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Record W4404545692 · doi:10.1051/epjconf/202431202001

Neutrino Experiments at the LHC

2024· article· en· W4404545692 on OpenAlexaff
U. Köse

Bibliographic record

VenueEPJ Web of Conferences · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsInstitute of Particle Physics
FundersFundação para a Ciência e a TecnologiaJapan Society for the Promotion of ScienceNuclear PhysicsPromotion and Mutual Aid Corporation for Private Schools of JapanTsinghua UniversityNational Natural Science Foundation of ChinaAgencia Nacional de Investigación y DesarrolloNational Research Foundation of KoreaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungMinistry of Education, Culture, Sports, Science and TechnologyInstitute of Materials and Systems for Sustainability, Nagoya UniversityInstitut Català de Nanociència i NanotecnologiaCERNDeutsche ForschungsgemeinschaftNational Research FoundationBundesministerium für Bildung und ForschungTürkiye Enerji, Nükleer ve Maden Araştırma KurumuNational Science Foundation
KeywordsLarge Hadron ColliderNeutrinoParticle physicsPhysicsNuclear physics

Abstract

fetched live from OpenAlex

The LHC neutrino experiments, FASER and SND@LHC were approved by the CERN Research Board in 2019 and 2021, respectively, to operate during LHC Run 3. Both experiments began taking physics data in July 2022 and have since recorded approximately 70 fb -1 of data from proton-proton collisions with a center-of-mass energy of 13.6 TeV. These experiments achieved the first direct observation of neutrino interactions at the LHC, using the active electronic components of their detector. Additionally, FASER ν , using 2% of its data sample, detected the highest-energy ν e and ν µ interactions ever observed from an artificial source and made the first measurements of neutrino interaction cross-sections over energy ranges of 560–1740 GeV for ν e and 520–1760 GeV for ν µ . Additionally, both experiments are actively searching for physics beyond the Standard Model, with FASER already publishing initial results on Dark Photons and Axion-like Particles. In this report, we will discuss the status of the experiments, including the detector concept, performance, and the first physics results from Run 3 data.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.999

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)0.0020.000

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 head0.024
GPT teacher head0.297
Teacher spread0.273 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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