Exploring QCD matter in extreme conditions with Machine Learning-Reference-Cited by-同舟云学术

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Exploring QCD matter in extreme conditions with Machine Learning

Published:2024-02 Issue: Volume:135 Page:104084
ISSN:0146-6410
Container-title:Progress in Particle and Nuclear Physics
language:en
Short-container-title:Progress in Particle and Nuclear Physics

Author:

Zhou Kai^ORCID,Wang Lingxiao^ORCID,Pang Long-Gang,Shi Shuzhe

Publisher

Elsevier BV

Subject

Nuclear and High Energy Physics

Reference694 articles.

1. Quark-Gluon Plasma: From Big Bang to Little Bang, Vol. 23;Yagi,2005

2. The Little-Bang and the femto-nova in nucleus-nucleus collisions

3. The QCD Vacuum, Hadrons and the Superdense Matter, Vol. 71;Shuryak,2004

Cited by 22 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. Building imaginary-time thermal field theory with artificial neural networks*;Chinese Physics C;2024-10-01

2. Multi-dimensional hadron structure through the lens of gluon Wigner distribution;Physics Reports;2024-09

3. Neural simulation-based inference of the neutron star equation of state directly from telescope spectra;Journal of Cosmology and Astroparticle Physics;2024-09-01

4. Machine learning study to identify collective flow in small and large colliding systems;Physical Review C;2024-08-28

5. Thermodynamic properties of a relativistic Bose gas under rigid rotation;Physical Review D;2024-08-26

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