DYTurbo: Fast predictions for Drell–Yan processes
Why this work is in the frame
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Bibliographic record
Abstract
Drell–Yan lepton pair production processesare extremely important for Standard Model (SM) pre-cision tests and for beyond the SM searches at hadroncolliders. Fast and accurate predictions are essential toenable the best use of the precision measurements ofthese processes; they are used for parton density fits, forthe extraction of fundamental parameters of the SM, andfor the estimation of background processes in searches.This paper describes a new numerical program,DYTurbo,for the calculation of the QCD transverse-momentumresummation of Drell–Yan cross sections up to next-to-next-to-leading logarithmic accuracy combined withthe fixed-order results at next-to-next-to-leading order(O(α2S)), including the full kinematical dependence ofthe decaying lepton pair with the corresponding spincorrelations and the finite-width effects. TheDYTurboprogram is an improved reimplementation of theDYqT,DYResandDYNNLOprograms, which provides fast andnumerically precise predictions through the factorisationof the cross section into production and decay variables,and the usage of quadrature rules based on interpolatingfunctions for the integration over kinematic variables.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it