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Holographic Photon Production and Anisotropic Flow

2017· article· en· W2595420238 on OpenAlexafffund
Ioannis Iatrakis, Elias Kiritsis, Chun Shen, Di-Lun Yang

Bibliographic record

VenueNuclear and Particle Physics Proceedings · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicBlack Holes and Theoretical Physics
Canadian institutionsMcGill University
FundersFP7 Research Potential of Convergence RegionsEuropean Research CouncilOffice of ScienceNederlandse Organisatie voor Wetenschappelijk OnderzoekMinisterie van Onderwijs, Cultuur en WetenschapRIKENNatural Sciences and Engineering Research Council of CanadaEuropean CommissionSeventh Framework ProgrammeU.S. Department of Energy
KeywordsPhysicsQuark–gluon plasmaPhotonLarge Hadron ColliderQuantum chromodynamicsParticle physicsAnisotropyHolographyHadronPlasmaGluonNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

The thermal-photon emission from strongly coupled gauge theories at finite temperature via the bottom-up models in holographic QCD in the deconfined phase is studied. The models are constructed to approximately reproduce the electric conductivity obtained from lattice simulations for the quark gluon plasma (QGP). The emission rates are then embedded in hydrodynamic simulations combined with prompt photons and hadronic contributions to analyze the spectra and anisotropic flow of direct photons in RHIC and LHC. In general, the holographic models enhance the yield and improve the agreement in spectra, while they reduce the flow in low p T and increase it in high p T .

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2017
Admission routes2
Has abstractyes

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