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Record W2951645291 · doi:10.48550/arxiv.1612.06754

Rapidity-dependent jet energy loss in small systems with finite-size effects and running coupling

2016· preprint· en· W2951645291 on OpenAlexafffund
Chanwook Park, Chun Shen, Sangyong Jeon, Charles Gale

Bibliographic record

VenuearXiv (Cornell University) · 2016
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaOffice of ScienceU.S. Department of EnergyMcGill UniversityKillam TrustsCanada Council for the ArtsCompute Canada
KeywordsJet quenchingRapidityPhysicsElliptic flowMultiplicity (mathematics)Jet (fluid)Nuclear physicsThermalEnergy flowCoupling lossCoupling (piping)Energy (signal processing)Particle physicsMechanicsQuark–gluon plasmaHadronHeavy ionThermodynamicsMaterials science

Abstract

fetched live from OpenAlex

Longitudinal dynamics of particle production and rapidity-dependent jet energy loss are investigated in small and asymmetric colliding systems. We utilize an improved version of \textsc{martini} in which two improvements are implemented to calculate the effect of the strongly coupled QGP droplet on jet energy loss. We show that those realistic prescriptions improve the results of nuclear modification factor calculations. We also observe visible energy loss of jets in a thermal background of high-multiplicity p-Pb collisions, and a clear correlation between the energy loss and elliptic flow coefficients for energetic particles. We conclude that systematic measurements of jet quenching in central collisions of small systems can support the formation of the QGP droplet.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0000.001
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 head0.036
GPT teacher head0.194
Teacher spread0.158 · 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.

Study designSimulation or modeling
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

Citations2
Published2016
Admission routes2
Has abstractyes

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