Rapidity gap cross sections measured with the ATLAS detector in pp collisions at $\sqrt{s} = 7 \mbox{~TeV}$
Bibliographic record
Abstract
Pseudorapidity gap distributions in proton-proton collisions at $\sqrt {s} =7~\mbox{~TeV}$ are studied using a minimum bias data sample with an integrated luminosity of 7.1 μb−1. Cross sections are measured differentially in terms of Δη F , the larger of the pseudorapidity regions extending to the limits of the ATLAS sensitivity, at η=±4.9, in which no final state particles are produced above a transverse momentum threshold $p_{\mathrm{T}}^{\mathrm{cut}}$ . The measurements span the region 0<Δη F <8 for $200 \mbox{~MeV}< p_{\mathrm{T}}^{\mathrm {cut}} < 800 \mbox{~MeV}$ . At small Δη F , the data test the reliability of hadronisation models in describing rapidity and transverse momentum fluctuations in final state particle production. The measurements at larger gap sizes are dominated by contributions from the single diffractive dissociation process (pp→Xp), enhanced by double dissociation (pp→XY) where the invariant mass of the lighter of the two dissociation systems satisfies M Y ≲7 GeV. The resulting cross section is dσ/dΔη F ≈1 mb for Δη F ≳3. The large rapidity gap data are used to constrain the value of the Pomeron intercept appropriate to triple Regge models of soft diffraction. The cross section integrated over all gap sizes is compared with other LHC inelastic cross section measurements.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".