您当前的位置：
首页 >
文章列表页 >
Application of machine learning to the study of QCD transition in heavy ion collisions
Special Issue for QCD Phase Diagram and Critical Point | 更新时间：2024-10-25
|

    • Application of machine learning to the study of QCD transition in heavy ion collisions

      增强出版
    • “In the field of high-energy heavy ion collisions, scientists use machine learning to study the equation of state of nuclear matter, phase transition classification, and critical point search, providing new ideas for solving symbolic problems.”
    • NUCLEAR TECHNIQUES   Vol. 46, Issue 4, Article number: 040014(2023)

    • DOI：10.11889/j.0253-3219.2023.hjs.46.040014    

      CLC： TL99;O571.6;O572.2

    • Received：06 March 2023，

      Revised：03 April 2023，

      Published：15 April 2023

    移动端阅览

  • LI Fupeng,PANG Longgang,WANG Xinnian.Application of machine learning to the study of QCD transition in heavy ion collisions[J].NUCLEAR TECHNIQUES,2023,46(04):040014-040014. DOI： 10.11889/j.0253-3219.2023.hjs.46.040014.

  •  
  •  

0

Views

145

下载量

2

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

SSA-XGBoost model based high-precision density prediction method for well logging
Neutron/gamma (n/γ) discrimination method based on KPCA-MPA-ELM
Studies on several problems in nuclear physics by using machine learning
QCD phase transitions using the QCD Dyson-Schwinger equation approach
Transport model study of conserved charge fluctuations and QCD phase transition in heavy-ion collisions

Related Author

WU Wensheng
LI Rui
LI Hulin
TUO Xianguo
ZHANG Yunlong
ZHANG Guiyu
HU Wanping
LI Qingfeng

Related Institution

College of Geophysics, China University of Petroleum
Chengdu Huilite Automation Technology Co., Ltd.
School of Information Engineering, Southwest University of Science and Technology
Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering
School of Automation & Information Engineering, Sichuan University of Science & Engineering
0