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Measurement of the Centrality Dependence of the Dijet Yield in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>+</mml:mo><mml:mi>Pb</mml:mi></mml:mrow></mml:math> Collisions at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msqrt><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:mi>NN</mml:mi></mml:mrow></mml:msub></mml:msqrt><mml:mo>=</mml:mo><mml:mn>8.16</mml:mn><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>TeV</mml:mi></mml:math> with the ATLAS Detector

2024· preprint· lv· W4386435724 on OpenAlexafffund
G. Aad, B. Abbott, K. Abeling, Nils Julius Abicht, S. H. Abidi, A. Aboulhorma, H. Abramowicz, H. Abreu, Yiming Abulaiti, B. S. Acharya, Claire Adam Bourdarios, L. Adamczyk, Sagar Addepalli, Matt Addison, J. Adelman, A. Adıgüzel, T. Adye, A. A. Affolder, Yoav Afik, M. N. Agaras, J. Agarwala, A. Aggarwal, C. Agheorghiesei, A. Ahmad, F. Ahmadov, W. S. Ahmed, Sudha Ahuja, X. Ai, G. Aielli, A. Aikot, M. Ait Tamlihat, B. Aitbenchikh, I. Aizenberg, M. Akbiyik, T. P. A. Åkesson, A. V. Akimov, Daiya Akiyama, Nilima Nilesh Akolkar, Pavol Bartos, G. Bianco, F. L. Castillo, Shenjian Chen, Xiaotong Chu, Ian Allan Connelly, B. Eckerova, Laura Franconi, Andrea García Alonso, Vincent Hedberg, X. Jia, T. Jones, Alexander Khanov, F. Ledroit, Huanguo Li, Hui Li, X. Li, Yanwen Liu, J. C. MacDonald, Wolfgang Mader, Michael William O'Keefe, S. Rodriguez Bosca, M. Shiyakova, Rongkun Wang, Ligang Xia, Y. Yamazaki, Xiao Yang, Jingbo Ye, Shuwei Ye, Y. Zhang

Bibliographic record

VenuePhysical Review Letters · 2024
Typepreprint
Languagelv
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsUniversity of British ColumbiaYork UniversityUniversity of TorontoSimon Fraser UniversityTRIUMFCarleton UniversityUniversity of AlbertaUniversité de MontréalInstitute of Particle PhysicsUniversity of VictoriaMcGill University
FundersIrish Rugby Football UnionH2020 Marie Skłodowska-Curie ActionsRutherford Appleton LaboratoryAgencia Nacional de Promoción Científica y TecnológicaFundação para a Ciência e a TecnologiaJapan Society for the Promotion of ScienceAustralian Research CouncilNational Research Council CanadaHorizon 2020 Framework ProgrammeAgencia Nacional de Investigación y DesarrolloServices Fédéraux des Affaires Scientifiques, Techniques et CulturellesH2020 European Research CouncilNorges ForskningsrådMinisterio de Ciencia e InnovaciónInstitut National de Physique Nucléaire et de Physique des ParticulesMinistry of Science and Technology, TaiwanCanada Foundation for InnovationConselho Nacional de Desenvolvimento Científico e TecnológicoNarodowe Centrum NaukiKnut och Alice Wallenbergs StiftelseBrookhaven National LaboratoryEuropean Regional Development FundBritish Columbia Knowledge Development FundCentre National de la Recherche ScientifiqueMax-Planck-GesellschaftNella and Leon Benoziyo Center for Neurological Diseases, Weizmann Institute of ScienceCanada Research ChairsGöran Gustafssons Stiftelse för Naturvetenskaplig och Medicinsk ForskningBundesministerium für Wissenschaft, Forschung und WirtschaftGeneralitat ValencianaMinisterio de Ciencia, Tecnología e InnovaciónGeneralitat de CatalunyaDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekChinese Academy of SciencesNatural Sciences and Engineering Research Council of CanadaMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Bildung und ForschungMinisterstvo Školství, Mládeže a TělovýchovyEuropean CommissionLeverhulme TrustFundação de Amparo à Pesquisa do Estado de São PauloGerman-Israeli Foundation for Scientific Research and DevelopmentScience and Technology Facilities CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungMinistry of Science and Technology of the People's Republic of ChinaAgence Nationale de la RechercheAustrian Science FundJavna Agencija za Raziskovalno Dejavnost RSNational Research FoundationNarodowa Agencja Wymiany AkademickiejEuropean Cooperation in Science and TechnologyGeneral Secretariat for Research and TechnologyInstituto Nazionale di Fisica NucleareUnited States-Israel Binational Science FoundationHelmholtz-GemeinschaftDanmarks GrundforskningsfondTürkiye Enerji, Nükleer ve Maden Araştırma KurumuAzərbaycan Milli Elmlər Akademiyası“la Caixa” FoundationEuropean Social FundCentre National pour la Recherche Scientifique et TechniqueRoyal SocietyCompute CanadaNational Science FoundationAlexander von Humboldt-StiftungTRIUMFCentres de Recerca de CatalunyaCERNCanarieIsrael Science FoundationNorth Dakota Game and Fish DepartmentNational Natural Science Foundation of ChinaU.S. Department of Energy
KeywordsPhysicsPartonParticle physicsCentralityScalingValence (chemistry)ScatteringNuclear physicsAtlas (anatomy)ProtonHadronCombinatoricsGeometry

Abstract

fetched live from OpenAlex

ATLAS measured the centrality dependence of the dijet yield using 165 nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16 TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

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 distilled prediction

Teacher imitation

Not 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)0.007
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0030.005
Meta-epidemiology (broad)0.0020.008
Bibliometrics0.0010.005
Science and technology studies0.0050.007
Scholarly communication0.0040.003
Open science0.0100.011
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.1280.005

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 head0.024
GPT teacher head0.261
Teacher spread0.237 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2024
Admission routes2
Has abstractyes

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