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Improved Limits on Millicharged Particles Using the ArgoNeuT Experiment at Fermilab

2020· article· en· W2990707528 on OpenAlexfundno aff
R. Acciarri, C. Adams, J. Asaadi, B. Baller, T. Bolton, C. Bromberg, F. Cavanna, D. Edmunds, R. S. Fitzpatrick, B. Fleming, Roni Harnik, C. James, I. Lepetic, B. R. Littlejohn, Zhen Liu, X. Luo, O. Palamara, G. Scanavini, M. Söderberg, J. Spitz, A. M. Szelc, W. Wu, T. Yang

Bibliographic record

VenuePhysical Review Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsFermilabInstitut National de Physique Nucléaire et de Physique des ParticulesFundação para a Ciência e a TecnologiaAgencia Nacional de Promoción Científica y TecnológicaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungScience and Technology Facilities CouncilMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Bildung und ForschungNatural Sciences and Engineering Research Council of CanadaEuropean Social FundRoyal SocietyCentre National pour la Recherche Scientifique et TechniqueJapan Society for the Promotion of ScienceNational Research Center "Kurchatov Institute"European Regional Development FundBritish Columbia Knowledge Development FundMax-Planck-GesellschaftCentre National de la Recherche ScientifiqueIsrael Science FoundationComisión Nacional de Investigación Científica y TecnológicaTürkiye Atom Enerjisi KurumuJoint Institute for Nuclear ResearchMinisterstwo Edukacji i NaukiConselho Nacional de Desenvolvimento Científico e TecnológicoOffice of ScienceBundesministerium für Wissenschaft, Forschung und WirtschaftGeneralitat de CatalunyaGeneralitat ValencianaAustrian Science FundU.S. Department of EnergyNational Natural Science Foundation of ChinaEuropean CommissionLeverhulme TrustFundação de Amparo à Pesquisa do Estado de São PauloJavna Agencija za Raziskovalno Dejavnost RSAgence Nationale de la RechercheServices Fédéraux des Affaires Scientifiques, Techniques et CulturellesDepartment of Science and Technology, Ministry of Science and Technology, IndiaGeneral Secretariat for Research and TechnologyDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekNeutrino Physics CenterNational Science FoundationCompute CanadaAlexander von Humboldt-StiftungHigh Energy PhysicsTRIUMFAchievement Rewards for College Scientists FoundationDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)Centres de Recerca de CatalunyaCERNDanmarks GrundforskningsfondCanarie
KeywordsFermilabPhysicsTime projection chamberDetectorParticle physicsNuclear physicsRange (aeronautics)Event (particle physics)Parameter spaceElectronAstrophysicsOpticsAerospace engineeringStatistics

Abstract

fetched live from OpenAlex

A search for millicharged particles, a simple extension of the standard model, has been performed with the ArgoNeuT detector exposed to the Neutrinos at the Main Injector beam at Fermilab. The ArgoNeuT liquid argon time projection chamber detector enables a search for millicharged particles through the detection of visible electron recoils. We search for an event signature with two soft hits (MeV-scale energy depositions) aligned with the upstream target. For an exposure of the detector of 1.0×10^{20} protons on target, one candidate event has been observed, compatible with the expected background. This search is sensitive to millicharged particles with charges between 10^{-3}e and 10^{-1}e and with masses in the range from 0.1 to 3 GeV. This measurement provides leading constraints on millicharged particles in this large unexplored parameter space region.

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)0.002
metaresearch head score (Gemma)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.041
GPT teacher head0.293
Teacher spread0.252 · 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

Citations104
Published2020
Admission routes1
Has abstractyes

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