Pseudorapidity density, transverse momentum spectra, and elliptic flow studies in Xe-Xe collision systems at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msqrt><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:mi>N</mml:mi><mml:mi>N</mml:mi></mml:mrow></mml:msub></mml:msqrt><mml:mo>=</mml:mo><mml:mn>5.44</mml:mn><mml:mspace width="0.28em"/><mml:mi>TeV</mml:mi></mml:mrow></mml:math> using the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi mathvariant="normal">HYDJET</mml:mi><mml:mo>+</mml:mo><mml:mo>+</mml:mo></mml:mrow></mml:math> model
Bibliographic record
Abstract
In this paper, we present a systematic study of Xe-Xe collisions at 5.44-TeV center-of-mass energy. We employ the Monte Carlo (hydrodynamics plus jets) $\mathrm{HYDJET}++$ model to calculate the pseudorapidity distribution, transverse momentum $({p}_{T})$ spectra and the elliptic flow $({v}_{2})$ of charged hadrons with different parameters in two geometrical configurations: body-body and tip-tip type of Xe-Xe collisions. The kinematic ranges $0<{p}_{T}<50\phantom{\rule{0.28em}{0ex}}\mathrm{GeV}/c$ and $|\ensuremath{\eta}|<0.8$ are considered for our paper. Results are obtained for seven classes of centrality. For comparison, we have shown results from the AMPT model with the string-melting version. The results obtained for Xe-Xe collision systems for minimum bias at midrapidity match well with the experimental data of the ALICE/CMS Collaborations. We observe that the pseudorapidity density depends on the size and geometry of the colliding system. The centrality dependence of average transverse momentum ($\ensuremath{\langle}{p}_{T}\ensuremath{\rangle}$) and average elliptic flow ($\ensuremath{\langle}{v}_{2}\ensuremath{\rangle}$) is also observed. The charged hadron properties also show clear dependence on the geometrical configuration of the collisions. Our model results have been compared to results obtained in the AMPT model. The $\mathrm{HYDJET}++$ model justifies data more closely than the AMPT model, the latter mostly overpredicts the experimental data.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".