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Record W2526502097 · doi:10.1142/s0217732316300378

Strong coupling constant from Adler function in lattice QCD

2016· article· en· W2526502097 on OpenAlexafffund
Renwick J. Hudspith, Randy Lewis, Kim Maltman, Eigo Shintani

Bibliographic record

VenueModern Physics Letters A · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsYork University
FundersRIKENScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsLattice QCDLattice field theoryLattice (music)Particle physicsCoupling constantLattice constantQuantum chromodynamicsMathematical physicsLattice model (finance)Quantum mechanics

Abstract

fetched live from OpenAlex

We compute the QCD coupling constant, [Formula: see text], from the Adler function with vector hadronic vacuum polarization (HVP) function. On the lattice, Adler function can be measured by the differential of HVP at two different momentum scales. HVP is measured from the conserved-local vector current correlator using nf = 2 + 1 flavor Domain Wall lattice data with three different lattice cutoffs, up to a[Formula: see text] 3.14 GeV. To avoid the lattice artifact due to O(4) symmetry breaking, we set the cylinder cut on the lattice momentum with reflection projection onto vector current correlator, and it then provides smooth function of momentum scale for extracted HVP. We present a global fit of the lattice data at a justified momentum scale with three lattice cutoffs using continuum perturbation theory at [Formula: see text] to obtain the coupling in the continuum limit at arbitrary scale. We take the running to Z boson mass through the appropriate thresholds, and obtain [Formula: see text](MZ) = 0.1191(24)(37) where the first is statistical error and the second is systematic one.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.236
Teacher spread0.220 · 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 designSimulation or modeling
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
Published2016
Admission routes2
Has abstractyes

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