1,47, Q. L. Xiu1,43, G. F. Xu1, J. J. Xu1,47, L. Xu1, Q. J. Xu14, X. P. Xu41, F. Yan54, L. Yan56A,56C, W. B. Yan53,43, W. C. Yan2, Y. H. Yan20, H. J. Yang38,h, H. X. Yang1, L. Yang58, R. X. Yang53,43, 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. Yu30, J. S. Yu20, C. Z. Yuan1,47, Y. Yuan1, A. Yuncu46B,a, A. A. Zafar55, 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. Zhang59, J. Q. Zhang4, J. W. Zhang1,43,47, J. Y. Zhang1, J. Z. Zhang1,47, K. Zhang1,47, L. Zhang45, T. J. Zhang38,h, X. Y. Zhang37, Y. Zhang53,43, Y. H. Zhang1,43, Y. T. Zhang53,43, Yang Zhang1, Yao Zhang1, Yi Zhang9,j, Z. H. Zhang6, Z. P. Zhang53, Z. Y. Zhang58, G. Zhao1, J. W. Zhao1,43, J. Y. Zhao1,47, J. Z. Zhao1,43, Lei Zhao53,43, Ling Zhao1, M. G. Zhao34, Q. Zhao1, S. J. Zhao61, T. C. Zhao1, Y. B. Zhao1,43, Z. G. Zhao53,43, A. Zhemchugov27,b, B. Zheng54, J. P. Zheng1,43, Y. H. Zheng47, B. Zhong32, L. Zhou1,43, Q. Zhou1,47, X. Zhou58, X. K. Zhou53,43, X. R. Zhou53,43, Xiaoyu Zhou20, Xu Zhou20, A. N. Zhu1,47, J. Zhu34, J. Zhu44, K. Zhu1, K. J. Zhu1,43,47, S. H. Zhu52, W. J. Zhu34, X. L. Zhu45, Y. C. Zhu53,43, 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 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 Seoul National University, Seoul, 151-747 Korea
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 Minnesota, Minneapolis, Minnesota 55455, USA
51 University of Muenster, Wilhelm-Klemm-Str. 9, 48149 Muenster, Germany
52 University of Science and Technology Liaoning, Anshan 114051, People’s Republic of China
53 University of Science and Technology of China, Hefei 230026, People’s Republic of China
54 University of South China, Hengyang 421001, People’s Republic of China
55 University of the Punjab, Lahore-54590, Pakistan
56 (A)University of Turin, I-10125, Turin, Italy; (B)University of Eastern Piedmont, I-15121, Alessandria, Italy; (C)INFN, I-10125, Turin, Italy
57 Uppsala University, Box 516, SE-75120 Uppsala, Sweden
58 Wuhan University, Wuhan 430072, People’s Republic of China
59 Xinyang Normal University, Xinyang 464000, People’s Republic of China
60 Zhejiang University, Hangzhou 310027, People’s Republic of China
61 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
k Currently at: Center for Underground Physics, Institute for Basic Science, Daejeon 34126, Korea
Abstract
We present the first amplitude analysis of the decay . We use an collision data sample corresponding to an integrated luminosity of 3.19 collected with the BESIII detector at a center-of-mass energy of GeV. We observe for the first time the pure -annihilation decays and . We measure the absolute branching fractions %, which is larger than the branching fractions of other measured pure -annihilation decays by at least one order of magnitude. In addition, we measure the branching fraction of with significantly improved precision.
pacs:
13.25.Ft, 12.38.Qk, 14.40.Lb
The theoretical understanding of the weak decay of charm mesons is challenging because the charm quark mass is not heavy enough to describe exclusive processes with a heavy-quark expansion. The -annihilation (WA) process may occur as a result of final-state-interactions (FSI) and the WA amplitude may be comparable with the tree-external-emission amplitude HaiYangCheng1 ; Li:2012cfa ; Li:2013xsa ; HaiYangCheng2 . However, the theoretical calculation of the WA amplitude is currently difficult. Hence measurements of decays involving a WA contribution provide the best method to investigate this mechanism.
Among the measured decays involving WA contributions, two decays with mode, and , only occur through WA, which we refer to as ‘pure WA decay’. Here and denote vector and pseudoscalar mesons, respectively. The branching fractions (BFs) of these pure WA decays are at the PDG . These BF measurements allow the determination of two distinct WA amplitudes for mode. In addition, they improve our understanding of SU(3)-flavor symmetry and violation in the charm sector HaiYangCheng2 . However, for mode, where denotes a scalar meson, there are neither experimental measurements nor theoretical calculations of the BFs.
Two decays with mode and are pure WA decays if - mixing is ignored. Their decay diagrams are shown in Fig. 1.
In this Letter, we search for them with an amplitude analysis of . We also present improved measurements of the BFs of and decays. Throughout this Letter, charge conjugation and are implied unless explicitly stated.
We use a data sample corresponding to an integrated luminosity of 3.19 , taken at a center-of-mass energy of GeV with the BESIII detector located at Beijing Electron Position Collider Yu:IPAC2016-TUYA01 . The BESIII detector and the upgraded multi-gap resistive plate chambers used in the time-of-flight systems are described in Refs. detector and MRPC , respectively. We study the background and determine tagging efficiencies with a generic Monte Carlo (GMC) sample that is simulated with geant4 sim . The GMC sample includes all known open-charm decay processes, which are generated with conexc ConExc and evtgen EvtGen , initial-state radiative decays to the or , and continuum processes. We determine signal efficiencies from Monte Carlo (MC) samples of decays that are generated according to the amplitude fit results to data reported in this Letter.
In the data sample, the mesons are mainly produced via the process of , ; we refer to the directly produced from the decay as . To exploit the dominance of the process, we use the double-tag (DT) method tagmethod . The single-tag (ST) mesons are reconstructed using seven hadronic decays: , , , , , , and . A DT is formed by selecting a decay in the side of the event recoiling against the tag. Here, , , and are reconstructed using , , and channels, respectively. The selection criteria for charged tracks, photons, and are the same as those reported in Ref. omegapi . The candidate is required to have an invariant mass of the combination in the interval GeV.
The invariant mass of the tagged (signal) candidates are required to be in the interval GeV/ ( GeV/). For the ST mesons, the recoil mass is required to be within the range GeV to suppress events from non- processes. Here, is the four-momentum of the colliding system, is the three-momentum of the candidate and is the mass PDG . For events with multiple tag candidates for a single tag mode, the one with a value of closest to is chosen. If there are multiple signal candidates present against a selected tag candidate, the one with a value of closest to is accepted.
We perform a seven-constraint (7C) kinematic fit to the selected DT candidates for two reasons. First, to successfully perform an amplitude analysis, the 7C fit ensures that all events fall within the Dalitz plot. Second, it allows the selection of the candidate. In the 7C fit, aside from constraints arising from four-momentum conservation, the invariant masses of the , , and combinations used to reconstruct the signal candidate are constrained to the nominal , and masses PDG , respectively. The candidate used in the 7C fit that produces the smallest is selected. We require to avoid introducing a broad peak in the background distribution arising from events that are inconsistent with the signal hypothesis. To further suppress the background, we perform another 7C kinematic fit, referred to as the ‘7CA fit’, by replacing the signal mass constraint with a mass constraint in which the invariant mass of either the or candidate and the selected is constrained to the nominal mass PDG . We require one of the values of the to be less than 500, to ensure reasonable consistency with the signal hypothesis. To suppress the background associated with the fake candidates in the signal events, we veto events with , where is the angle between the momentum vector from a mass constraint fit and that from the 7CA kinematic fit. After applying these criteria, we further reduce the background, by using a multi-variable analysis method Hocker:2007ht in which a boosted decision tree (BDT) classifier is developed using the GMC sample. The BDT takes three discriminating variables as inputs: the invariant mass of the photon pair used to reconstruct the candidate, the momentum of the lower-energy photon from the candidate, and the momentum of the candidate. Studies of the GMC sample show that a requirement on the output of the BDT retains 77.8% signal and rejects 73.4% background. Events in which the signal candidate lies within the interval GeV are retained for the amplitude analysis. The background events in the signal region from the GMC sample are used to model the corresponding background in data. To check the accuracy of the GMC background modeling, we compare the , and distributions of events outside the selected interval between data and the GMC sample; the distributions are found to be compatible within the statistical uncertainties. We retain a sample of 1239 candidates that has a purity of %.
The amplitude analysis is performed using an unbinned maximum-likelihood fit to the accepted candidate events in data. The background contribution is subtracted in the likelihood calculation by assigning negative weights to the background events. The total amplitude is modeled as the coherent sum of the amplitudes of all intermediate processes, , where and are the magnitude and phase of the amplitude, respectively. The amplitude is given by . Here is a function that describes the propagator of the intermediate resonance. The resonance is parameterized by a relativistic Breit-Wigner function, while the resonance is parameterized as a two-channel-coupled Flatté formula ( and ), . Here, and are the phase space factors: , where is denoted as the magnitude of the momentum of the daughter particle in the rest system and is the invariant mass square of . We use the coupling constants GeV and , reported in Ref. BAM-168 . The function describes angular-momentum conservation in the decay and is constructed using the covariant tensor formalism Zou . The function is the Blatt-Weisskopf barrier factor of the intermediate state ( meson). Further, according to the topology diagrams shown in Fig. 1, the W-annihilation amplitudes of decays and imply the relationship .
For each amplitude, the statistical significance is determined from the change in and the number of degrees of freedom (NDOF) when the fit is performed with and without the amplitude included. In the nominal fit, only amplitudes that have a significance greater than are considered, where is the standard deviation. In addition to the amplitude, both and amplitudes are found to be significant. However, the latter two amplitude phases are found to be approximately correlated with one another; their fitted are found to be consistent with each other while a difference in is found to be close to , which indicates there is no significant mixing in . Consequently, in the nominal fit, we set the values of of these two amplitudes to be equal with a phase difference of . We refer to the coherent sum of these two amplitudes as “”. The non-resonant process is also considered, where the subscript denotes a vector non-resonant state of the combination. We consider other possible amplitudes that involve , , , , or , as well as the non-resonant partners; none of these amplitudes has a statistical significance greater than , so they are not included in the nominal model. In the fit, the values of and for the amplitude are fixed to be one and zero, respectively, so that all other amplitudes are measured relative to this amplitude. The masses and widths of the intermediate resonances used in the fit, except for those of the , are taken from Ref. PDG .
For , , and , the resulting statistical significances are greater than 20, 5.7, and 16.2, respectively. Their phases and fit fractions (FFs) are listed in Table 1. Here the FF for the intermediate process is defined as , where is the standard element of the three-body phase space. The Dalitz plot of versus for data is shown in Fig. 2(a). The projections of the fit on , and are shown in Figs. 2(b-d). The projections on and for events with GeV are shown in Figs. 2(e,f), in which peaks are observed. The fit quality is determined by calculating the of the fit using an adaptive binning of the versus Dalitz plot that requires each bin contains at least 10 events. The goodness of fit is /NDOF=82.8/77.
Systematic uncertainties for the amplitude analysis are considered from five sources: (I) line-shape parameterizations of the resonances, (II) fixed parameters in the amplitudes, (III) the background level and distribution in the Dalitz plot, (IV) experimental effects, and (V) the fitter performance. We determine these systematic uncertainties separately by taking the difference between the values of , and FFn found by the altered and nominal fits. The uncertainties related to the assumed resonance line-shape are estimated by using the following alternatives: a Gounaris-Sakurai function GS for the propagator and a three-channel-coupled Flatté formula, which adds the channel BAM-168 , for the propagator. Since varying the propagators results in different normalization factors, the effect on all FFs is considered. The uncertainties related to the fixed parameters in the amplitudes are considered by varying the mass and width of by PDG , the mass and coupling constants of by the uncertainties reported in Ref. BAM-168 , and the effect of varying the radii of the non-resonant state and meson within GeV*-1*. In addition, for the resonance, the effective radius reported in Ref. PDG is used as an alternative. The uncertainty related to the assumed background level is determined by changing the background fraction within its statistical uncertainty. The uncertainty related to the assumed background shape is estimated by using an alternative distribution simulated with , . To estimate the uncertainty from the experimental effect related to the kinematic fits and BDT classifier, we set the requirements for the result of the two kinematic fits to be twice the values used in the nominal selection, alter the requirement to be greater than 0.996, and adjust the BDT requirement such that the purity is approximately equal to the sample used in the nominal fit. The fitter performance is investigated with the same method as reported in Ref. K3Pi . The biases are small and taken as the systematic uncertainties. The contributions of individual systematic uncertainties are summarized in Table 2, and are added in quadrature to obtain the total systematic uncertainty.
Further, we measure the total BF of without reconstructing to improve the statistical precision. The ST yields () and DT yield () of data are determined by the fits to the resulting and distributions, as shown in Figs. 3(a-g) and Fig. 3(h), respectively. In each fit, the signal shape is modeled with the MC-simulated shape convoluted with a Gaussian function, which accounts for any difference in resolution between the data and MC, and the background is described with a second-order Chebychev polynomial.
These fits give a total ST yield of and a signal yield of . Based on the signal MC sample, generated according to the amplitude analysis results reported in this Letter, the DT efficiencies () are determined. With , , and the ST efficiencies (), the relationship , where the index denotes the tag mode, is used to obtain .
For the total BF measurement, the systematic uncertainty related to the signal shape is studied by performing an alternative fit without convolving the Gaussian resolution function. The BF shift of 0.5% is taken as the uncertainty. The systematic uncertainty arising from the assumed background shape and the fit range is studied by replacing our nominal ones with a first-order Chebychev polynomial and a fit range of GeV, respectively. The largest BF shift of 0.6% is taken as the related uncertainty. The possible bias due to the measurement method is estimated to be 0.2% by comparing the measured BF in the GMC sample, using the same method as in data analysis, to the value assumed in the generation. The uncertainties from particle identification and tracking efficiencies are assigned to be 0.5% and 1.0% omegapi , respectively. The relative uncertainty in the reconstruction efficiency is 2.0% omegapi , and the uncertainty in reconstruction is assumed to be comparable to that on reconstruction and correlated with it. The uncertainty from the Dalitz model of 0.6% is estimated as the change of efficiency when the model parameters are varied by their systematic uncertainties (this term is not considered when calculating the BFs of the intermediate processes). The uncertainties due to MC statistics (0.2%) and the value of used PDG (0.5%) are also considered. Adding these uncertainties in quadrature gives a total systematic uncertainty of 4.3%.
We obtain to be . Using the FFs listed in Table 1, the BFs for the intermediate processes and are calculated to be % and %, respectively. With the definition of fit fraction, fraction of with respect to the total fraction of is evaluated to be 0.66. Multiplying by the FF of determined from the nominal fit and , the BF of is determined to be %.
In summary, we present the first amplitude analysis of the decay . The absolute BF of is measured with a precision improved by a factor of 2.5 compared with the world average value PDG . We observe the pure WA decays for the first time with a statistical significance of 16.2. The measured is larger than other measured BFs of pure WA decays and by at least one order of magnitude. Furthermore, when the measured - mixing rate Ablikim:2018pik is considered, the expected effect of - mixing is lower than the WA contribution in decay by two orders of magnitude, which is negligible.
With the measured , the WA contribution with respect to the tree-external-emission contribution in mode is estimated to be AoverT , which is significantly greater than that (0.10.2) in and modes Li:2013xsa ; HaiYangCheng2 . This measurement sheds light on the FSI effect and non-perturbative strong interaction HaiYangCheng1 ; HaiYangCheng2 , and provides a theoretical challenge to understand such a large WA contribution. In addition, the result of this analysis is an essential input to determine the effect from on the -wave contribution to the model-dependent amplitude analysis of Mitchell:2009aa ; delAmoSanchez:2010yp .
The authors greatly thanks Prof. Fu-Sheng Yu and Prof. Haiyang Cheng for the useful discussions. 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. 11475185, 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. U1332201, U1532257, U1532258; CAS Key Research Program of Frontier Sciences under Contracts Nos. QYZDJ-SSW-SLH003, QYZDJ-SSW-SLH040; 100 Talents Program of CAS; National 1000 Talents Program of China; 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; WCU Program of National Research Foundation of Korea under Contract No. R32-2008-000-10155-0.
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