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Measurement of the integrated luminosity of data samples collected during 2019-2022 by the Belle II experiment*
I. Adachi, L. Aggarwal, H. Ahmed, J. K. Ahn, H. Aihara, Н. Акопов, A. Aloisio, N. Althubiti, N. Anh Ky, D. M. Asner, H. Atmacan, T. Aushev, V. Aushev, M. Aversano, R. Ayad, V. Babu, H. Bae, S. Bahinipati, P. Bambade, Sw. Banerjee, M. Barrett, J. Baudot, A. Baur, A. Beaubien, F. Becherer, Jürgen Becker, J. V. Bennett, F. U. Bernlochner, V. Bertacchi, M. Bertemes, E. Bertholet, M. Bessner, S. Bettarini, F. Bianchi, L. Bierwirth, T. Bilka, D. Biswas, D. Bodrov, J. Borah, A. Boschetti, A. Bozek, P. Branchini, T. E. Browder, A. Budano, S. Bussino, Q. Campagna, M. Campajola, L. Cao, G. Casarosa, C. Cecchi, J. Cerasoli, P. Chang, R. Cheaib, P. Cheema, B. G. Cheon, K. Chilikin, K. Chirapatpimol, K. Cho, S. -J. Cho, S. Choudhury, J. Cochran, L. Corona, J. X. Cui, S. Das, E. De La Cruz–Burelo, S. A. De La Motte, G. de Marino, G. De Nardo, G. De Pietro, R. de Sangro, M. Destefanis, S. Dey, R. Dhamija, A. Di Canto, F. Di Capua, J. Dingfelder, Z. Doležal, I. Domínguez Jiménez, T. V. Dong, K. Dort, D. Dossett, S. Dubey, K. Dugic, G. Dujany, P. Ecker, D. Epifanov, P. Feichtinger, T. Ferber, T. Fillinger, C. Finck, G. Finocchiaro, A. Fodor, F. Forti, A. Frey, B. G. Fulsom, A. Gabrielli, E. Ganiev, M. Garcia-Hernandez, R. Garg, G. Gaudino, V. Gaur, A. Gaz, A. Gellrich, G. Ghevondyan, Dilip Ghosh, H. Ghumaryan, G. Giakoustidis, R. Giordano, A. Giri, B. Gobbo, R. Godang, O. Gogota, P. Goldenzweig, W. Gradl, E. Graziani, D. Greenwald, Z. Gruberová, T. Gu, K. Gudkova, I. Haide, S. Halder, Y. F. Han, K. Hara, T. Hara, C. Harris, K. Hayasaka, H. Hayashii, S. Hazra, C. Hearty, M. T. Hedges, A. Heidelbach, I. Heredia-De La Cruz, M. Hernández Villanueva, T. Higuchi, M. Hohmann, Richard T. Hoppe, P. Horak, T. Humair, K. Inami, N. Ipsita, A. Ishikawa, R. Itoh, M. Iwasaki, W. W. Jacobs, D. E. Jaffe, E. -J. Jang, Q. P. Ji, S. Jia, Y. Jin, A. Johnson, K. K. Joo, H. Junkerkalefeld, M. Kaleta, Dibyajyoti Kalita, J. Kandra, K. H. Kang, G. Karyan, T. Kawasaki, F. Keil, C. Kiesling, C. -H. Kim, D. Y. Kim, Jae-Young Kim, K. -H. Kim, Y. -K. Kim, H. Kindo, K. Kinoshita, P. Kodyš, T. Koga, S. Kohani, K. Kojima, A. Korobov, S. Korpar, E. Kovalenko, R. Kowalewski, P. Križan, P. Krokovny, T. Kuhr, R. Kumar, K. Kumara, A. Kuzmin, Y. -J. Kwon, S. Lacaprara, Y. -T. Lai, K. Lalwani, T. Lam, L. Lanceri, J. S. Lange, M. Laurenza, K. Lautenbach, R. Leboucher, M. J. Lee, C. Lemettais, Peter Leo, D. Levit, P. M. Lewis, C. Li, L. K. Li, S. X. Li, W. Z. Li, Y. Li, Y. B. Li, Y. P. Liao, J. Libby, J. Lin, M. H. Liu, Q. Y. Liu, Z. Q. Liu, D. Liventsev, S. Longo, T. Lueck, C. Lyu, Yujia Ma, M. Maggiora, S. P. Maharana, R. Maiti, S. Maity, G. Mancinelli, R. Manfredi, E. Manoni, M. Mantovano, D. Marcantonio, S. Marcello, C. Mariñas, C. Martellini, A. Martens, A. Martini, T. Martinov, L. Massaccesi, M. Masuda, D. Matvienko, S. K. Maurya, J. A. McKenna, R. Mehta, F. Meier, M. Merola, C. Miller, M. Mirra, S. Mitra, K. Miyabayashi, G. B. Mohanty, S. Mondal, S. Moneta, R. Mussa, I. Nakamura, M. Nakao, Y. Nakazawa, M. Naruki, D. Narwal, Z. Natkaniec, A. Natochii, M. Nayak, G. Nazaryan, M. Neu, C. Niebuhr, S. Nishida, S. Ogawa, Y. Onishchuk, H. Ono, P. Pakhlov, G. Pakhlova, E. Paoloni, S. Pardi, K. Parham, H. Park, J. Park, K. Park, S. -H. Park, B. Paschen, A. Passeri, S. Patra, T. K. Pedlar, R. Peschke, R. Pestotnik, G. Pinna Angioni, P. L. M. Podesta-Lerma, T. Podobnik, S. Pokharel, C. Praz, S. Prell, E. Prencipe, M. T. Prim, H. Purwar, P. Rados, G. Raeuber, S. Raiz, N. Rauls, M. Reif, S. Reiter, M. Remnev, L. Reuter, I. Ripp-Baudot, G. Rizzo, S. H. Robertson, M. Röhrken, J. M. Roney, A. Rostomyan, N. Rout, S. Sandilya, L. Santelj, Y. Sato, V. Savinov, B. Scavino, M. Schnepf, C. Schwanda, A. J. Schwartz, Y. Seino, A. Selce, K. Senyo, J. Serrano, C. Sfienti, C. Sharma, C. P. Shen, X. D. Shi, T. Shillington, T. Shimasaki, D. Shtol, B. Shwartz, A. Sibidanov, F. Simon, J. B. Singh, J. Skorupa, R. Sobie, M. Sobotzik, A. Soffer, A. Sokolov, E. Solovieva, W. M. Song, B. Spruck, M. Starič, P. Stavroulakis, S. Stefkova, R. Stroili, Y. Sue, M. Sumihama, K. Sumisawa, W. Sutcliffe, N. Suwonjandee, H. Svidras, M. Takahashi, M. Takizawa, U. Tamponi, K. Tanida, F. Tenchini, A. Thaller, O. Tittel, R. Tiwary, E. Torassa, K. Trabelsi, I. Ueda, K. Unger, Y. Unno, K. Uno, S. Uno, P. Urquijo, Y. Ushiroda, S. Vahsen, R. van Tonder, K. E. Varvell, M. Veronesi, A. Vinokurova, V. S. Vismaya, L. Vitale, V. Vobbilisetti, R. Volpe, A. Vossen, M. Wakai, S. Wallner, E. Wang, Z. Wang, A. Warburton, Shun Watanuki, C. Wessel, E. Won, X. P. Xu, B. Yabsley, S. Yamada, W. Yan, S. B. Yang, J. Yelton, J. H. Yin, K. Yoshihara, C. Z. Yuan, L. Zani, B. Zhang, V. Zhilich, J. S. Zhou, Q. D. Zhou, V. Zhukova, R. Žlebčík
Bibliographic record
VenueChinese Physics C · 2024
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersInstitut National de Physique Nucléaire et de Physique des ParticulesAkademi Sains MalaysiaJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of CanadaKorea Research Environment Open NetworkNational Science and Technology CouncilCentro de Investigación y de Estudios Avanzados del Instituto Politécnico NacionalIstituto Nazionale di Fisica NucleareMinistry of Science and Higher Education of the Russian FederationNational Research University Higher School of EconomicsJavna Agencija za Raziskovalno Dejavnost RSNational Research Foundation of UkraineMax-Planck-GesellschaftKnut och Alice Wallenbergs StiftelseDeutsches Elektronen-SynchrotronThailand Center of Excellence in PhysicsGeneralitat ValencianaNational Research FoundationAustrian Science FundU.S. Department of EnergyNational Natural Science Foundation of ChinaMinistry of Education, Culture, Sports, Science and TechnologyDeutsche ForschungsgemeinschaftGrantová Agentura České RepublikyAlexander von Humboldt-StiftungBundesministerium für Bildung, Wissenschaft und ForschungMinistry of Education and Science of UkraineVietnam Academy of Science and TechnologyNatural Science Foundation of Shandong ProvinceCompute CanadaUniversity of TabukNational Science FoundationKorea Institute of Science and TechnologyBundesministerium für Bildung und ForschungCanarieTürkiye Bilimsel ve Teknolojik Araştırma KurumuAgence Nationale de la RechercheGrantová Agentura, Univerzita KarlovaCentre National de la Recherche ScientifiqueUniverzita Karlova v Praze
KeywordsLuminosityPhysicsAstrophysics
Abstract
Abstract A series of data samples was collected with the Belle II detector at the SuperKEKB collider from March 2019 to June 2022. We determine the integrated luminosities of these data samples using three distinct methodologies involving Bhabha ( ), digamma ( ), and dimuon ( ) events. The total integrated luminosity obtained with Bhabha, digamma, and dimuon events is (426.88 ± 0.03 ± 2.61) fb −1 , (429.28 ± 0.03 ± 2.62) fb −1 , and (423.99 ± 0.04 ± 3.83) fb −1 , where the first uncertainties are statistical and the second are systematic. The resulting total integrated luminosity obtained from the combination of the three methods is (427.87 ± 2.01) fb −1 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
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 score0.525
Threshold uncertainty score0.981
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.026 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 head0.019
GPT teacher head0.235
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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
Citations22
Published2024
Admission routes1
Has abstractyes