Record W4313404107 · doi:10.1088/1674-1137/acac69

Search for hidden-charm tetraquark with strangeness in *

2022· article· en· W4313404107 on OpenAlexaff

М. Н. Ачасов, P. Adlarson, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, V. Batozskaya, D. Becker, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, E. Bianco, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, H. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Çetin, J. F. Chang, W. L. Chang, G. Chelkov, C. Chen, Chao Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, Shaomin Chen, T. Chen, X. R. Chen, X. T. Chen, Y. B. Chen, Z. J. Chen, S. K. Choi, X. Chu, G. Cibinetto, F. Cossio, J. J. Cui, H. L. Dai, J. P. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Z. H. Duan, P. Egorov, Y. L. Fan, J. Fang, S. S. Fang, Wenxing Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, K. Fischer, M. Fritsch, C. Fritzsch, C. D. Fu, H. Gao, Y. N. Gao, Yang Gao, S. Garbolino, I. Garzia, P. Ge, Z. W. Ge, C. Geng, E. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, Y. T. Gu, C. Y. Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, W. Y. Han, X. Q. Hao, F. A. Harris, K. K. He, K. L. He, F. H. Heinsius, C. H. Heinz, Y. K. Heng, C. Herold, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, K. X. Huang, L. Q. Huang, X. T. Huang, Y. Huang, Z. Huang, T. Hussain, N. Hüsken, W. Imoehl, M. Irshad, P. Jackson, S. Jaeger, S. Janchiv, E.-J. Jang, J. H. Jeong, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, Z. Jiao, P. C. Jiang, S. S. Jiang, X. S. Jiang, Y. Jiang, J. B. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, S. Kabana, N. Kalantar-Nayestanaki, X. L. Kang, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupść, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, T. T. Lei, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. Li, H. B. Li, H. J. Li, H. Li, J. Q. Li, J. S. Li, J. W. Li, Ke Li, L. J Li, L. K. Li, Lei Li, M. H. Li, P. R. Li, S. X. Li, S. Y. Li, T. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Y. G. Li, Zhen-Yu Li, Z. Y. Li, C. Liang, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, A. Limphirat, C. X. Lin, D. X. Lin, T. Lin, B. J. Liu, C. Liu, F. H. Liu, D. Liu, Fang Liu, Feng Liu, G. M. Liu, H. Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, Jiayi Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, Lu Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, T. Liu, W. K. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. Lou, F. X. Lu, H. J. Lü, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, Z. H. Lu, C. L. Luo, M. X. Luo, T. Luo, X. L. Luo, X. R. Lyu, Y. F. Lyu, F. C., H. Lü, L. L., M. M., Q. M., R. Q., R. T., X. Y., Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, H. Miao, T. J. Min, R. E. Mitchell, X. H. Mo, N. Yu. Muchnoi, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, Y. Niu, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, Y. P. Pei, M. Pelizaeus, H. P. Peng, Κ. Peters, J. L. Ping, R. G. Ping, S. Plura, S. Pogodin, V. Prasad, F. Z. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, J. J. Qin, L. Q. Qin, X. P. Qin, X. S. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, C. F. Redmer, K. J. Ren, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, S. N. Ruan, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, K. Y. Shan, X. Y. Shan, J. F. Shangguan, L. G. Shao, M. Shao, C. P. Shen, H. F. Shen, W. H. Shen, X. Y. Shen, B. A. Shi, H. Shi, J. Y. Shi, Q. Q. Shi, R. S. Shi, X. Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. Stieler, P. P. Su, Y. J. Su, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. J. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, L. Y. Tao, Q. T. Tao, M. Tat, J. X. Teng, V. Thoren, W. H. Tian, Y. Tian, I. Uman, Bing Wang, B. Wang, B. L. Wang, C. W. Wang, D. Y. Wang, F. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, S. Wang, S. Wang, T. Wang, T. J. Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Yanlong Wang, Y. Q. Wang, Yaqian Wang, Z. Wang, Ziyi Wang, Ziyi Wang, D. H. Wei, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Y. Wu, Y. J. Wu, Z. Wu, T. Xiang, D. Xiao, G. Y. Xiao, H. Xiao, S. Y. Xiao, Y. L. Xiao, Z. J. Xiao, Changsheng Xie, X. H. Xie, Y. Xie, Y. G. Xie, Y. H. Xie, Z. P. Xie, T. Y. Xing, C. F. Xu, C. J. Xu, G. F. Xu, H. Y. Xu, Q. Xu, X. P. Xu, Y. C. Xu, Z. P. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, H. J. Yang, H. L. Yang, H. X. Yang, Tao Yang, Y. F. Yang, Yifan Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, Tao Yu, X. D. Yu, C. Z. Yuan, L. Yuan, S. C. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. A. Zafar, F. R. Zeng, X. Zeng, Y. Zeng, X. Y. Zhai, Y. H. Zhan, A. Q. Zhang, B. L. Zhang, B. X. Zhang, D. H. Zhang, G. Y. Zhang, H. Zhang, H. H. Zhang, H. H. Zhang, H. Q. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. X. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, Peng Zhang, Q. Y. Zhang, Shuihan Zhang, Shulei Zhang, X. D. Zhang, X. M. Zhang, X. Y. Zhang, X. Y. Zhang, Y. Zhang, Y. T. Zhang, Y. H. Zhang, Yan Zhang, Yao Zhang, Z. H. Zhang, Z. L. Zhang, Z. Y. Zhang, Z. Y. Zhang, Gang Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, X. Zhong, H. Zhou, L. P. Zhou, X. R. Zhou, X. K. Zhou, Xiang Zhou, Y. Z. Zhou, J. Zhu, K. J. Zhu, L. Zhu, S. H. Zhu, S. Q. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, J. H. Zou, J. Zu

Bibliographic record

VenueChinese Physics C · 2022

Typearticle

Languageen

FieldPhysics and Astronomy

TopicQuantum Chromodynamics and Particle Interactions

Canadian institutionsInstitute of Particle Physics

FundersFundamental Research Funds for the Central UniversitiesShanghai Key Laboratory for Particle Physics and CosmologyCAS Center for Excellence in Particle PhysicsVetenskapsrådetSuranaree University of TechnologyNational Natural Science Foundation of ChinaIstituto Nazionale di Fisica NucleareDeutsche ForschungsgemeinschaftInstitute of High Energy PhysicsU.S. Department of EnergyEuropean CommissionRoyal SocietyUniversity of Chinese Academy of SciencesChinese Academy of SciencesLanzhou UniversityScience and Technology Facilities CouncilThailand Science Research and InnovationStrong

KeywordsPhysicsStrangenessTetraquarkParticle physicsBranching fractionPrime (order theory)Mass spectrumNuclear physicsBaryonAtomic physicsHadronCombinatoricsQuantum mechanicsMass spectrometry

DOI10.1088/1674-1137/acac69

Abstract

fetched live from OpenAlex

Abstract We report a search for a heavier partner of the recently observed state, denoted as , in the process , based on collision data collected at the center-of-mass energies of , 4.682 and 4.699 GeV with the BESIII detector. The is of interest as it is expected to be a candidate for a hidden-charm and open-strange tetraquark. A partial-reconstruction technique is used to isolate recoil-mass spectra, which are probed for a potential contribution from ( ). We find an excess of ( ) candidates with a significance of , after considering systematic uncertainties, at a mass of . As the data set is limited in size, the upper limits are evaluated at the 90% confidence level on the product of the Born cross sections ( ) and the branching fraction ( ) of , under different assumptions of the mass from 4.120 to 4.140 MeV and of the width from 10 to 50 MeV at the three center-of-mass energies. The upper limits of are found to be at the level of pb at each energy. Larger data samples are needed to confirm the state and clarify its nature in the coming years.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001

metaresearch head score (Gemma)0.001

Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated

Candidate categoriesnone

Consensus categoriesnone

DomainCandidate signal: none · Consensus signal: none

Study designCandidate signal: Bench or experimental · Consensus signal: none

GenreCandidate signal: Empirical · Consensus signal: Empirical

Teacher disagreement score0.002

Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

Category	Codex	Gemma
Metaresearch	0.001	0.001
Meta-epidemiology (narrow)	0.000	0.000
Meta-epidemiology (broad)	0.000	0.000
Bibliometrics	0.001	0.001
Science and technology studies	0.001	0.000
Scholarly communication	0.001	0.000
Open science	0.000	0.001
Research integrity	0.000	0.000
Insufficient payload (model declined to judge)	0.002	0.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015

GPT teacher head0.289

Teacher spread0.274 · how far apart the two teachers sit on this one work

Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.

Study designBench or experimental

Domainnot available

GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6

Published2022

Admission routes1

Has abstractyes

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