Measurement of the azimuthal anisotropy for charged particle production in âS<inf>NN</inf> = 2.76 TeV lead-lead collisions with the ATLAS detector
Bibliographic record
Abstract
© 2012 CERN, for the ATLAS Collaboration. Differential measurements of charged particle azimuthal anisotropy are presented for lead-lead collisions at √sNN = 2.76 TeV with the ATLAS detector at the LHC, based on an integrated luminosity of approximately 8 μb− 1. This anisotropy is characterized via a Fourier expansion of the distribution of charged particles in azimuthal angle relative to the reaction plane, with the coefficients vn denoting the magnitude of the anisotropy. Significant v2–v6 values are obtained as a function of transverse momentum (0.5 < pT < 20 GeV), pseudorapidity (|η| < 2.5), and centrality using an event plane method. The vn values for n ≥ 3 are found to vary weakly with both η and centrality, and their pT dependencies are found to follow an approximate scaling relation, v1/nn (pT) ∝ v1/22 (pT), except in the top 5% most central collisions. A Fourier analysis of the charged particle pair distribution in relative azimuthal angle (Δϕ = ϕa − ϕb) is performed to extract the coefficients vn, n = (cos nΔϕ). For pairs of charged particles with a large pseudorapidity gap (|Δη = ηa − ηb| > 2) and one particle with pT < 3 GeV, the v2,2–v6,6 values are found to factorize as vn, n(paT, pbT) ≈ vn(paT)vn(pbT) in central and midcentral events. Such factorization suggests that these values of v2,2–v6,6 are primarily attributable to the response of the created matter to the fluctuations in the geometry of the initial state. A detailed study shows that the v1,1(paT, pbT) data are consistent with the combined contributions from a rapidity-even v1 and global momentum conservation.A two-component fit is used to extract the v1 contribution. The extracted v1 isobserved to cross zero at pT ≈ 1.0 GeV, reaches a maximum at 4–5 GeV with a value comparable to that for v3, and decreases at higher pT.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".