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Record W6887798045 · doi:10.17863/cam.54412

Search for dijet resonances in events with an isolated charged lepton using s = 13 TeV proton-proton collision data collected by the ATLAS detector

2020· article· en· W6887798045 on OpenAlexfundno aff

Bibliographic record

VenueApollo (University of Cambridge) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsnot available
FundersEuropean Social FundBritish Columbia Knowledge Development FundFundação para a Ciência e a TecnologiaInstitut National de Physique Nucléaire et de Physique des ParticulesAgencia Nacional de Promoción Científica y TecnológicaScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaCentre National pour la Recherche Scientifique et TechniqueNational Research Center "Kurchatov Institute"Centre National de la Recherche ScientifiqueMax-Planck-GesellschaftIsrael Science FoundationJoint Institute for Nuclear ResearchJapan Society for the Promotion of ScienceConselho Nacional de Desenvolvimento Científico e TecnológicoBundesministerium für Wissenschaft, Forschung und WirtschaftAustrian Science FundU.S. Department of EnergyNational Natural Science Foundation of ChinaFundação de Amparo à Pesquisa do Estado de São PauloJavna Agencija za Raziskovalno Dejavnost RSSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNederlandse Organisatie voor Wetenschappelijk OnderzoekMinistry of Education, Culture, Sports, Science and TechnologyGeneral Secretariat for Research and TechnologyAgence Nationale de la RechercheEuropean CommissionTürkiye Atom Enerjisi KurumuServices Fédéraux des Affaires Scientifiques, Techniques et CulturellesDepartment of Science and Technology, Ministry of Science and Technology, IndiaNational Science FoundationCompute CanadaDeutsche ForschungsgemeinschaftDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)European Regional Development FundBundesministerium für Bildung und ForschungCanarieCentres de Recerca de CatalunyaMinisterstwo Edukacji i NaukiCERNComisión Nacional de Investigación Científica y TecnológicaDanmarks GrundforskningsfondAlexander von Humboldt-Stiftung
KeywordsInvariant massLarge Hadron ColliderAtlas (anatomy)MuonLeptonDetectorATLAS experimentStandard Model (mathematical formulation)Context (archaeology)Dark matter

Abstract

fetched live from OpenAlex

Abstract: A search for dijet resonances in events with at least one isolated charged lepon is performed using 139 fb−1 of s = 13 TeV proton-proton collision data recorded by the ATLAS detector at the LHC. The dijet invariant-mass (mjj) distribution constructed from events with at least one isolated electron or muon is searched in the region 0.22 < mjj< 6.3 TeV for excesses above a smoothly falling background from Standard Model processes. Triggering based on the presence of a lepton in the event reduces limitations imposed by minimum transverse momentum thresholds for triggering on jets. This approach allows smaller dijet invariant masses to be probed than in inclusive dijet searches, targeting a variety of new-physics models, for example ones in which a new state is produced in association with a leptonically decaying W or Z boson. No statistically significant deviation from the Standard Model background hypothesis is found. Limits on contributions from generic Gaussian signals with widths ranging from that determined by the detector resolution up to 15% of the resonance mass are obtained for dijet invariant masses ranging from 0.25 TeV to 6 TeV. Limits are set also in the context of several scenarios beyond the Standard Model, such as the Sequential Standard Model, a technicolor model, a charged Higgs boson model and a simplified Dark Matter model.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.268
Teacher spread0.231 · 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 teacher head, 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

Citations1
Published2020
Admission routes1
Has abstractyes

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