Determining the jet transport coefficient <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mover accent="true"><mml:mi>q</mml:mi><mml:mo></mml:mo></mml:mover></mml:math> from inclusive hadron suppression measurements using Bayesian parameter estimation
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Bibliographic record
Abstract
We report a new determination of $\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{q}$, the jet transport coefficient of the quark-gluon plasma. We use the JETSCAPE framework, which incorporates a novel multistage theoretical approach to in-medium jet evolution and Bayesian inference for parameter extraction. The calculations, based on the Matter and Lbt jet quenching models, are compared to experimental measurements of inclusive hadron suppression in $\mathrm{Au}+\mathrm{Au}$ collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and $\mathrm{Pb}+\mathrm{Pb}$ collisions at the CERN Large Hadron Collider (LHC). The correlation of experimental systematic uncertainties is accounted for in the parameter extraction. The functional dependence of $\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{q}$ on jet energy or virtuality and medium temperature is based on a perturbative picture of in-medium scattering, with components reflecting the different regimes of applicability of Matter and Lbt. In the multistage approach, the switch between Matter and Lbt is governed by a virtuality scale ${Q}_{0}$. Comparison of the posterior model predictions to the RHIC and LHC hadron suppression data shows reasonable agreement, with moderate tension in limited regions of phase space. The distribution of $\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{q}/{T}^{3}$ extracted from the posterior distributions exhibits weak dependence on jet momentum and medium temperature $T$, with 90% credible region (CR) depending on the specific choice of model configuration. The choice of Matter$+$Lbt, with switching at virtuality ${Q}_{0}$, has 90% CR of $2<\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{q}/{T}^{3}<4$ for ${p}_{T,\mathrm{jet}}>40 \mathrm{GeV}/c$. The value of ${Q}_{0}$, determined here for the first time, is in the range 2.0--2.7 GeV.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it