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Record W3163165881 · doi:10.1088/1674-1137/ac2a1f

Investigation of experimental observables in search of the chiral magnetic effect in heavy-ion collisions in the STAR experiment *

2021· preprint· en· W3163165881 on OpenAlexafffund
S. Choudhury, J. C. Dunlop, ShinIchi Esumi, Y. Feng, E. Finch, Y. Hu, J. Jia, Jérôme Lauret, W. Li, Jinfeng Liao, Mike Lisa, T. Niida, Robert Ray, Masha Sergeeva, D. Y. Shen, Shuzhe Shi, P. Sørensen, Aihong Tang, Prithwish Tribedy, Gene Van Buren, Sergei A Voloshin, Fuqiang Wang, Gang Wang, H. Xu, Zhiwan Xu, N. Yao, J. Zhao

Bibliographic record

VenueChinese Physics C · 2021
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicHigh-Energy Particle Collisions Research
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaOffice of ScienceNational Natural Science Foundation of ChinaNuclear PhysicsFundamental Research Funds for the Central UniversitiesCentral China Normal UniversityChina Scholarship CouncilU.S. Department of EnergyNational Science Foundation
KeywordsPhysicsObservableLarge Hadron ColliderRelativistic Heavy Ion ColliderNuclear physicsQuark–gluon plasmaParticle physicsHadronPlasmaCascadeGluonMonte Carlo methodQuarkHeavy ionIonQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract The chiral magnetic effect (CME) is a novel transport phenomenon, arising from the interplay between quantum anomalies and strong magnetic fields in chiral systems. In high-energy nuclear collisions, the CME may survive the expansion of the quark-gluon plasma fireball and be detected in experiments. Over the past two decades, experimental searches for the CME have attracted extensive interest at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). The main goal of this study is to investigate three pertinent experimental approaches: the correlator, the R correlator, and the signed balance functions. We exploit simple Monte Carlo simulations and a realistic event generator (EBE-AVFD) to verify the equivalence of the core components among these methods and to ascertain their sensitivities to the CME signal and the background contributions for the isobar collisions at the RHIC.

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)0.001
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 score0.411
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.031
GPT teacher head0.316
Teacher spread0.285 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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