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Record W1496510216 · doi:10.1103/physrevc.79.034906

Single photons from relativistic collisions of lead nuclei at energies available at the CERN Super Proton Synchrotron (SPS): A reanalysis

2009· article· en· W1496510216 on OpenAlexaff
Rupa Chatterjee, Dinesh Kumar Srivastava, Sangyong Jeon

Bibliographic record

VenuePhysical Review C · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhysicsSuper Proton SynchrotronLarge Hadron ColliderPhotonNuclear physicsHadronFactorizationQuark–gluon plasmaYield (engineering)Elliptic flowQuarkParticle physicsQuantum mechanics

Abstract

fetched live from OpenAlex

We present a reanalysis of single photon production from a relativistic collision of lead nuclei at CERN SPS measured by the WA98 experiment. The refinements include use of isospin and shadowing corrected NLO pQCD treatment for prompt photon production using an optimized scale for factorization, renormalization, and fragmentation and use of hydrodynamics suited for noncentral collisions along with a well tested equation of state admitting a quark-hadron phase transition. A quantitative explanation of the data requires a large initial temperature (at a small formation time of about 0.2 fm/$c$) and a moderate increase in the prompt yield which could perhaps be attributed to the Cronin effect in nuclei. The data can also be explained using a moderate initial temperature (at a formation time of about 1 fm/$c$) with a very large $K$-factor multiplying the prompt yield. We show that different initial times give rise to different values for the elliptic flow parameter ${v}_{2}$ for thermal photons. We also argue that a measurement of ${v}_{2}$ for thermal photons could also distinguish between the scenarios with or without a phase transition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.027
GPT teacher head0.308
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2009
Admission routes1
Has abstractyes

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