Precise Determination of the Strong Coupling Constant from Dijet Cross Sections up to the Multi-TeV Range
Bibliographic record
Abstract
We determine the value of the strong coupling α_{s} and study its running over a wide range of scales as probed by the dijet production process at hadron colliders, based on a next-to-next-to-leading-order QCD analysis of LHC dijet data. From a large subset of these data a value of α_{s}(m_{Z})=0.1178±0.0022 is obtained for the strong coupling at the scale of the Z-boson mass m_{Z}, using the invariant mass of the dijet system to select the scale where α_{s} is probed. The combination of different datasets enhances the reach and precision of the analysis in the multi-TeV range and allows for the first determination of α_{s} up to scales of 7 TeV. Complementing the LHC data with dijet cross sections measured at the HERA electron-proton collider, the kinematic range is extended to test the running of the strong coupling toward smaller scales. Our results exhibit excellent agreement with predictions based on the renormalization group equation of QCD, and represent a comprehensive test of the asymptotic behavior of QCD, spanning more than three orders of magnitude in energy scale.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".