Jet Suppression and Azimuthal Anisotropy from RHIC to LHC
Bibliographic record
Abstract
Azimuthal anisotropies of high-$p_T$ particles produced in heavy-ion collisions are understood as an effect of a geometrical selection bias. Particles oriented in the direction in which the QCD medium formed in these collisions is shorter, suffer less energy loss, and thus, are over-represented in the final ensemble compared to those oriented in the direction in which the medium is longer. In this work we present the first semi-analytical predictions, including propagation through a realistic, hydrodynamical background, of the azimuthal anisotropies for jets, obtaining a quantitative agreement with available experimental data as function of the jet $p_T$, its cone size $R$ and the collisions centrality. Jets are multi-partonic, extended objects and their energy loss is sensitive to substructure fluctuations. This is determined by the physics of color coherence that relates to the ability of the medium to resolve those partonic fluctuations. Namely, color dipoles whose angle is smaller than a critical angle, $θ_c$, are not resolved by the medium and they effectively act as a coherent source of energy loss. We find that jet azimuthal anisotropies have a specially strong dependence on coherence physics due to the marked length-dependence of $θ_c$. By combining our predictions for the collision systems and center of mass energies studied at RHIC and the LHC, covering a wide range of typical values of $θ_c$, we show that the relative size of jet azimuthal anisotropies for jets with different cone-sizes $R$ follow a universal trend that indicates a transition from a coherent regime of jet quenching to a decoherent regime. These results suggest a way forward to reveal the role played by the physics of jet color decoherence in probing deconfined QCD matter.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".