Prompt and non-prompt $J/\psi $ and $\psi (2\mathrm {S})$ suppression at high transverse momentum in $5.02~\mathrm {TeV}$ Pb+Pb collisions with the ATLAS experiment
Bibliographic record
Abstract
A measurement of J/ψ and ψ(2S) production is presented.It is based on a data sample from Pb+Pb collisions at √ s NN = 5.02 TeV and pp collisions at √ s = 5.02 TeV recorded by the ATLAS detector at the LHC in 2015, corresponding to an integrated luminosity of 0.42 nb -1 and 25 pb -1 in Pb+Pb and pp, respectively.The measurements of per-event yields, nuclear modification factors, and nonprompt fractions are performed in the dimuon decay channel for 9 < p μμ T < 40 GeV in dimuon transverse momentum, and -2 < y μμ < 2 in rapidity.Strong suppression is found in Pb+Pb collisions for both prompt and non-prompt J/ψ, increasing with event centrality.The suppression of prompt ψ(2S) is observed to be stronger than that of J/ψ, while the suppression of non-prompt ψ(2S) is equal to that of the nonprompt J/ψ within uncertainties, consistent with the expectation that both arise from b-quarks propagating through the medium.Despite prompt and non-prompt J/ψ arising from different mechanisms, the dependence of their nuclear modification factors on centrality is found to be quite similar.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".