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Record W4401108604 · doi:10.1103/physrevd.110.014046

QCD bounds on leading-order hadronic vacuum polarization contributions to the muon anomalous magnetic moment

2024· article· en· W4401108604 on OpenAlexafffund
Siyuan Li, T. G. Steele, J. Ho, Reehana Raza, Karina Williams, R. T. Kleiv

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsThompson Rivers UniversityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnomalous magnetic dipole momentMuonVacuum polarizationPhysicsHadronParticle physicsQuantum chromodynamicsPolarization (electrochemistry)Moment (physics)Nuclear physicsMagnetic momentOrder (exchange)Electron magnetic dipole momentQuantum electrodynamicsCondensed matter physicsMagnetic fieldMagnetic dipoleQuantum mechanicsChemistry

Abstract

fetched live from OpenAlex

QCD bounds on the leading-order (LO) hadronic vacuum polarization (HVP) contribution to the anomalous magnetic moment of the muon [ a μ HVP , LO , a μ = ( g − 2 ) μ / 2 ] are determined by imposing Hölder inequalities and related inequality constraints on systems of finite-energy QCD sum rules. This novel methodology is complementary to lattice QCD and data-driven approaches to determining a μ HVP , LO . For the light-quark ( u , d , s ) contributions up to five-loop order in perturbation theory in the chiral limit, LO in light-quark mass corrections, next-to-leading order in dimension-four QCD condensates, and to LO in dimension-six QCD condensates, we find that ( 657.0 ± 34.8 ) × 10 − 10 ≤ a μ HVP , LO ≤ ( 788.4 ± 41.8 ) × 10 − 10 , bridging the range between lattice QCD and data-driven values. Published by the American Physical Society 2024

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)0.003
metaresearch head score (Gemma)0.011
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0120.002

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 head0.010
GPT teacher head0.406
Teacher spread0.396 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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