Measurement of the distributions of event-by-event flow harmonics in lead-lead collisions at √sNN = 2.76 TeV with the ATLAS detector at the LHC
Bibliographic record
Abstract
The distributions of event-by-event harmonic flow coefficients v n for n = 2- 4 are measured in sNN−−−−√ = 2.76 TeV Pb + Pb collisions using the ATLAS detector at the LHC. The measurements are performed using charged particles with transverse momentum p T > 0.5 GeV and in the pseudorapidity range |η| < 2.5 in a dataset of approximately 7 μb−1 recorded in 2010. The shapes of the v n distributions suggest that the associated flow vectors are described by a two-dimensional Gaussian function in central collisions for v 2 and over most of the measured centrality range for v 3 and v 4. Significant deviations from this function are observed for v 2 in mid-central and peripheral collisions, and a small deviation is observed for v 3 in mid-central collisions. In order to be sensitive to these deviations, it is shown that the commonly used multi-particle cumulants, involving four particles or more, need to be measured with a precision better than a few percent. The v n distributions are also measured independently for charged particles with 0.5 < p T < 1 GeV and p T > 1 GeV. When these distributions are rescaled to the same mean values, the adjusted shapes are found to be nearly the same for these two p T ranges. The v n distributions are compared with the eccentricity distributions from two models for the initial collision geometry: a Glauber model and a model that includes corrections to the initial geometry due to gluon saturation effects. Both models fail to describe the experimental data consistently over most of the measured centrality range.
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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) | 0.000 | 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 | 0.001 | 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 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".