Measurements of the absolute branching fractions of decays
M. Ablikim1, M. N. Achasov10,c, P. Adlarson64, S. Ahmed15, M. Albrecht4, R. Aliberti28, A. Amoroso63A,63C, Q. An60,48, Anita21, X. H. Bai54, Y. Bai47, O. Bakina29, R. Baldini Ferroli23A, I. Balossino24A, Y. Ban38,k, K. Begzsuren26, J. V. Bennett5, N. Berger28, M. Bertani23A, D. Bettoni24A, F. Bianchi63A,63C, J Biernat64, J. Bloms57, A. Bortone63A,63C, I. Boyko29, R. A. Briere5, H. Cai65, X. Cai1,48, A. Calcaterra23A, G. F. Cao1,52, N. Cao1,52, S. A. Cetin51B, J. F. Chang1,48, W. L. Chang1,52, G. Chelkov29,b, D. Y. Chen6, G. Chen1, H. S. Chen1,52, M. L. Chen1,48, S. J. Chen36, X. R. Chen25, Y. B. Chen1,48, Z. J Chen20,l, W. S. Cheng63C, G. Cibinetto24A, F. Cossio63C, X. F. Cui37, H. L. Dai1,48, J. P. Dai42,g, X. C. Dai1,52, A. Dbeyssi15, R. B. de Boer4, D. Dedovich29, Z. Y. Deng1, A. Denig28, I. Denysenko29, M. Destefanis63A,63C, F. De Mori63A,63C, Y. Ding34, C. Dong37, J. Dong1,48, L. Y. Dong1,52, M. Y. Dong1,48,52, S. X. Du68, J. Fang1,48, S. S. Fang1,52, Y. Fang1, R. Farinelli24A, L. Fava63B,63C, F. Feldbauer4, G. Felici23A, C. Q. Feng60,48, M. Fritsch4, C. D. Fu1, Y. Fu1, X. L. Gao60,48, Y. Gao61, Y. Gao38,k, Y. G. Gao6, I. Garzia24A,24B, E. M. Gersabeck55, A. Gilman56, K. Goetzen11, L. Gong37, W. X. Gong1,48, W. Gradl28, M. Greco63A,63C, L. M. Gu36, M. H. Gu1,48, S. Gu2, Y. T. Gu13, C. Y. Guan1,52, A. Q. Guo22, L. B. Guo35, R. P. Guo40, Y. P. Guo9,h, Y. P. Guo28, A. Guskov29, S. Han65, T. T. Han41, T. Z. Han9,h, X. Q. Hao16, F. A. Harris53, K. L. He1,52, F. H. Heinsius4, C. H. Heinz28, T. Held4, Y. K. Heng1,48,52, M. Himmelreich11,f, T. Holtmann4, Y. R. Hou52, Z. L. Hou1, H. M. Hu1,52, J. F. Hu42,g, T. Hu1,48,52, Y. Hu1, G. S. Huang60,48, L. Q. Huang61, X. T. Huang41, Y. P. Huang1, Z. Huang38,k, N. Huesken57, T. Hussain62, W. Ikegami Andersson64, W. Imoehl22, M. Irshad60,48, S. Jaeger4, S. Janchiv26,j, Q. Ji1, Q. P. Ji16, X. B. Ji1,52, X. L. Ji1,48, H. B. Jiang41, X. S. Jiang1,48,52, X. Y. Jiang37, J. B. Jiao41, Z. Jiao18, S. Jin36, Y. Jin54, T. Johansson64, N. Kalantar-Nayestanaki31, X. S. Kang34, R. Kappert31, M. Kavatsyuk31, B. C. Ke43,1, I. K. Keshk4, A. Khoukaz57, P. Kiese28, R. Kiuchi1, R. Kliemt11, L. Koch30, O. B. Kolcu51B,e, B. Kopf4, M. Kuemmel4, M. Kuessner4, A. Kupsc64, M. G. Kurth1,52, W. Kühn30, J. J. Lane55, J. S. Lange30, P. Larin15, L. Lavezzi63A,63C, H. Leithoff28, M. Lellmann28, T. Lenz28, C. Li39, C. H. Li33, Cheng Li60,48, D. M. Li68, F. Li1,48, G. Li1, H. B. Li1,52, H. J. Li9,h, J. L. Li41, J. Q. Li4, Ke Li1, L. K. Li1, Lei Li3, P. L. Li60,48, P. R. Li32, S. Y. Li50, W. D. Li1,52, W. G. Li1, X. H. Li60,48, X. L. Li41, Z. B. Li49, Z. Y. Li49, H. Liang60,48, H. Liang1,52, Y. F. Liang45, Y. T. Liang25, L. Z. Liao1,52, J. Libby21, C. X. Lin49, B. Liu42,g, B. J. Liu1, C. X. Liu1, D. Liu60,48, D. Y. Liu42,g, F. H. Liu44, Fang Liu1, Feng Liu6, H. B. Liu13, H. M. Liu1,52, Huanhuan Liu1, Huihui Liu17, J. B. Liu60,48, J. Y. Liu1,52, K. Liu1, K. Y. Liu34, Ke Liu6, L. Liu60,48, Q. Liu52, S. B. Liu60,48, Shuai Liu46, T. Liu1,52, X. Liu32, Y. B. Liu37, Z. A. Liu1,48,52, Z. Q. Liu41, Y. F. Long38,k, X. C. Lou1,48,52, F. X. Lu16, H. J. Lu18, J. D. Lu1,52, J. G. Lu1,48, X. L. Lu1, Y. Lu1, Y. P. Lu1,48, C. L. Luo35, M. X. Luo67, P. W. Luo49, T. Luo9,h, X. L. Luo1,48, S. Lusso63C, X. R. Lyu52, F. C. Ma34, H. L. Ma1, L. L. Ma41, M. M. Ma1,52, Q. M. Ma1, R. Q. Ma1,52, R. T. Ma52, X. N. Ma37, X. X. Ma1,52, X. Y. Ma1,48, Y. M. Ma41, F. E. Maas15, M. Maggiora63A,63C, S. Maldaner28, S. Malde58, Q. A. Malik62, A. Mangoni23B, Y. J. Mao38,k, Z. P. Mao1, S. Marcello63A,63C, Z. X. Meng54, J. G. Messchendorp31, G. Mezzadri24A, T. J. Min36, R. E. Mitchell22, X. H. Mo1,48,52, Y. J. Mo6, N. Yu. Muchnoi10,c, H. Muramatsu56, S. Nakhoul11,f, Y. Nefedov29, F. Nerling11,f, I. B. Nikolaev10,c, Z. Ning1,48, S. Nisar8,i, S. L. Olsen52, Q. Ouyang1,48,52, S. Pacetti23B,23C, X. Pan9,h, Y. Pan55, A. Pathak1, P. Patteri23A, M. Pelizaeus4, H. P. Peng60,48, K. Peters11,f, J. Pettersson64, J. L. Ping35, R. G. Ping1,52, A. Pitka4, R. Poling56, V. Prasad60,48, H. Qi60,48, H. R. Qi50, M. Qi36, T. Y. Qi9, T. Y. Qi2, S. Qian1,48, W.-B. Qian52, Z. Qian49, C. F. Qiao52, L. Q. Qin12, X. S. Qin4, Z. H. Qin1,48, J. F. Qiu1, S. Q. Qu37, K. H. Rashid62, K. Ravindran21, C. F. Redmer28, A. Rivetti63C, V. Rodin31, M. Rolo63C, G. Rong1,52, Ch. Rosner15, M. Rump57, A. Sarantsev29,d, Y. Schelhaas28, C. Schnier4, K. Schoenning64, M. Scodeggio24A, D. C. Shan46, W. Shan19, X. Y. Shan60,48, M. Shao60,48, C. P. Shen9, P. X. Shen37, X. Y. Shen1,52, H. C. Shi60,48, R. S. Shi1,52, X. Shi1,48, X. D Shi60,48, J. J. Song41, Q. Q. Song60,48, W. M. Song27,1, Y. X. Song38,k, S. Sosio63A,63C, S. Spataro63A,63C, F. F. Sui41, G. X. Sun1, J. F. Sun16, L. Sun65, S. S. Sun1,52, T. Sun1,52, W. Y. Sun35, X Sun20,l, Y. J. Sun60,48, Y. K. Sun60,48, Y. Z. Sun1, Z. T. Sun1, Y. H. Tan65, Y. X. Tan60,48, C. J. Tang45, G. Y. Tang1, J. Tang49, V. Thoren64, B. Tsednee26, I. Uman51D, B. Wang1, B. L. Wang52, C. W. Wang36, D. Y. Wang38,k, H. P. Wang1,52, K. Wang1,48, L. L. Wang1, M. Wang41, M. Z. Wang38,k, Meng Wang1,52, W. H. Wang65, W. P. Wang60,48, X. Wang38,k, X. F. Wang32, X. L. Wang9,h, Y. Wang49, Y. Wang60,48, Y. D. Wang15, Y. F. Wang1,48,52, Y. Q. Wang1, Z. Wang1,48, Z. Y. Wang1, Ziyi Wang52, Zongyuan Wang1,52, D. H. Wei12, P. Weidenkaff28, F. Weidner57, S. P. Wen1, D. J. White55, U. Wiedner4, G. Wilkinson58, M. Wolke64, L. Wollenberg4, J. F. Wu1,52, L. H. Wu1, L. J. Wu1,52, X. Wu9,h, Z. Wu1,48, L. Xia60,48, H. Xiao9,h, S. Y. Xiao1, Y. J. Xiao1,52, Z. J. Xiao35, X. H. Xie38,k, Y. G. Xie1,48, Y. H. Xie6, T. Y. Xing1,52, X. A. Xiong1,52, G. F. Xu1, J. J. Xu36, Q. J. Xu14, W. Xu1,52, X. P. Xu46, F. Yan9,h, L. Yan63A,63C, L. Yan9,h, W. B. Yan60,48, W. C. Yan68, Xu Yan46, H. J. Yang42,g, H. X. Yang1, L. Yang65, R. X. Yang60,48, S. L. Yang1,52, Y. H. Yang36, Y. X. Yang12, Yifan Yang1,52, Zhi Yang25, M. Ye1,48, M. H. Ye7, J. H. Yin1, Z. Y. You49, B. X. Yu1,48,52, C. X. Yu37, G. Yu1,52, J. S. Yu20,l, T. Yu61, C. Z. Yuan1,52, W. Yuan63A,63C, X. Q. Yuan38,k, Y. Yuan1, Z. Y. Yuan49, C. X. Yue33, A. Yuncu51B,a, A. A. Zafar62, Y. Zeng20,l, B. X. Zhang1, Guangyi Zhang16, H. H. Zhang49, H. Y. Zhang1,48, J. L. Zhang66, J. Q. Zhang4, J. W. Zhang1,48,52, J. Y. Zhang1, J. Z. Zhang1,52, Jianyu Zhang1,52, Jiawei Zhang1,52, L. Zhang1, Lei Zhang36, S. Zhang49, S. F. Zhang36, T. J. Zhang42,g, X. Y. Zhang41, Y. Zhang58, Y. H. Zhang1,48, Y. T. Zhang60,48, Yan Zhang60,48, Yao Zhang1, Yi Zhang9,h, Z. H. Zhang6, Z. Y. Zhang65, G. Zhao1, J. Zhao33, J. Y. Zhao1,52, J. Z. Zhao1,48, Lei Zhao60,48, Ling Zhao1, M. G. Zhao37, Q. Zhao1, S. J. Zhao68, Y. B. Zhao1,48, Y. X. Zhao25, Z. G. Zhao60,48, A. Zhemchugov29,b, B. Zheng61, J. P. Zheng1,48, Y. Zheng38,k, Y. H. Zheng52, B. Zhong35, C. Zhong61, L. P. Zhou1,52, Q. Zhou1,52, X. Zhou65, X. K. Zhou52, X. R. Zhou60,48, A. N. Zhu1,52, J. Zhu37, K. Zhu1, K. J. Zhu1,48,52, S. H. Zhu59, W. J. Zhu37, X. L. Zhu50, Y. C. Zhu60,48, Z. A. Zhu1,52, 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 Sezione di Perugia, I-06100, Perugia, Italy; (C)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 Modern Physics, Lanzhou 730000, People’s Republic of China
26 Institute of Physics and Technology, Peace Ave. 54B, Ulaanbaatar 13330, Mongolia
27 Jilin University, Changchun 130012, People’s Republic of China
28 Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
29 Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
30 Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
31 KVI-CART, University of Groningen, NL-9747 AA Groningen, The Netherlands
32 Lanzhou University, Lanzhou 730000, People’s Republic of China
33 Liaoning Normal University, Dalian 116029, People’s Republic of China
34 Liaoning University, Shenyang 110036, People’s Republic of China
35 Nanjing Normal University, Nanjing 210023, People’s Republic of China
36 Nanjing University, Nanjing 210093, People’s Republic of China
37 Nankai University, Tianjin 300071, People’s Republic of China
38 Peking University, Beijing 100871, People’s Republic of China
39 Qufu Normal University, Qufu 273165, People’s Republic of China
40 Shandong Normal University, Jinan 250014, People’s Republic of China
41 Shandong University, Jinan 250100, People’s Republic of China
42 Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
43 Shanxi Normal University, Linfen 041004, People’s Republic of China
44 Shanxi University, Taiyuan 030006, People’s Republic of China
45 Sichuan University, Chengdu 610064, People’s Republic of China
46 Soochow University, Suzhou 215006, People’s Republic of China
47 Southeast University, Nanjing 211100, People’s Republic of China
48 State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People’s Republic of China
49 Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
50 Tsinghua University, Beijing 100084, People’s Republic of China
51 (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
52 University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
53 University of Hawaii, Honolulu, Hawaii 96822, USA
54 University of Jinan, Jinan 250022, People’s Republic of China
55 University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
56 University of Minnesota, Minneapolis, Minnesota 55455, USA
57 University of Muenster, Wilhelm-Klemm-Str. 9, 48149 Muenster, Germany
58 University of Oxford, Keble Rd, Oxford, UK OX13RH
59 University of Science and Technology Liaoning, Anshan 114051, People’s Republic of China
60 University of Science and Technology of China, Hefei 230026, People’s Republic of China
61 University of South China, Hengyang 421001, People’s Republic of China
62 University of the Punjab, Lahore-54590, Pakistan
63 (A)University of Turin, I-10125, Turin, Italy; (B)University of Eastern Piedmont, I-15121, Alessandria, Italy; (C)INFN, I-10125, Turin, Italy
64 Uppsala University, Box 516, SE-75120 Uppsala, Sweden
65 Wuhan University, Wuhan 430072, People’s Republic of China
66 Xinyang Normal University, Xinyang 464000, People’s Republic of China
67 Zhejiang University, Hangzhou 310027, People’s Republic of China
68 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 Novosibirsk State University, Novosibirsk, 630090, Russia
d Also at the NRC ”Kurchatov Institute”, PNPI, 188300, Gatchina, Russia
e Also at Istanbul Arel University, 34295 Istanbul, Turkey
f Also at Goethe University Frankfurt, 60323 Frankfurt am Main, Germany
g 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
h 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
i Also at Harvard University, Department of Physics, Cambridge, MA, 02138, USA
j Currently at: Institute of Physics and Technology, Peace Ave.54B, Ulaanbaatar 13330, Mongolia
k Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, People’s Republic of China
l School of Physics and Electronics, Hunan University, Changsha 410082, China
Abstract
Based on 2.93 fb-1 collision data taken at center-of-mass energy of 3.773 GeV by the
BESIII detector,
we report the measurements of the absolute branching fractions of ,
,
,
,
,
,
,
, and
.
The decays , , , , and are observed for the first time.
The branching fractions of the decays , , , and are measured with improved precision
compared to the world-average values.
pacs:
13.20.Fc, 14.40.Lb
I Introduction
Multi-body hadronic decays provide an ideal laboratory to study strong and weak interactions.
Amplitude analyses of these decays offer comprehensive information of quasi-two-body decays, which are important to explore mixing,
charge-parity () violation and quark SU(3)-flavor asymmetry breaking phenomenon ref5 ; theory_1 ; theory_2 ; chenghy1 ; yufs .
In particular, for the search of violation, it is important to understand the intermediate structures for the singly Cabibbo-suppressed decays
of xwkang ; Charles:2009ig ; yufs-cpv .
Current measurements of the decays containing or are limited pdg2018 .
The branching fractions (BFs) of
FOCUS_kskspipi ; ARGUS_kkpipi ,
FOCUS_kskpipi ,
FOCUS_kskpipi , and
ACCMOR_kkpipi0 were only determined relative to some well known decays
or via topological normalization, with poor precision.
This paper presents the first direct measurements of the absolute BFs for the decays
,
,
,
,
,
,
,
, and
.
The decay is not included since it suffers from poor statistics and high background.
Throughout this paper, charge conjugate processes are implied.
An collision data sample corresponding to an integrated luminosity of 2.93 fb-1lum_bes3 collected at a
center-of-mass energy of 3.773 GeV with the BESIII detector is used to perform this analysis.
II BESIII detector and Monte Carlo simulation
The BESIII detector is a magnetic
spectrometer BESIII located at the Beijing Electron
Positron Collider (BEPCII) Yu:IPAC2016-TUYA01 . The
cylindrical core of the BESIII detector consists of a helium-based
multilayer drift chamber (MDC), a plastic scintillator time-of-flight
system (TOF), and a CsI(Tl) electromagnetic calorimeter (EMC),
which are all enclosed in a superconducting solenoidal magnet
providing a 1.0 T magnetic field. The solenoid is supported by an
octagonal flux-return yoke with resistive plate counter muon
identifier modules interleaved with steel. The acceptance of
charged particles and photons is 93% over solid angle. The
charged-particle momentum resolution at is
, and the resolution is for the electrons
from Bhabha scattering. The EMC measures photon energies with a
resolution of () at GeV in the barrel (end cap)
region. The time resolution of the TOF barrel part is 68 ps, while
that of the end cap part is 110 ps.
Simulated samples produced with the geant4-based geant4 Monte Carlo (MC) package including the geometric description of the BESIII detector and the
detector response, are used to determine the detection efficiency
and to estimate the backgrounds. The simulation includes the beam-energy spread and initial-state radiation (ISR) in the
annihilations modeled with the generator kkmckkmc .
The inclusive MC samples consist of the production of
pairs with consideration of quantum coherence for all neutral
modes, the non- decays of the , the ISR
production of the and states, and the
continuum processes.
The known decay modes are modeled with evtgenevtgen using the BFs taken from the
Particle Data Group (PDG) pdg2018 , and the remaining unknown decays
from the charmonium states are modeled with lundcharmlundcharm . The final-state radiations
from charged final-state particles are incorporated with the photos package photos .
III Measurement Method
The or pair is produced without an additional hadron in annihilations at GeV. This process
offers a clean environment to measure the BFs of the hadronic decay with the double-tag (DT) method.
The single-tag (ST) candidate events are selected by reconstructing a or in the following hadronic final states:
, , and , and
,
, , , ,
and .
The event in which a signal candidate is selected in the presence of an ST meson,
is called a DT event.
The BF of the signal decay is determined by
(1)
where
and
are the total yields of the ST and DT candidates in data, respectively.
is the ST yield for the tag mode . For the signal decays involving meson(s) in the final states, is
the net DT yields after removing the peaking background from the corresponding non- decays. For the other signal decays, the variable corresponds to
the fitted DT yields as described later.
Here, is the efficiency of detecting the signal decay, averaged over the tag mode , which is given by:
(2)
where and are the efficiencies of detecting ST and DT candidates in the tag mode , respectively.
IV Event selection
The selection criteria of , , , and are the same as those used in the analyses presented in
Refs. epjc76 ; cpc40 ; bes3-pimuv ; bes3-Dp-K1ev ; bes3-etaetapi ; bes3-omegamuv ; bes3-etamuv ; bes3-etaX .
All charged tracks, except those from decays, are required to have a polar angle with respect to the beam direction
within the MDC acceptance , and a distance of closest approach to the interaction point (IP) within 10 cm along the beam direction
and within 1 cm in the plane transverse to the beam direction. Particle identification (PID) for charged pions, kaons, and protons is performed by
exploiting TOF information and the specific ionization energy loss measured by the MDC.
The confidence levels for pion and kaon hypotheses ( and ) are calculated. Kaon and pion candidates are required to
satisfy and , respectively.
The candidates are reconstructed from two oppositely charged tracks to which no PID criteria are applied and which masses are assumed to be that of pions.
The charged tracks from the candidate must satisfy . In addition, due to the long lifetime of the meson,
there is a less stringent criterion on the distance of closest approach to the IP in the beam direction of less than 20 cm and no requirement on the
distance of closest approach in the plane transverse to the beam direction.
Furthermore, the pairs are constrained to originate from a common vertex and their invariant mass is required to be within ,
which corresponds to about three times the fitted resolution around the nominal mass. The decay length of the candidate is required to be
larger than two standard deviations of the vertex resolution away from the IP.
The candidate is reconstructed via its decay. The photon candidates are selected using the information from the EMC shower.
It is required that each EMC shower starts within 700 ns of the event start time and its energy is greater than 25 (50) MeV in the barrel (end cap)
region of the EMC BESIII .
The energy deposited in the nearby TOF counters is included to improve the reconstruction efficiency and energy resolution. The opening angle between
the candidate shower and the nearest charged track must be greater than . The pair is taken as a candidate
if its invariant mass is within GeV. To improve the resolution, a kinematic fit constraining the
invariant mass to the nominal mass pdg2018 is imposed on the selected photon pair.
V Yields of ST mesons
To select candidates, the backgrounds from cosmic rays and Bhabha events are rejected by using the same requirements described in Ref. deltakpi .
In the selection of candidates, the decays are suppressed by requiring the mass of all pairs to
be outside GeV/.
The tagged mesons are identified using two variables, namely the energy difference
(3)
and the beam-constrained mass
(4)
Here, is the beam energy,
and are the momentum and energy of
the candidate in the rest frame of system, respectively.
For each tag mode, if there are multiple candidates in an event,
only the one with the smallest is kept.
The tagged candidates are required to satisfy
MeV for the tag modes containing in the final states
and MeV for the other tag modes, thereby taking into account the different resolutions.
To extract the yields of ST mesons for individual tag modes, binned-maximum likelihood fits are performed on the corresponding
distributions of the accepted ST candidates following Refs. epjc76 ; cpc40 ; bes3-pimuv ; bes3-Dp-K1ev ; bes3-etaetapi ; bes3-omegamuv ; bes3-etamuv .
In the fits, the signal is modeled by an MC-simulated shape convolved with
a double-Gaussian function describing the resolution difference between data and MC simulation.
The combinatorial background shape is described by an ARGUS function ARGUS
defined as ,
where denotes , is an endpoint fixed at 1.8865 GeV, is a normalization factor, and is a free parameter.
The resulting fits to the
distributions for each mode are shown in
Fig. 1.
The total yields of the ST and mesons in data are and
, respectively, where the uncertainties are statistical only.
Fig. 1: Fits to the distributions of
the ST (left column) and (middle and right columns) candidates,
where the points with error bars are data,
the blue solid and red dashed curves are the fit results
and the fitted backgrounds, respectively.
VI Yields of DT events
In the recoiling sides against the tagged candidates, the signal decays are selected
by using the residual tracks that have not been used to reconstruct the tagged candidates.
To suppress the contribution in the individual mass spectra for the
, , and decays, the
and invariant masses are required to be outside GeV/ and GeV/, respectively.
To suppress the background from in the identification of the process,
the invariant mass is required to be outside GeV/.
These requirements correspond to at least five times the fitted mass resolution away from the fitted mean of the mass peak.
The signal mesons are identified using the energy difference
and the beam-constrained mass , which are calculated with Eqs. (3) and (4)
by substituting “tag” with “sig”.
For each signal mode, if there are multiple candidates in an event, only the one with the smallest is kept.
The signal decays are required to satisfy the mode-dependent requirements,
as shown in the second column of Table 1.
To suppress incorrectly identified candidates, the opening angle between the tagged and the signal is required to be greater than ,
resulting in a loss of (2-6)% of the signal and suppressing (8-55)% of the background.
Figure 2 shows the
versus distribution of the accepted DT candidates in data.
The signal events concentrate around ,
where is the nominal mass pdg2018 .
The events with correctly reconstructed () and incorrectly
reconstructed (), named BKGI, are spread along the lines around
or .
The events smeared along the diagonal, named BKGII,
are mainly from the processes.
The events with uncorrelated and incorrectly reconstructed and , named BKGIII,
disperse across the whole allowed kinematic region.
For each signal decay mode, the yield of DT events () is obtained from a two-dimensional (2D) unbinned maximum-likelihood
fit cleo-2Dfit on the versus distribution of the accepted candidates. In the fit, the probability
density functions (PDFs) of signal, BKGI, BKGII, and BKGIII are constructed as
•
signal: ,
•
BKGI: ,
•
BKGII: , and
•
BKGIII: ,
respectively.
Here, , , , and .
The PDFs of signal , , and are described by the corresponding MC-simulated shapes.
is an ARGUS function ARGUS defined above,
where denotes , , or ; is fixed at 1.8865 GeV.
is a Gaussian function with mean of zero and standard deviation parametrized by ,
where and are fit parameters.
Fig. 2:
The
versus distribution of the accepted DT candidates of in data.
Here, ISR denotes the signal spreading along the diagonal direction.
Combinatorial pairs from the decays
[and ], , , , , , [and ]
may also satisfy the selection criteria
and form peaking backgrounds around in the distributions for ,
,
,
,
, and
, respectively.
This kind of peaking background is estimated by selecting events in the sideband region of
.
For , , , , and decays,
one-dimensional (1D) signal and sideband regions are used.
For and decays, 2D signal and sideband regions are used.
The 2D signal region is defined as the square region with both combinations lying in the signal regions.
The 2D sideband 1 (2) regions are defined as the square regions with 1 (2) combination(s) located in the 1D sideband regions
and the rest in the 1D signal region.
Figure 3 shows 1D and 2D invariant-mass distributions as well as the signal and sideband regions.
Fig. 3: (a) The invariant-mass distributions of the candidate events
of data (points with error bars) and inclusive MC sample (histogram).
Pairs of the red solid (blue dashed) arrows denote the signal (sideband) regions.
(b) Distribution of versus for the candidate events in data.
Red solid box denotes the 2D signal region.
Pink dot-dashed (blue dashed) boxes indicate the 2D sideband 1 (2) regions.
For the signal decays involving meson(s) in the final states,
the net yields of DT events are calculated by subtracting the sideband contribution from the DT fitted yield by
(5)
Here, for the decays with one meson while for the decays with two mesons.
The combinatorial backgrounds are assumed to be uniformly distributed and double-counting is avoided by subtracting (2) yields from (1)
yields appropriately.
and
are the fitted yields in the 1D or 2D signal region and sideband region, respectively.
For the other signal decays, the net yields of DT events are . Figure 4 shows the and
projections of the 2D fits to data. From these 2D fits, we obtain the DT yields for individual signal decays as shown in Table 1.
For each signal decay mode, the statistical significance is calculated according to
,
where and are the maximum likelihoods of the fits with and without involving the signal component, respectively.
The effect of combinatorial backgrounds in the -signal regions has been considered for the decays involving a .
The statistical significance for each signal decay is found to be greater than .
VII Results
Each of the , , , and decays
is modeled by the corresponding mixed signal MC samples, in which the dominant decay modes containing resonances of
, , and are mixed with the phase space (PHSP) signal MC samples. The mixing ratios are determined by
examining the corresponding invariant mass and momentum spectra. The other decays, which are limited in statistics, are generated with the PHSP generator.
The momentum and the polar angle distributions of the daughter particles and the invariant masses of each two- and three-body particle combinations
of the data agree with those of the MC simulations. As an example, Fig. 5 shows the invariant mass distributions of two or three-body particle combinations of candidate events for data and MC simulations.
The measured values of ,
, and the obtained BFs are summarized in Table 1. The current world-average values are also given for comparison.
The signal efficiencies have been corrected by the necessary data-MC differences in the selection efficiencies of and tracking and PID
procedures and the reconstruction.
These efficiencies also include the BFs of the and decays.
The efficiency for () is lower than that of ()
due to the rejection in the () mass spectrum.
Fig. 4: Projections on the and
distributions of the 2D fits to the DT candidate events with all or tags.
Data are shown as points with error bars.
Blue solid, light blue dotted, blue dot-dashed, red dot-long-dashed,
and pink long-dashed curves denote the overall fit results,
signal, BKGI, BKGII, and BKGIII components (see text), respectively.
Fig. 5: The invariant mass distributions of two or three-body particle combinations of candidate events for data and MC simulations.
Data are shown as points with error bars. Red solid histograms are mixed signal MC samples. Blue dashed histograms are PHSP signal MC samples. Yellow hatched histograms are the backgrounds estimated from the inclusive MC sample.
VIII Systematic uncertainties
The systematic uncertainties are estimated relative to the measured BFs and are discussed below.
In BF determinations using Eq. (1), all uncertainties associated with the selection of tagged canceled in the ratio.
The systematic uncertainties in the total yields of ST mesons related to the fits to the ST
candidates, were previously estimated to be
0.5% for both neutral and charged epjc76 ; cpc40 ; bes3-pimuv .
The tracking and PID efficiencies for or , and ,
are investigated using DT hadronic events.
The averaged ratios between data and MC efficiencies () of tracking (PID) for or are weighted by the corresponding momentum spectra of signal MC events,
giving to be and to be close to unity. After correcting the MC efficiencies by ,
the residual uncertainties of are assigned as the systematic uncertainties of tracking efficiencies,
which are (0.4-0.7)% per and (0.2-0.3)% per . and are all close to unity and their individual uncertainties, (0.2-0.3)%,
are taken as the associated systematic uncertainties per or .
The systematic error related to the uncertainty in the reconstruction efficiency
is estimated from measurements of and control samples sysks
and found to be 1.6% per .
The systematic uncertainty of reconstruction efficiency is assigned as (0.7-0.8)% per
from a study of DT hadronic decays of
and decays tagged by either or epjc76 ; cpc40 .
The systematic uncertainty in the 2D fit to the versus distribution is examined via the repeated measurements in which the signal shape
and the endpoint of the ARGUS function ( MeV/) are varied.
Quadratically summing the changes of the BFs for these two sources yields the corresponding systematic uncertainties.
The systematic uncertainty due to the requirement is assigned to be 0.3%,
which corresponds to the largest efficiency difference with and without smearing the data-MC Gaussian resolution of for signal MC events.
Here, the smeared Gaussian parameters are obtained by using the samples of DT events , , , and versus the same tags in our nominal analysis.
The systematic uncertainties due to sideband choice and rejection mass window
are assigned
by examining the changes of the BFs via varying nominal sideband and corresponding rejection window by MeV/.
For the decays whose efficiencies are estimated with mixed signal MC events,
the systematic uncertainty in the MC modeling is determined by comparing the signal efficiency when changing the percentage of MC sample components.
For the decays whose efficiencies are estimated with PHSP-distributed signal MC events, the uncertainties are assigned as the change of the signal efficiency after adding the possible decays containing or .
The imperfect simulations of the momentum and distributions of charged particles are considered as a source of systematic uncertainty.
The signal efficiencies are re-weighted by those distributions in data with background subtracted.
The largest change of the re-weighted to nominal efficiencies, 0.9%, is assigned as the corresponding systematic uncertainty.
The measurements of the BFs of the neutral decays are affected by quantum correlation effect. For each neutral decay, the -even component is estimated by the -even tag
and the -odd tag .
Using the same method as described in Ref. QC-factor
and the necessary parameters quoted from Refs. R-ref1 ; R-ref2 ; R-ref3 ,
we find the correction factors to account for the quantum correlation effect on the measured BFs are
, , , and
for , ,
, and , respectively.
After correcting the signal efficiencies by the individual factors, the residual uncertainties are
assigned as systematic uncertainties.
The uncertainties due to the limited MC statistics for various signal decays, (0.4-0.8)%, are taken into account as a systematic uncertainty.
The uncertainties of the quoted BFs of the and
decays are 0.07% and 0.03%, respectively pdg2018 .
The efficiencies of opening angle requirement is studied by using the DT events of , , and tagged by the same tag modes in our nominal analysis. The difference of the accepted efficiencies between data and MC simulations,
0.4% for the decays without ,
0.8% for the decays involving one and
0.3% for the decays involving two s,
is assigned as the associated systematic uncertainty.
Table 2 summarizes the systematic uncertainties in the BF measurements. For each signal decay,
the total systematic uncertainty is obtained by adding the above
effects in quadrature to be (2.6-6.0)% for various signal decay modes.
Table 1: Requirements of ,
net yields of DT candidates (),
signal efficiencies (),
and the obtained BFs () for various signal decays as well as comparisons with the world-average BFs ().
The first and second uncertainties for are statistical and systematic, respectively,
while the uncertainties for and are statistical only.
The world-average BF of is obtained by summing over the contributions of and .
Signal mode
(MeV)
(%)
()
()
–
–
–
–
–
Table 2:
Systematic uncertainties (%) in the measurements of the BFs of the signal decays
(1) ,
(2) ,
(3) ,
(4) ,
(5) ,
(6) ,
(7) ,
(8) , and
(9) .
Source/Signal decay
1
2
3
4
5
6
7
8
9
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
tracking
1.0
0.6
0.9
0.9
1.6
0.4
1.1
1.2
0.3
PID
0.4
0.4
0.6
0.6
1.0
0.2
0.6
0.7
0.2
reconstruction
…
3.2
1.6
1.6
…
1.6
1.6
1.6
3.2
reconstruction
1.6
…
0.7
0.7
0.8
1.6
…
…
0.7
requirement
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
0.7
rejection
4.2
2.4
…
…
…
4.2
…
0.8
…
sideband
…
0.2
1.1
0.2
…
1.3
0.1
0.1
0.2
Quoted BFs
0.0
0.1
0.1
0.1
0.0
0.1
0.1
0.1
0.1
MC statistics
0.8
0.6
0.7
0.6
0.5
0.4
0.4
0.5
0.6
MC modeling
1.3
1.0
0.5
0.7
2.1
1.4
0.5
0.7
0.5
Imperfect simulation
0.9
0.9
0.9
0.9
0.9
0.9
0.9
0.9
0.9
opening angle
0.3
0.4
0.8
0.8
0.8
0.3
0.4
0.4
0.8
2D fit
1.3
2.8
3.1
1.5
1.9
2.7
0.5
0.6
3.0
Quantum correlation effect
1.6
2.8
3.4
1.1
…
…
…
…
…
Total
5.5
5.9
5.4
3.3
3.8
6.0
2.6
2.8
4.8
IX Summary
In summary, by analyzing a data sample obtained in collisions at GeV with the BESIII detector and
corresponding to an integrated luminosity of 2.93 fb-1, we obtained the first direct measurements of the absolute BFs of
nine decays containing or mesons.
The , , , ,
and decays are observed for the first time. Compared to the world-average values, the BFs of
the , , , and decays are measured with
improved precision. Our BFs of and are in agreement with individual world averages within
while our BFs of and
deviate with individual world averages by and , respectively. The precision of the BF of is improved by a factor of
about seven.
Future amplitude analyses of all these decays with larger data samples foreseen at BESIII bes3-white-paper , Belle II belle2-white-paper , and LHCb lhcb-white-paper will supply rich information of the two-body decay modes containing scalar, vector, axial and tensor mesons, thereby benefiting the understanding of quark SU(3)-flavor symmetry.
X Acknowledgement
Authors thank for valuable discussions with Prof. Fu-sheng Yu.
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. 11775230, 11475123, 11625523, 11635010, 11735014, 11822506, 11835012, 11935015, 11935016, 11935018, 11961141012; 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. U1532101, U1932102, U1732263, U1832207; 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; ERC under Contract No. 758462; German Research Foundation DFG under Contracts Nos. Collaborative Research Center CRC 1044, FOR 2359; Istituto Nazionale di Fisica Nucleare, Italy; Ministry of Development of Turkey under Contract No. DPT2006K-120470; National Science and Technology fund; STFC (United Kingdom); The Knut and Alice Wallenberg Foundation (Sweden) under Contract No. 2016.0157; The Royal Society, UK under Contracts Nos. DH140054, DH160214; The Swedish Research Council; U. S. Department of Energy under Contracts Nos. DE-FG02-05ER41374, DE-SC-0012069.