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Record W4414520806 · doi:10.34133/research.0941

Diffusion Wake: A Distinctive Consequence of the Mach-Cone Wake Induced by Supersonic Jets in High-Energy Heavy-Ion Collisions

2025· article· en· W4414520806 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch · 2025
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsRapiditySupersonic speedWakeAsymmetryDiffusionRidgeSIGNAL (programming language)

Abstract

fetched live from OpenAlex

In this Research Perspective, we briefly review the diffusion wake, a distinctive consequence of the Mach-cone wake induced by the supersonic jets in ultrarelativistic heavy-ion collisions. The diffusion wake depletes soft hadrons in the direction opposite to the propagating jet. According to coupled transport and hydrodynamic simulations, a valley in the 2-dimensional jet–hadron correlation in azimuthal angle and rapidity arises on the top of the multiple-parton interaction ridge as an unambiguous signal of the diffusion wake induced by <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mi>γ</mml:mi> </mml:math> -jets in heavy-ion collisions. In dijet events with a finite rapidity gap, the rapidity asymmetry of the jet–hadron correlation has been shown to be a robust signal of the diffusion wake. The same rapidity asymmetry can also be applied to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mi>γ</mml:mi> </mml:math> -jet events, and both are background-free. Experimental measurements of these signals can provide valuable insights into the properties of the quark–gluon plasma formed in high-energy heavy-ion collisions.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.442

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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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