Measurement of jet fragmentation in Pb+Pb and $pp$ collisions at $\sqrt{s_{NN}} = 5.02$ TeV with the ATLAS detector
Bibliographic record
Abstract
CERN-LHC. This paper presents a measurement of jet fragmentation functions in 0.49 nb−1 of Pb+Pb collisions and 25 pb−1 of pp collisions at sNN=5.02 TeV collected in 2015 with the ATLAS detector at the LHC. These measurements provide insight into the jet quenching process in the quark-gluon plasma created in the aftermath of ultrarelativistic collisions between two nuclei. The modifications to the jet fragmentation functions are quantified by dividing the measurements in Pb+Pb collisions by baseline measurements in pp collisions. This ratio is studied as a function of the transverse momentum of the jet, the jet rapidity, and the centrality of the collision. In both collision systems, the jet fragmentation functions are measured for jets with transverse momentum between 126 and 398 GeV and with an absolute value of jet rapidity less than 2.1. An enhancement of particles carrying a small fraction of the jet momentum is observed, which increases with centrality and with increasing jet transverse momentum. Yields of particles carrying a very large fraction of the jet momentum are also observed to be enhanced. Between these two enhancements of the fragmentation functions a suppression of particles carrying an intermediate fraction of the jet momentum is observed in Pb+Pb collisions. A small dependence of the modifications on jet rapidity is observed.
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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) | 0.001 | 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".