Comparative studies of jet quenching in relativistic heavy ion collisions
Bibliographic record
Abstract
Heavy ion collisions (HIC) performed at major experimental facilities such as the Large Hadron Collider (LHC, Switzerland) or the Relativistic Heavy Ion Collider (RHIC, USA) produce a novel state of matter known as the Quark-Gluon Plasma (QGP). An important signal of the creation of the QGP is the observation of jet energy loss or jet quenching in these collisions. This thesis studies jet energy loss via two parallel and independent comparative analyses. The first study uses MARTINI in the first, single-stage energy loss simulation to analyze the effect of changing the collision kernel which encodes information about the interactions of the jet with the QGP medium and is a crucial ingredient of energy loss rates. Recent efforts have resulted in this kernel's next-to-leading order (NLO) and non-perturbative (NP) evaluations. New inelastic rates are generated with the higher-order kernels and used in MARTINI simulations of energy loss. The simulations are then compared against those using the leading-order (LO) kernel. Systematic differences are shown between the three rate-sets, which can be absorbed into a re-scaled strong coupling constant within a single-stage energy loss model. Simulation results also demonstrate the need to go beyond a single-stage simulation and the physical necessity of a delayed parton shower or a multi-stage simulation.The second study concerns the first comparative analysis of two important models of jet-medium interactions, MARTINI and CUJET, which employ the AMY-McGill and the DGLV energy loss frameworks, respectively. Two multi-stage models are constructed using JETSCAPE, incorporating MARTINI and CUJET as components in their workflow. The models are then applied to multiple HIC systems to calculate nuclear modification factors of charged hadrons, jets and jet substructure observables such as jet fragmentation function ratio. The simulations also contain photons via jet-medium interactions for the first time. We show systematic differences between the models in jet and jet-medium photon observables. The relation of the observed differences to the inelastic rates of the models is shown and points of improvement are discussed
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".