Determination of the strong coupling constant from transverse energy$-$energy correlations in multijet events at $\sqrt{s} = 13$ TeV with the ATLAS detector
Bibliographic record
Abstract
Measurements of transverse energy$-$energy correlations and their associated azimuthal asymmetries in multijet events are presented. The analysis is performed using a data sample corresponding to 139 $\mbox{fb\(^{-1}\)}$ of proton$-$proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV, collected with the ATLAS detector at the Large Hadron Collider. The measurements are presented in bins of the scalar sum of the transverse momenta of the two leading jets and unfolded to particle level. They are then compared to next-to-next-to-leading-order perturbative QCD calculations for the first time, which feature a significant reduction in the theoretical uncertainties estimated using variations of the renormalisation and factorisation scales. The agreement between data and theory is good, thus providing a precision test of QCD at large momentum transfers $Q$. The strong coupling constant $α_s$ is extracted differentially as a function of $Q$, showing a good agreement with the renormalisation group equation and with previous analyses. A simultaneous fit to all transverse energy$-$energy correlation distributions across different kinematic regions yields a value of $α_\mathrm{s}(m_Z) = 0.1175 \pm 0.0006 \mbox{ (exp.)} ^{+0.0034}_{-0.0017} \mbox{ (theo.)}$, while the global fit to the asymmetry distributions yields $α_{\mathrm{s}}(m_Z) = 0.1185 \pm 0.0009 \mbox{ (exp.)} ^{+0.0025}_{-0.0012} \mbox{ (theo.)}$.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".