E. Waheed
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
P. Urquijo
School of Physics, University of Melbourne, Victoria 3010
I. Adachi
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193
H. Aihara
Department of Physics, University of Tokyo, Tokyo 113-0033
S. Al Said
Department of Physics, Faculty of Science, University of Tabuk, Tabuk 71451
Department of Physics, Faculty of Science, King Abdulaziz University, Jeddah 21589
D. M. Asner
Brookhaven National Laboratory, Upton, New York 11973
H. Atmacan
University of Cincinnati, Cincinnati, Ohio 45221
V. Aulchenko
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
T. Aushev
National Research University Higher School of Economics, Moscow 101000
S. Bahinipati
Indian Institute of Technology Bhubaneswar, Satya Nagar 751007
P. Behera
Indian Institute of Technology Madras, Chennai 600036
K. Belous
Institute for High Energy Physics, Protvino 142281
J. Bennett
University of Mississippi, University, Mississippi 38677
M. Bessner
University of Hawaii, Honolulu, Hawaii 96822
V. Bhardwaj
Indian Institute of Science Education and Research Mohali, SAS Nagar, 140306
B. Bhuyan
Indian Institute of Technology Guwahati, Assam 781039
T. Bilka
Faculty of Mathematics and Physics, Charles University, 121 16 Prague
J. Biswal
J. Stefan Institute, 1000 Ljubljana
A. Bobrov
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
D. Bodrov
National Research University Higher School of Economics, Moscow 101000
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
J. Borah
Indian Institute of Technology Guwahati, Assam 781039
A. Bozek
H. Niewodniczanski Institute of Nuclear Physics, Krakow 31-342
M. Bračko
Faculty of Chemistry and Chemical Engineering, University of Maribor, 2000 Maribor
J. Stefan Institute, 1000 Ljubljana
P. Branchini
INFN - Sezione di Roma Tre, I-00146 Roma
T. E. Browder
University of Hawaii, Honolulu, Hawaii 96822
A. Budano
INFN - Sezione di Roma Tre, I-00146 Roma
M. Campajola
INFN - Sezione di Napoli, I-80126 Napoli
Università di Napoli Federico II, I-80126 Napoli
D. Červenkov
Faculty of Mathematics and Physics, Charles University, 121 16 Prague
M.-C. Chang
Department of Physics, Fu Jen Catholic University, Taipei 24205
P. Chang
Department of Physics, National Taiwan University, Taipei 10617
A. Chen
National Central University, Chung-li 32054
B. G. Cheon
Department of Physics and Institute of Natural Sciences, Hanyang University, Seoul 04763
K. Chilikin
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
H. E. Cho
Department of Physics and Institute of Natural Sciences, Hanyang University, Seoul 04763
K. Cho
Korea Institute of Science and Technology Information, Daejeon 34141
S.-J. Cho
Yonsei University, Seoul 03722
S.-K. Choi
Gyeongsang National University, Jinju 52828
Y. Choi
Sungkyunkwan University, Suwon 16419
S. Choudhury
Indian Institute of Technology Hyderabad, Telangana 502285
D. Cinabro
Wayne State University, Detroit, Michigan 48202
S. Cunliffe
Deutsches Elektronen–Synchrotron, 22607 Hamburg
S. Das
Malaviya National Institute of Technology Jaipur, Jaipur 302017
G. De Nardo
INFN - Sezione di Napoli, I-80126 Napoli
Università di Napoli Federico II, I-80126 Napoli
G. De Pietro
INFN - Sezione di Roma Tre, I-00146 Roma
R. Dhamija
Indian Institute of Technology Hyderabad, Telangana 502285
F. Di Capua
INFN - Sezione di Napoli, I-80126 Napoli
Università di Napoli Federico II, I-80126 Napoli
Z. Doležal
Faculty of Mathematics and Physics, Charles University, 121 16 Prague
T. V. Dong
Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics, Fudan University, Shanghai 200443
D. Epifanov
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
T. Ferber
Deutsches Elektronen–Synchrotron, 22607 Hamburg
D. Ferlewicz
School of Physics, University of Melbourne, Victoria 3010
B. G. Fulsom
Pacific Northwest National Laboratory, Richland, Washington 99352
R. Garg
Panjab University, Chandigarh 160014
V. Gaur
Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061
N. Gabyshev
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
A. Giri
Indian Institute of Technology Hyderabad, Telangana 502285
P. Goldenzweig
Institut für Experimentelle Teilchenphysik, Karlsruher Institut für Technologie, 76131 Karlsruhe
B. Golob
Faculty of Mathematics and Physics, University of Ljubljana, 1000 Ljubljana
J. Stefan Institute, 1000 Ljubljana
E. Graziani
INFN - Sezione di Roma Tre, I-00146 Roma
T. Gu
University of Pittsburgh, Pittsburgh, Pennsylvania 15260
Y. Guan
University of Cincinnati, Cincinnati, Ohio 45221
K. Gudkova
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
C. Hadjivasiliou
Pacific Northwest National Laboratory, Richland, Washington 99352
S. Halder
Tata Institute of Fundamental Research, Mumbai 400005
O. Hartbrich
University of Hawaii, Honolulu, Hawaii 96822
K. Hayasaka
Niigata University, Niigata 950-2181
H. Hayashii
Nara Women’s University, Nara 630-8506
W.-S. Hou
Department of Physics, National Taiwan University, Taipei 10617
C.-L. Hsu
School of Physics, University of Sydney, New South Wales 2006
T. Iijima
Kobayashi-Maskawa Institute, Nagoya University, Nagoya 464-8602
Graduate School of Science, Nagoya University, Nagoya 464-8602
K. Inami
Graduate School of Science, Nagoya University, Nagoya 464-8602
A. Ishikawa
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193
R. Itoh
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193
M. Iwasaki
Osaka City University, Osaka 558-8585
Y. Iwasaki
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
W. W. Jacobs
Indiana University, Bloomington, Indiana 47408
S. Jia
Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics, Fudan University, Shanghai 200443
Y. Jin
Department of Physics, University of Tokyo, Tokyo 113-0033
K. K. Joo
Chonnam National University, Gwangju 61186
A. B. Kaliyar
Tata Institute of Fundamental Research, Mumbai 400005
K. H. Kang
Kyungpook National University, Daegu 41566
H. Kichimi
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
C. H. Kim
Department of Physics and Institute of Natural Sciences, Hanyang University, Seoul 04763
D. Y. Kim
Soongsil University, Seoul 06978
K.-H. Kim
Yonsei University, Seoul 03722
K. T. Kim
Korea University, Seoul 02841
Y.-K. Kim
Yonsei University, Seoul 03722
K. Kinoshita
University of Cincinnati, Cincinnati, Ohio 45221
P. Kodyš
Faculty of Mathematics and Physics, Charles University, 121 16 Prague
T. Konno
Kitasato University, Sagamihara 252-0373
A. Korobov
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
S. Korpar
Faculty of Chemistry and Chemical Engineering, University of Maribor, 2000 Maribor
J. Stefan Institute, 1000 Ljubljana
E. Kovalenko
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
P. Križan
Faculty of Mathematics and Physics, University of Ljubljana, 1000 Ljubljana
J. Stefan Institute, 1000 Ljubljana
R. Kroeger
University of Mississippi, University, Mississippi 38677
P. Krokovny
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
M. Kumar
Malaviya National Institute of Technology Jaipur, Jaipur 302017
R. Kumar
Punjab Agricultural University, Ludhiana 141004
K. Kumara
Wayne State University, Detroit, Michigan 48202
Y.-J. Kwon
Yonsei University, Seoul 03722
Y.-T. Lai
Kavli Institute for the Physics and Mathematics of the Universe (WPI), University of Tokyo, Kashiwa 277-8583
J. S. Lange
Justus-Liebig-Universität Gießen, 35392 Gießen
M. Laurenza
INFN - Sezione di Roma Tre, I-00146 Roma
Dipartimento di Matematica e Fisica, Università di Roma Tre, I-00146 Roma
S. C. Lee
Kyungpook National University, Daegu 41566
J. Li
Kyungpook National University, Daegu 41566
L. K. Li
University of Cincinnati, Cincinnati, Ohio 45221
Y. B. Li
Peking University, Beijing 100871
L. Li Gioi
Max-Planck-Institut für Physik, 80805 München
J. Libby
Indian Institute of Technology Madras, Chennai 600036
K. Lieret
Ludwig Maximilians University, 80539 Munich
D. Liventsev
Wayne State University, Detroit, Michigan 48202
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
C. MacQueen
School of Physics, University of Melbourne, Victoria 3010
M. Masuda
Earthquake Research Institute, University of Tokyo, Tokyo 113-0032
Research Center for Nuclear Physics, Osaka University, Osaka 567-0047
T. Matsuda
University of Miyazaki, Miyazaki 889-2192
M. Merola
INFN - Sezione di Napoli, I-80126 Napoli
Università di Napoli Federico II, I-80126 Napoli
F. Metzner
Institut für Experimentelle Teilchenphysik, Karlsruher Institut für Technologie, 76131 Karlsruhe
K. Miyabayashi
Nara Women’s University, Nara 630-8506
R. Mizuk
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
National Research University Higher School of Economics, Moscow 101000
G. B. Mohanty
Tata Institute of Fundamental Research, Mumbai 400005
R. Mussa
INFN - Sezione di Torino, I-10125 Torino
M. Nakao
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193
A. Natochii
University of Hawaii, Honolulu, Hawaii 96822
L. Nayak
Indian Institute of Technology Hyderabad, Telangana 502285
M. Nayak
School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978
M. Niiyama
Kyoto Sangyo University, Kyoto 603-8555
N. K. Nisar
Brookhaven National Laboratory, Upton, New York 11973
S. Nishida
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193
S. Ogawa
Toho University, Funabashi 274-8510
H. Ono
Nippon Dental University, Niigata 951-8580
Niigata University, Niigata 950-2181
P. Oskin
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
P. Pakhlov
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
Moscow Physical Engineering Institute, Moscow 115409
G. Pakhlova
National Research University Higher School of Economics, Moscow 101000
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
T. Pang
University of Pittsburgh, Pittsburgh, Pennsylvania 15260
H. Park
Kyungpook National University, Daegu 41566
S.-H. Park
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
A. Passeri
INFN - Sezione di Roma Tre, I-00146 Roma
S. Patra
Indian Institute of Science Education and Research Mohali, SAS Nagar, 140306
S. Paul
Department of Physics, Technische Universität München, 85748 Garching
Max-Planck-Institut für Physik, 80805 München
T. K. Pedlar
Luther College, Decorah, Iowa 52101
R. Pestotnik
J. Stefan Institute, 1000 Ljubljana
L. E. Piilonen
Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061
T. Podobnik
Faculty of Mathematics and Physics, University of Ljubljana, 1000 Ljubljana
J. Stefan Institute, 1000 Ljubljana
V. Popov
National Research University Higher School of Economics, Moscow 101000
E. Prencipe
Forschungszentrum Jülich, 52425 Jülich
M. T. Prim
University of Bonn, 53115 Bonn
M. Röhrken
Deutsches Elektronen–Synchrotron, 22607 Hamburg
A. Rostomyan
Deutsches Elektronen–Synchrotron, 22607 Hamburg
N. Rout
Indian Institute of Technology Madras, Chennai 600036
G. Russo
Università di Napoli Federico II, I-80126 Napoli
D. Sahoo
Tata Institute of Fundamental Research, Mumbai 400005
S. Sandilya
Indian Institute of Technology Hyderabad, Telangana 502285
L. Santelj
Faculty of Mathematics and Physics, University of Ljubljana, 1000 Ljubljana
J. Stefan Institute, 1000 Ljubljana
T. Sanuki
Department of Physics, Tohoku University, Sendai 980-8578
V. Savinov
University of Pittsburgh, Pittsburgh, Pennsylvania 15260
G. Schnell
Department of Physics, University of the Basque Country UPV/EHU, 48080 Bilbao
IKERBASQUE, Basque Foundation for Science, 48013 Bilbao
C. Schwanda
Institute of High Energy Physics, Vienna 1050
A. J. Schwartz
University of Cincinnati, Cincinnati, Ohio 45221
Y. Seino
Niigata University, Niigata 950-2181
K. Senyo
Yamagata University, Yamagata 990-8560
M. E. Sevior
School of Physics, University of Melbourne, Victoria 3010
M. Shapkin
Institute for High Energy Physics, Protvino 142281
C. Sharma
Malaviya National Institute of Technology Jaipur, Jaipur 302017
C. P. Shen
Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics, Fudan University, Shanghai 200443
J.-G. Shiu
Department of Physics, National Taiwan University, Taipei 10617
F. Simon
Max-Planck-Institut für Physik, 80805 München
J. B. Singh
Panjab University, Chandigarh 160014
A. Sokolov
Institute for High Energy Physics, Protvino 142281
E. Solovieva
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
M. Starič
J. Stefan Institute, 1000 Ljubljana
Z. S. Stottler
Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061
J. F. Strube
Pacific Northwest National Laboratory, Richland, Washington 99352
M. Sumihama
Gifu University, Gifu 501-1193
T. Sumiyoshi
Tokyo Metropolitan University, Tokyo 192-0397
W. Sutcliffe
University of Bonn, 53115 Bonn
M. Takizawa
Showa Pharmaceutical University, Tokyo 194-8543
J-PARC Branch, KEK Theory Center, High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
Meson Science Laboratory, Cluster for Pioneering Research, RIKEN, Saitama 351-0198
U. Tamponi
INFN - Sezione di Torino, I-10125 Torino
K. Tanida
Advanced Science Research Center, Japan Atomic Energy Agency, Naka 319-1195
F. Tenchini
Deutsches Elektronen–Synchrotron, 22607 Hamburg
K. Trabelsi
Université Paris-Saclay, CNRS/IN2P3, IJCLab, 91405 Orsay
M. Uchida
Tokyo Institute of Technology, Tokyo 152-8550
T. Uglov
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
National Research University Higher School of Economics, Moscow 101000
Y. Unno
Department of Physics and Institute of Natural Sciences, Hanyang University, Seoul 04763
K. Uno
Niigata University, Niigata 950-2181
S. Uno
High Energy Accelerator Research Organization (KEK), Tsukuba 305-0801
SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193
Y. Usov
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
S. E. Vahsen
University of Hawaii, Honolulu, Hawaii 96822
R. Van Tonder
University of Bonn, 53115 Bonn
G. Varner
University of Hawaii, Honolulu, Hawaii 96822
K. E. Varvell
School of Physics, University of Sydney, New South Wales 2006
A. Vinokurova
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
C. H. Wang
National United University, Miao Li 36003
E. Wang
University of Pittsburgh, Pittsburgh, Pennsylvania 15260
M.-Z. Wang
Department of Physics, National Taiwan University, Taipei 10617
P. Wang
Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049
X. L. Wang
Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) and Institute of Modern Physics, Fudan University, Shanghai 200443
J. Wiechczynski
H. Niewodniczanski Institute of Nuclear Physics, Krakow 31-342
E. Won
Korea University, Seoul 02841
B. D. Yabsley
School of Physics, University of Sydney, New South Wales 2006
W. Yan
Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026
S. B. Yang
Korea University, Seoul 02841
H. Ye
Deutsches Elektronen–Synchrotron, 22607 Hamburg
J. Yelton
University of Florida, Gainesville, Florida 32611
J. H. Yin
Korea University, Seoul 02841
Y. Yusa
Niigata University, Niigata 950-2181
Z. P. Zhang
Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei 230026
V. Zhilich
Budker Institute of Nuclear Physics SB RAS, Novosibirsk 630090
Novosibirsk State University, Novosibirsk 630090
V. Zhukova
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991
Abstract
We present a measurement of the branching fractions of the Cabibbo favored and the Cabibbo suppressed decays. We find and decays, where the first uncertainty is statistical,
the second is systematic, and the third uncertainty is due to the branching fraction. The ratio of branching fractions of and is measured to be . These measurements are performed using the full Belle dataset, which corresponds to pairs and use the Belle II software framework for data analysis.
††preprint: Belle Preprint 2021-25KEK Preprint 2021-30
I Introduction
Two-body decays of mesons serve as an important test bed for phenomenological studies of the quark flavor sector of the Standard Model of particle physics. The Cabibbo-favored mode is an especially clean and abundant hadronic decay that provides a good opportunity to test models of hadronic meson decays. Due to the large mass of the quark, the influence of the strong interaction in these decays can be calculated more reliably than those in light-meson decays. It has been suggested that improved measurements of color-favored hadronic two-body decays of mesons will lead to a better understanding of poorly known quantum chromodynamics (QCD) effects cite-qcdeffetcs . The decays of mesons to two-body hadronic final states can be analyzed by decomposing their amplitudes in terms of different decay topologies and then applying SU(3) flavor symmetry of QCD to derive relations between them. The Cabibbo-suppressed mode only receives contributions from color-allowed tree amplitudes while receives contributions from both color-allowed tree and exchange amplitudes cite-arXiv:1012.2784 . These two decay modes can be related by a ratio cite-belleold ,
(1)
where is the Cabibbo angle, and and are meson decay constants. The theoretical description for these hadronic decays has considerably improved over the years cite-theory1 ; cite-theory2 and has been followed by several recent developments cite-arXix1606.02888 ; cite-arXiv:2007.10338 . This description relies on factorization and SU(3)-symmetry assumptions, so measurements of these modes can be used to test these hypotheses in heavy-quark hadronic decays. The above two modes are also important because they constitute high-statistics control samples for the hadronic -decay measurements related to time-dependent violation and the extraction of the Cabibbo-Kobayashi-Maskawa unitarity-triangle angle cite-theory3 . Experimentally, calculating the ratio of the branching fractions of and modes has the advantage that many systematic uncertainties cancel, enabling tests of theoretical predictions, particularly those of factorization and SU(3) symmetry breaking in QCD.
The theoretical predictions made in Refs. cite-arXix1606.02888 ; cite-arXiv:2007.10338 are based on the framework of QCD factorization, at next-to-next-to-leading order. However, these predictions significantly differ from the experimental values. Several attempts cite-arXiv:2103.04138 ; cite-arXiv:2109.04950 ; cite-arXiv:2008.01086 have been made to explain the discrepancy in both and decays within the context of new physics. Final-state rescattering effects on have also been proposed to explain the discrepancy cite-arXiv:2109.10811 . The results in Ref. cite-arXiv:2109.10811 rule out rescattering effects as a cause for the discrepancies and hence hint at a possible beyond-the-SM explanation.
Earlier, Belle reported a study of the Cabibbo-suppressed decay using a small data datasetset cite-belleold by measuring the ratio of branching fraction of Cabibbo-suppressed to that of the Cabibbo-favored decay. The branching fraction for decay was previously measured by BABAR cite-BaBar1 ; cite-BaBar2 , CLEO cite-cleo1 ; cite-cleo2 and ARGUS cite-argus . LHCb measured the branching fraction of as well as the ratio of hadronization fractions cite-DKlhcb . A clear understanding of decays constitutes an important ingredient for the measurement , which in turn will aid the measurement of rare decay . Currently, the world averages cite-PDG for the branching fractions of and decays are and , respectively, where the uncertainty is the sum in quadrature of the statistical and systematic errors. LHCb cite-ratiolhcb measured the ratio of the branching fractions for and to be , which dominates the current world-average value.
In this paper, we present measurements of the branching fractions of and decays using the full dataset collected with the Belle detector.
The paper is organized as follows. Sec. II describes the Belle detector, as well as the data and simulation samples used in this analysis. The event selection requirements are outlined in Sec. III. Sec. IV describes how the values of and the branching fraction are determined from the data. The results and the evaluation of systematic uncertainties are described in Sec. V, and the conclusion is given in Sec. VI.
II THE BELLE DETECTOR AND DATA SAMPLE
We use the full data sample containing events recorded with the Belle detector cite-Belle at the KEKB asymmetric-beam-energy collider cite-KEKB . Belle is a large-solid-angle magnetic spectrometer that consists of a silicon vertex detector, a 50-layer central drift chamber (CDC), an array of aerogel threshold Cherenkov counters (ACC), a barrel-like arrangement of time-of-flight scintillation counters (TOF), and an electromagnetic calorimeter comprised of CsI(Tl) crystals. All these detector components are located inside a superconducting solenoid coil that provides a 1.5 T magnetic field cite-Belle .
A Monte Carlo (MC) simulated event sample is used to optimize the event selection, study background and compare the distributions observed in collision data with expectations. A signal-only simulated event sample is utilized to model the features of the signal for fits and determine selection efficiencies. One million signal events are generated for both decay channels. The so-called generic MC sample consists of simulated events that include , , , , and processes in realistic proportions, and corresponds in size to more than five times the data. The generic MC sample is used to study background and make comparisons with the data. The - and -meson decays are simulated with the EvtGen generator cite-EvtGen where the D_DALITZ model is used for the final state. The effect of final-state radiation is simulated by the PHOTOS package cite-PHOTOS . The interactions of particles with the detector are simulated using GEANT3cite-GEANT .
III EVENT SELECTION AND RECONSTRUCTION
We use the Belle II Analysis Software Framework (basf2) cite-basf2 for the decay-chain reconstruction and convert the Belle data to basf2 format using the B2BII software package cite-b2bii . The decays and have nearly the same kinematic properties. The former is used to establish selection criteria on kinematic variables and determine the experimental resolution due to its larger data size compared to the latter. Charged particle tracks originating from collisions are selected by requiring and , where and represent the distance of closest approach to the interaction point (IP) in the plane transverse to and along the axis, respectively. The axis is the direction opposite the beam.
Information from the CDC, ACC, and TOF is used to determine a likelihood ratio for charged particle identification (PID), where and are the likelihoods that a particular track is either a kaon or a pion, respectively. The likelihood value ranges from 0 to 1 where 0 (1) means the track is likely to be a (). To ensure high efficiency and purity, we require for kaon candidates and for pion candidates. The charged candidate is formed using combinations, which is then combined with a prompt hadron to form a candidate. (The inclusion of charge conjugate states is implied throughout this paper.) meson candidates are required to have a mass within of the known mass value cite-PDG , where the Gaussian resolution is approximately . The effective value is obtained by fitting the invariant mass distribution of decays with a double Gaussian function for signal and a first-order polynomial for background as shown in Fig. 1.
Figure 1: Fit to the invariant mass distribution for in data. The black vertical dotted lines show the mass window. The dashed curve shows the signal component and dotted black line shows the background component. The distribution of pulls between the fit and the data points is also shown.
The kinematic variables used to discriminate decays from background are the beam-energy-constrained mass
(2)
and the energy difference
(3)
Here and are the candidate’s energy and momentum, respectively, and is the beam energy; these quantities are calculated in the center-of-mass frame. Natural units = c = 1 are used throughout the paper. For correctly reconstructed signal events, peaks at the known mass of the meson and peaks at zero. We retain the candidates satisfying and .
The background from continuum processes are suppressed by requiring the ratio of the second-to-zeroth order Fox-Wolfram moments cite-r2 to be less than 0.3. This selection removes of the continuum while rejecting of the signal in both and decays. After applying the aforementioned selection criteria, only of events are found to have more than one candidate. In such events, we choose the best candidate as the one having the smallest value of where is the known mass.
The kaon identification efficiency is determined from a kinematically selected sample of high momentum mesons, which is used to calibrate the PID performance. With the application of the requirements for pions and for kaons, the kaon efficiency () value is found to be and the rate of pions misidentified as kaons is .
IV Simultaneous Fit
As the branching fraction is an order of magnitude larger than that of , the former can serve as an excellent calibration sample for the signal determination procedure. Furthermore, there is a significant contamination from decays in the sample in which the fast charged pion is misidentified as a kaon. A simultaneous fit to samples enriched in prompt tracks that are identified as either pions or kaons [], allows us to directly determine this cross feed contribution from data. An unbinned maximum-likelihood fit is performed to extract the signal yield by fitting the distribution simultaneously in pion and kaon enriched samples. The yields of the and signals, as well as their cross feed contributions, in the pion and kaon enriched samples can be expressed by the following relations:
(4)
(5)
(6)
(7)
Here the values of are the kaon and the pion yields in pion enriched sample with [], and the are the kaon and pion yields in the kaon enriched sample with []. The pion misidentification rate is a free parameter, as well as and , where the latter is the total signal yield for the decay. Due to a small contribution from cross feed in the pion-enriched sample, the kaon identification efficiency is fixed to the value given in Sec. III. The yields are obtained from fitting the distribution. The background components are divided into the following categories in the fit:
1.
continuum background and combinatorial background, in which the final state particles could be from either the or meson in an event; and
2.
cross feed background from , where , in which the charged kaon is misidentified as a pion or vice versa.
The signal distributions are represented by the sum of a double Gaussian function and an asymmetric Gaussian with a common mean. These signal probability density functions (PDFs) are common to both kaon- and pion-enhanced samples. The means of the signal PDFs for and are directly extracted from the data, along with a single scaling factor to the narrowest signal Gaussian to account for any difference in resolution between simulated and data samples. Other parameters are fixed to those obtained from a fit to a large simulated sample of signal events.
A combined PDF is used to model combinatorial background consisting of continuum background and background for () decay, where the continuum is modeled with a first-order polynomial and the combinatorial background with an exponential function. The slope of the linear background and the exponential function’s exponent are determined from the fit to data; other parameters are fixed to those obtained from a fit to the corresponding simulated sample.
The cross feed background is described by a double Gaussian function in the () sample. The mean and scale factor for the cross feed component PDF in the kaon-enhanced sample are determined from the fit to data.
There is a background that can peak in the same manner as the signal mode, which we call the “peaking background”. The most prominent decay that peaks in the distribution is or . This source accounts for 2 of the total background. To reject this contamination arising due to leptons misidentified as pions, we veto candidates with an invariant mass value falling within of the known mass cite-PDG . This essentially removes this peaking background with 3 signal loss. The remaining peaking background contributions include semileptonic decays for which the normalization is fixed from MC simulation. All yields are determined from a fit to data except for the peaking background yield. The uncertainty associated with the fixed peaking component is included in the systematic uncertainties. All other shape parameters are fixed to their MC values. The yields obtained from the fit are listed in Table 1, and the signal-enhanced fit projections for the data are shown in Fig. 2.
Table 1: Various event yields and their statistical uncertainties obtained from the simultaneous fit.
Parameter
Fit value
total yield
background yield
background yield
Figure 2: distributions for candidates obtained from the (left) pion-enriched and (right) kaon-enriched data samples. The projections of the combined fit and individual components of a simultaneous unbinned maximum-likelihood fit are overlaid. The long-dashed red curve shows the component. The large-dotted magenta curve shows the component. The small-dotted gray curve shows the combinatorial background component and the dash-dotted green curve show the peaking background component in decay. The distribution of pulls between the fit and the data points is also shown.
V RESULTS
The branching fraction of decay is calculated as,
(8)
where is the yield of obtained from the fit, is the total number of pairs, is the detection efficiency for determined from signal MC events where the error is the associated statistical error from MC sample. The factor represents the neutral meson production ratio at the , which is cite-PDG , and is the subdecay branching fraction of , which is cite-PDG . The branching fraction for decay is calculated by multiplying the value from the fit by the calculated branching fraction.
The systematic uncertainties in the measurements from various sources are listed in Table 2. Since the kinematics of and processes are similar, most of the systematic effects cancel in the ratio of their branching fractions. The main source of systematic uncertainty that does not cancel is the uncertainty in identification efficiency. All the sources of systematic uncertainty are assumed to be independent, such that the total uncertainty is the quadratic sum of their contributions. The uncertainty associated with the subdecay branching fraction is taken from its world average cite-PDG . The uncertainty due to prompt tracking efficiency is based on a previous study of high momentum tracks. Tracking efficiency is calculated as the ratio between partially and fully reconstructed decays in data and MC events. The entry for represents the uncertainty in the total number of events in data. Here refers to the uncertainty due to branching fraction calculated from PDG 2020 cite-PDG along with the uncertainty due to isospin asymmetry calculated in cite-isospin . The efficiency variation due to the model is evaluated by varying the model and adding a phase space component. The resulting difference with respect to the measured central value of the branching fraction is treated as a systematic uncertainty. The systematic uncertainty due to PDFs for the components and the cross feed components are evaluated by varying the fixed shape parameters by . The uncertainty due to the kaon identification efficiency is calculated by varying the measured value by its uncertainty obtained in data from the calibration sample as described in Sec. III. The mass window and for veto position have been varied and the resulting difference with respect to the measured branching fraction is taken as a systematic. The uncertainty due to the peaking background is obtained by varying its yield by the statistical uncertainty in its estimation. The uncertainty associated with the reconstruction efficiency is measured using signal MC data samples. We perform tests to validate the fit procedure and determine any possible bias in the fit procedure. The bias is not corrected and is used as a systematic uncertainty. The uncertainty due to the continuum suppression requirement is found to be negligible.
Table 2: Systematic uncertainties in the measured value and branching fractions for and . The total systematic uncertainty is the quadratic sum of the uncorrelated uncertainties.
Source
–
1.71
1.71
Tracking
–
1.40
1.40
–
1.37
1.37
–
1.92
1.92
model
–
PDF parametrization
1.63
PID efficiency of
mass selection window
0.56
veto selection
0.004
Peaking background yield
0.04
MC statistics
0.04
0.04
Fit bias
–
0.58
Total
The ratio of branching fractions is found to be,
(9)
The total yield from the simultaneous fit is used to determine the branching fraction of the decay,
(10)
where the first uncertainty is statistical, the second is systematic, and the third is associated with branching fraction. The branching fraction of is calculated by multiplying Eq. (9) by Eq. (10),
(11)
The value obtained from the fit is , which agrees within one standard deviations with the expected pion misidentification rate as given in Sec. III. In both measurements listed in Eqs. (10) and (11), one of the dominant sources of systematic uncertainty arises from the fixed PDF parametrization.
VI Conclusion
In summary, we have reported measurements of the branching fraction ratio between Cabibbo suppressed and Cabibbo favored using the full data sample collected by the Belle experiment, which supersedes the previous Belle measurement cite-belleold . We also present a measurement of the branching fractions for and decays.The branching fraction and values are compatible with the corresponding world averages cite-PDG within their uncertainties. Individual branching fractions of and deviate from the theory predictions in Refs. cite-arXix1606.02888 ; cite-arXiv:2007.10338 , however, the ratio agrees within uncertainties.
Acknowledgements
We thank the KEKB group for the excellent operation of the
accelerator; the KEK cryogenics group for the efficient
operation of the solenoid; and the KEK computer group, and the Pacific Northwest National
Laboratory (PNNL) Environmental Molecular Sciences Laboratory (EMSL)
computing group for strong computing support; and the National
Institute of Informatics, and Science Information NETwork 5 (SINET5) for
valuable network support. We acknowledge support from
the Ministry of Education, Culture, Sports, Science, and
Technology (MEXT) of Japan, the Japan Society for the
Promotion of Science (JSPS), and the Tau-Lepton Physics
Research Center of Nagoya University;
the Australian Research Council including Grants No.
DP180102629, No. DP170102389, No. DP170102204, No. DP150103061, and No. FT130100303; Austrian Federal Ministry of Education, Science and Research (FWF) and
FWF Austrian Science Fund No. P 31361-N36;
the National Natural Science Foundation of China under Contracts
No. 11435013, No. 11475187, No. 11521505, No. 11575017, No. 11675166, and No. 11705209; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS), Grant No. QYZDJ-SSW-SLH011; the CAS Center for Excellence in Particle Physics (CCEPP); the Shanghai Science and Technology Committee (STCSM) under Grant No. 19ZR1403000; the Ministry of Education, Youth and Sports of the Czech
Republic under Contract No. LTT17020;
Horizon 2020 ERC Advanced Grant No. 884719 and ERC Starting Grant No. 947006 “InterLeptons” (European Union);
the Carl Zeiss Foundation, the Deutsche Forschungsgemeinschaft, the
Excellence Cluster Universe, and the VolkswagenStiftung;
the Department of Atomic Energy (Project Identification No. RTI 4002) and the Department of Science and Technology of India;
the Istituto Nazionale di Fisica Nucleare of Italy;
National Research Foundation (NRF) of Korea Grants
No. 2016R1D1A1B01010135, No. 2016R1D1A1B02012900, No. 2018R1A2B3003643,
No. 2018R1A6A1A06024970, No. 2019K1A3A7A09033840,
No. 2019R1I1A3A01058933, No. 2021R1A6A1A03043957,
No. 2021R1F1A1060423, No. 2021R1F1A1064008;
Radiation Science Research Institute, Foreign Large-size Research Facility Application Supporting project, the Global Science Experimental Data Hub Center of the Korea Institute of Science and Technology Information and KREONET/GLORIAD;
the Polish Ministry of Science and Higher Education and
the National Science Center;
the Ministry of Science and Higher Education of the Russian Federation, Agreement 14.W03.31.0026, and the HSE University Basic Research Program, Moscow; University of Tabuk research Grants No.
S-1440-0321, No. S-0256-1438, and No. S-0280-1439 (Saudi Arabia);
the Slovenian Research Agency Grants No. J1-9124 and No. P1-0135;
Ikerbasque, Basque Foundation for Science, Spain;
the Swiss National Science Foundation;
the Ministry of Education and the Ministry of Science and Technology of Taiwan;
and the United States Department of Energy and the National Science Foundation.
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