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Record W2076450724 · doi:10.1103/physrevc.76.014908

Three-particle azimuthal correlations and Mach shocks

2007· article· en· W2076450724 on OpenAlex
Thorsten Renk, Jörg Ruppert

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

VenuePhysical Review C · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhysicsHadronMach numberParticle (ecology)PartonAzimuthMonte Carlo methodNuclear physicsHeavy ionQuantum mechanicsMechanicsIonOptics

Abstract

fetched live from OpenAlex

Measurements of angular correlations of hadrons with a (semi)hard trigger hadron in heavy-ion collisions at RHIC show large angular structures opposite to the trigger which were a priori unexpected. These away side large angle correlations were first observed in two-particle correlations [S. S. Adler et al. (PHENIX Collaboration), Phys. Rev. Lett. 97, 052301 (2006) and J. Adams et al. (STAR Collaboration), Phys. Rev. Lett. 95, 152301 (2005)] and have recently also been investigated in three-particle correlation measurements [J. G. Ulery (STAR Collaboration), Nucl. Phys. A774, 581 (2006) and F. Wang, arXiv:nucl-ex/0610027]. We show that the correlation signal can be understood in terms of sonic shockwaves (`Mach cones') excited by hard partons supersonically traversing the medium. The propagation of such shocks through the medium evolution is treated in a Monte Carlo (MC) framework [T. Renk and J. Ruppert, Phys. Rev. C 73, 011901(R) (2006) and Phys. Lett. B646, 19 (2007)]. We demonstrate that two- and especially three-particle correlations offer nontrivial insight into the medium-averaged speed of sound and the evolution of flow. Our findings imply that the assumption of ``deflected jets'' is not necessary to account for the observed correlations.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.517

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 head0.027
GPT teacher head0.359
Teacher spread0.332 · 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