Precise measurement of the $t\bar{t}$ production cross-section and lepton differential distributions in $eμ$ dilepton events from $\sqrt{s}=13$ TeV $pp$ collisions with the ATLAS detector
Bibliographic record
Abstract
The inclusive top quark pair ($t\bar{t}$) cross-section $\sigma _{t\bar{t}}$ has been measured in proton–proton collisions at $\sqrt{s}=13\,\text {TeV}$, using $140\,{\text {fb}^{-1}} $ of data collected by the ATLAS experiment at the Large Hadron Collider. Using events with an opposite-charge $e\mu $ pair and b-tagged jets, the cross-section is measured to be: $\begin{aligned} \sigma _{t\bar{t}} & = 829.3\pm 1.3\,\mathrm {(stat)}\ \pm 8.0\,\mathrm {(syst)}\ \pm 7.3\,\mathrm {(lumi)}\ \\ & \quad \pm 1.9\,\mathrm {(beam)}\,\textrm{pb}, \end{aligned}$where the uncertainties reflect the limited size of the data sample, experimental and theoretical systematic effects, the integrated luminosity, and the proton beam energy, giving a total uncertainty of 1.3%. The result is used to determine the top quark pole mass via the dependence of the predicted cross-section on ${m_{t}^\textrm{pole}}$, giving ${m_{t}^\textrm{pole}}=172.8^{+1.5}_{-1.7}$ $\text {GeV}$. The same event sample is used to measure absolute and normalised differential cross-sections for the $t\bar{t} \rightarrow e\mu \nu \bar{\nu }b\bar{b} $ process as a function of single-lepton and dilepton kinematic variables. Complementary measurements of $e\mu b\bar{b} $ production, treating both $t\bar{t}$ and Wt events as signal, are also provided. Both sets of differential cross-sections are compared to the predictions of various Monte Carlo event generators, demonstrating that the state-of-the-art generators Powheg MiNNLO and Powhegbb4l describe the data better than Powheghvq.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".