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Record W4415908454 · doi:10.1051/epjconf/202533908002

Direct virtual photon production in Au+Au collision at 27 and 54.4 GeV

2025· article· en· W4415908454 on OpenAlexaff

Bibliographic record

VenueEPJ Web of Conferences · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsPhotonHadronVirtual particleRadiationTransverse planeQuantum chromodynamicsThermalBremsstrahlung

Abstract

fetched live from OpenAlex

As electromagnetic probes, photons have the advantage of escaping unimpeded from their emission source, allowing them to carry valuable information about the properties and dynamics of the hot quantum chromodynamics (QCD) medium created in heavy-ion collisions. Particularly, the transverse momentum distribution of direct virtual photons emitted from the hot QCD medium exhibits sensitivity to the system temperature. Direction photons from thermal radiation in the low transverse momentum region are expected to be a quark-gluon plasma (QGP) thermometer. However, the photon from hadronic decays make the extraction of the thermal radiation contribution very challenging. The STAR experiment has recorded large datasets of Au+Au collisions in the Beam Energy Scan Phase-II (BES-II) program, spanning center-of-mass energies of √ s NN = 3 - 54.4 GeV. In these proceedings, we present the latest direct virtual photon measurement in Au+Au collisions at √ s NN = 27 and 54.4 GeV, including p T differential invariant yields and total yields in different centrality bin. The total yields increase rapidly with increasing dN ch / d η. Notably, it scales with ( dN ch / d η) α , where α = 1.46 ± 0.07.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.016
GPT teacher head0.290
Teacher spread0.274 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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