Under-saturation of quarks at early stages of relativistic nuclear collisions: The hot glue initial scenario and its observable signatures-Reference-Cited by-同舟云学术

Under-saturation of quarks at early stages of relativistic nuclear collisions: The hot glue initial scenario and its observable signatures

Published:2015-11 Issue:8-9 Volume:336 Page:744-748
ISSN:0004-6337
Container-title:Astronomische Nachrichten
language:en
Short-container-title:Astron. Nachr.

Author:

Stöcker H.,Beitel M.,Biró T. S.,Csernai L. P.,Gallmeister K.,Gorenstein M. I.,Greiner C.,Mishustin I. N.,Panero M.,Raha S.,Satarov L. M.,Schramm S.,Senzel F.,Sinha B.,Steinheimer J.,Struckmeier J.,Vovchenko V.,Xu Z.,Zhou K.,Zhuang P.

Funder

LOEWE Initiative HIC for FAIR of the state of Hesse

Helmholtz Graduate School HIRE for FAIR

Frankfurt international graduate school for science, FIGSS at FIAS

Karin and Carlo Giersch Foundation, Frankfurt

HGF

BMBF

Publisher

Wiley

Subject

Space and Planetary Science,Astronomy and Astrophysics

Reference40 articles.

1. Centrality dependence of the pseudorapidity density distribution for charged particles in Pb–Pb collisions at sNN=2.76 TeV

2. Successive Equilibration in Quark-Gluon Plasma

3. Thermalization of hadrons via Hagedorn states

4. Parton equilibration in relativistic heavy ion collisions

5. Highly relativistic nucleus-nucleus collisions: The central rapidity region

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transverse momentum distributions of the identified particles in mini–bias non-single diffracted p＋p collisions at 200 GeV;Chinese Journal of Physics;2024-02

2. Exploring QCD matter in extreme conditions with Machine Learning;Progress in Particle and Nuclear Physics;2024-02

3. Probing the gluon plasma with charm balance functions;The European Physical Journal C;2021-11

4. PANDA as midrapidity detector for a future HESR Collider at FAIR;The European Physical Journal A;2020-06

5. Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning;The European Physical Journal C;2020-06