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Record W4410092143 · doi:10.1103/physrevc.111.054904

QCD jets in a hot and dense medium: A study of shower formation time and collision kernels

2025· article· en· W4410092143 on OpenAlexafffund
Rouzbeh Modarresi Yazdi, Shuzhe Shi, Charles Gale, Sangyong Jeon

Bibliographic record

VenuePhysical review. C · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsMcGill University
FundersNuclear PhysicsOffice of ScienceAlliance de recherche numérique du CanadaNatural Sciences and Engineering Research Council of CanadaTsinghua UniversityU.S. Department of Energy
KeywordsShowerCollisionQuantum chromodynamicsParticle physicsPhysicsNuclear physicsComputer scienceProgramming languageThermodynamics

Abstract

fetched live from OpenAlex

With the use of , a model which considers evolving QCD jets against a fluid dynamical background, it is shown that the introduction of formation time to the parton shower after the initial hard scattering is essential for a simultaneous description of charged hadron and jet <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:msub> <a:mi>R</a:mi> <a:mrow> <a:mi>A</a:mi> <a:mi>A</a:mi> </a:mrow> </a:msub> </a:math> . This inclusion also improves jet shape ratios at small angle and jet fragmentation function ratios of leading charged hadrons. The framework is then aimed at a study of the leading-order, next-to-leading-order, and nonperturbative collision kernels. Sizable differences in the modification of jet substructure observables, i.e., jet shape and fragmentation functions, are observed. Such differences are caused by the difference in the radiation rates of relatively soft gluons that survive in the evolution in medium.

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 score0.502
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.359
Teacher spread0.343 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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