Measurement of ZZ production in pp collisions at $ \sqrt{s}=7 $ TeV and limits on anomalous ZZZ and ZZγ couplings with the ATLAS detector
Bibliographic record
Abstract
Abstract A measurement of theZZproduction cross section in proton-proton collisions at $ \sqrt{s}=7 $ TeV using data recorded by the ATLAS experiment at the Large Hadron Collider is presented. In a data sample corresponding to an integrated luminosity of 4.6 fb−1collected in 2011, events are selected that are consistent either with twoZbosons decaying to electrons or muons or with oneZboson decaying to electrons or muons and a secondZboson decaying to neutrinos. TheZZ(*)→ℓ+ℓ−ℓ′+ℓ′−and $ ZZ\to {\ell^{+}}{\ell^{-}}\nu \overline{\nu} $ cross sections are measured in restricted phase-space regions. These results are then used to derive the total cross section forZZevents produced with bothZbosons in the mass range 66 to 116 GeV, $ \sigma_{ZZ}^{\mathrm{tot}} = 6.7 \pm 0.7\;\,\left( {\mathrm{stat}.} \right)\;\;_{-0.3}^{+0.4}\;\,\left( {\mathrm{syst}.} \right) \pm 0.3\;\,\left( {\mathrm{lumi}.} \right) $ pb, which is consistent with the Standard Model prediction of $ 5.89_{-0.18}^{+0.22 } $ pb calculated at next-to-leading order in QCD. The normalized differential cross sections in bins of various kinematic variables are presented. Finally, the differential event yield as a function of the transverse momentum of the leadingZboson is used to set limits on anomalous neutral triple gauge boson couplings inZZproduction.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".