利用输运模型和机器学习方法研究CSR能区的低温高密核物质
结题报告
批准号:
U2032145
项目类别:
联合基金项目
资助金额:
50.0 万元
负责人:
王永佳
依托单位:
学科分类:
兰州重离子加速器
结题年份:
2023
批准年份:
2020
项目状态:
已结题
项目参与者:
王永佳
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中文摘要
本项目将基于微观输运模型和机器学习方法对CSR能区(费米能量到每核子1 GeV左右)重离子碰撞中形成的低温高密核物质性质进行研究。重点关注核物质在较高重子密度和同位旋时的状态方程,以及CSR能区中的涨落现象与核物质性质的关联。利用机器(深度)学习等人工智能技术来分析CSR能区重离子碰撞中的理论模拟数据及实验数据,寻找对该能区碰撞中形成的核物质性质更敏感的探测窗口或新观测量,探索从更高维度的复杂数据空间中寻找出关键的物理信息的途径。采用贝叶斯分析方法考虑输运模型不确定参数的范围,通过对不同能量、系统、同位旋等重离子碰撞的模拟,细致分析产额、集体流、HBT关联函数等多个观测量,结合最新实验数据,约束描述低温高密核物质性质的参数(如不可压缩系数K0及其高阶项J0,以及对称能斜率参数L和曲率参数Ksym等)的可靠范围。通过对末态粒子产额高阶矩的计算,探究CSR能区中的涨落现象与核物质性质的关联。
英文摘要
In this project, the properties of the low-temperature and high-density nuclear matter produced in heavy-ion collision (HIC) at the CSR energies (from the Fermi energy up to 1 GeV per nucleon) will be investigated with transport model and machine-learning technique. We will concentrate on the nuclear equation of state at high baryon density and isospin density, as well as the correlation between the fluctuation observables and the properties of the dense nuclear matter formed at the CSR energies. By using the machine (deep) learning technique to analyze the huge amount of HIC data obtained both from transport model simulations and experiments, more sensitive windows or new observable for probing the properties of the low-temperature and high-density nuclear matter at the CSR energies are hoped to be obtained, valuable features are expected to be extracted from the high-dimensional data spaces. Observables (such as, particle multiplicity, collective flow, and HBT correlation function) from HIC with various beam energies, system, and isospin symmetry will be calculated by using transport model in which uncertainty of various parameters is considered. Based on Bayesian analyses, reliable range of parameters (such as the nuclear incompressibility K0 and its higher order J0, the slope of symmetry energy L and the curvature Ksym) that we are interested in will be extracted from the comparison of experimental data to the related transport model calculations. The cumulant for particle multiplicity distribution will be calculated as well in order to obtain the correlation between the fluctuation observables and the properties of the nuclear matter produced at the CSR energies.
期刊论文列表
专著列表
科研奖励列表
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专利列表
DOI:10.1007/s41365-023-01205-3
发表时间:2023-04
期刊:Nuclear Science and Techniques
影响因子:2.8
作者:Kui Xiao;Pengrui Li;Yong-Jia Wang;Fu-Hu Liu;Qingfeng Li
通讯作者:Kui Xiao;Pengrui Li;Yong-Jia Wang;Fu-Hu Liu;Qingfeng Li
DOI:10.1360/sspma-2020-0491
发表时间:2021
期刊:中国科学. 物理学, 力学, 天文学
影响因子:--
作者:崔特;刘玲;李鹏程;王永佳;李庆峰
通讯作者:李庆峰
DOI:10.1007/s11467-023-1313-3
发表时间:2023-05
期刊:Frontiers of Physics
影响因子:7.5
作者:Yongjia Wang;Qingfeng Li
通讯作者:Yongjia Wang;Qingfeng Li
Comparison of heavy-ion transport simulations: Mean-field dynamics in a box
重离子输运模拟的比较:盒子中的平均场动力学
DOI:10.1103/physrevc.104.024603
发表时间:2021-08-05
期刊:PHYSICAL REVIEW C
影响因子:3.1
作者:Colonna, Maria;Zhang, Ying-Xun;Zhang, Feng-Shou
通讯作者:Zhang, Feng-Shou
DOI:10.7538/yzk.2022.youxian.0827
发表时间:2023
期刊:原子能科学技术
影响因子:--
作者:魏国俊;王永佳;李庆峰;刘福虎
通讯作者:刘福虎
基于输运模型对核子有效质量劈裂、高密对称能及相关的模型依赖问题的研究
  • 批准号:
    11505057
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    18.0万元
  • 批准年份:
    2015
  • 负责人:
    王永佳
  • 依托单位:
国内基金
海外基金