Bulk medium properties of heavy-ion collisions from the beam energy scan with a multistage hydrodynamic model
Bibliographic record
Abstract
I introduce a method to reconstruct full rapidity distributions of charged particle multiplicity and net proton yields, crucial for constraining the longitudinal dynamics of nuclear matter created in the beam energy scan program. Employing rapidity distributions within a multistage hydrodynamic model calibrated for <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mrow><a:mtext>Au</a:mtext><a:mo>+</a:mo><a:mtext>Au</a:mtext></a:mrow></a:math> collisions at <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"><b:mrow><b:msqrt><b:msub><b:mi>s</b:mi><b:mi>NN</b:mi></b:msub></b:msqrt><b:mo>=</b:mo><b:mn>7.7</b:mn><b:mo>–</b:mo><b:mn>200</b:mn><b:mspace width="4pt"/><b:mi>GeV</b:mi></b:mrow></b:math>, I estimate the total energy and baryon number deposited into the collision fireball, offering insights into initial dynamics and the identification of nuclear remnants. I explore the potential of rapidity-dependent measurements in probing equations of state at finite chemical potentials. Furthermore, I compare the freeze-out parameters derived from both hydrodynamics and thermal models, highlighting that the parameters extracted via thermal models represent averaged properties across rapidities. Published by the American Physical Society 2024
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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) | 0.000 | 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".