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Record W4224215410 · doi:10.1007/jhep04(2022)129

Systematically testing singlet models for (g − 2)μ

2022· article· en· W4224215410 on OpenAlexafffund
Rodolfo Capdevilla, David Curtin, Yonatan Kahn, Gordan Krnjaic

Bibliographic record

VenueJournal of High Energy Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of TorontoPerimeter Institute
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Colleges and UniversitiesGovernment of CanadaInnovation, Science and Economic Development CanadaInstitut Périmètre de physique théoriqueAlfred P. Sloan FoundationHigh Energy PhysicsU.S. Department of Energy
KeywordsPhysicsMuonParticle physicsMuon colliderColliderLarge Hadron ColliderNuclear physicsStandard Model (mathematical formulation)Physics beyond the Standard ModelAnomaly (physics)UnitarityLeptonScale (ratio)Particle acceleratorElectronBeam (structure)

Abstract

fetched live from OpenAlex

Abstract We comprehensively study all viable new-physics scenarios that resolve the muon (g − 2)μ anomaly with only Standard Model singlet particles coupled to muons via renormalizable interactions. Since such models are only viable in the MeV–TeV mass range and require sizable muon couplings, they predict abundant accelerator production through the same interaction that resolves the anomaly. We find that a combination of fixed-target (NA64μ, M3), B-factory (BABAR, Belle II), and collider (LHC, muon collider) searches can cover nearly all viable singlets scenarios, independently of their decay modes. In particular, future muon collider searches offer the only certain test of singlets above the GeV scale, covering all higher masses up to the TeV-scale unitarity limit for these models. Intriguingly, we find that $$ \mathcal{O}\left(100\ \mathrm{GeV}\right) $$ O 100 GeV muon colliders may yield better coverage for GeV-scale singlets compared to TeV-scale concepts, which has important implications for the starting center-of-mass energy of a staged muon collider program.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.027
GPT teacher head0.246
Teacher spread0.219 · 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 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

Citations45
Published2022
Admission routes2
Has abstractyes

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