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Quantitative Characterization of Quark-Gluon Plasma Properties with Dynamical Fluctuations

具有动态涨落的夸克-胶子等离子体特性的定量表征

基本信息

批准号：
2012922
负责人：
Chun Shen
金额：
$ 25.51万
依托单位：
Wayne State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-15 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2012922&HistoricalAwards=false
关键词：
Quantitative Characterization Quark Gluon Plasma

项目摘要

Quantifying the phase structure of matter at extreme temperature and density has profound impacts on understanding how quarks and gluons, the building blocks of nucleons, interact collectively and elucidating the property of the early Universe within the first microsecond after its creation in the Big Bang. High energy collisions of atomic nuclei create the Quark-Gluon Plasma (QGP), a new state of matter at about 2 trillion degrees Kelvin. The QGP behaves like a nearly perfect fluid, which flows ten times better than water. This project will develop a new theoretical framework to model how small ripples evolve in the QGP fluid. By decoding these ripples' traces in the experimental measurements, the PI will quantify the QGP properties and identify whether the nature of phase transition from ordinary matter to the QGP is like water transits to vapor. This project interweaves nuclear physics, high-performance computing, and advanced machine learning techniques. The interdisciplinary nature of the project helps the participating students acquire solid training in theoretical physics as well as computational science skills.This project will develop the first theoretical framework to model the 3D dynamical evolution of stochastic fluctuations in relativistic heavy-ion collisions. By studying how fluctuations of energy, momentum, and charge density dissipate in the collision system, one can quantify the thermal, critical, and transport properties of the QGP using experimental measurements. By integrating the proposed framework with the Bayesian analysis and applying them to heavy-ion collisions over wide ranges of collision energies, the PI and his group will extract quantitative phenomenological constraints on the QGP properties. Searching the critical point signature in experimental data is slated to break new ground in the application of deep learning techniques to physical science. This proposed framework serves as an essential infrastructure to guide and interpret the experiments at Relativistic Heavy Ion Collider Beam Energy Scan phase II, and high luminosity runs at the Large Hadron Collider. The theoretical advancement in understanding the dynamics of such a strongly-coupled many-body system can generate interesting cross-talk with cold atomic physics, cosmology, and neutron star/black mergers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

量化物质在极端温度和密度下的相结构对于理解夸克和胶子（核子的组成部分）如何集体相互作用以及阐明早期宇宙在大爆炸中创建后的第一微秒内的性质具有深远的影响。原子核的高能碰撞产生了夸克-胶子等离子体（QGP），这是一种约2万亿开氏度的新物质状态。QGP表现得像一种近乎完美的流体，其流动性比水好十倍。这个项目将开发一个新的理论框架来模拟QGP流体中的小波纹如何演变。通过对实验测量中的这些波纹痕迹进行解码，PI将量化QGP的性质，并确定从普通物质到QGP的相变性质是否像水转变为蒸汽。该项目交织了核物理，高性能计算和先进的机器学习技术。该项目的跨学科性质有助于参与学生获得坚实的理论物理训练以及计算科学技能。该项目将开发第一个理论框架，以模拟相对论重离子碰撞中随机涨落的3D动力学演化。通过研究碰撞系统中能量、动量和电荷密度的波动如何消散，人们可以使用实验测量来量化QGP的热、临界和输运性质。通过将所提出的框架与贝叶斯分析相结合，并将其应用于大范围碰撞能量的重离子碰撞，PI和他的团队将提取对QGP性质的定量唯象约束。在实验数据中搜索临界点签名将在深度学习技术应用于物理科学方面开辟新天地。这个建议的框架作为一个必不可少的基础设施，以指导和解释实验在相对论重离子对撞机束能量扫描第二阶段，和高亮度运行在大型强子对撞机。在理解这种强耦合多体系统动力学方面的理论进步可以与冷原子物理学、宇宙学和中子星星/黑色合并产生有趣的串扰。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（22）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Resonance production in Pb+Pb collisions at 5.02 TeV

5.02 TeV 下 Pb Pb 碰撞中的共振产生

DOI：
10.1051/epjconf/202225910008
发表时间：
2022
期刊：
EPJ Web of Conferences
影响因子：
0
作者：
Oliinychenko, Dmytro;Shen, Chun
通讯作者：
Shen, Chun

Multisystem Bayesian constraints on the transport coefficients of QCD matter

DOI：
10.1103/physrevc.103.054904
发表时间：
2020-11
期刊：
arXiv: High Energy Physics - Phenomenology
影响因子：
0
作者：
D. Everett;W. Ke;J. Paquet;G. Vujanovic;S. Bass;L. Du;C. Gale;M. Heffernan;U. Heinz;
通讯作者：
D. Everett;W. Ke;J. Paquet;G. Vujanovic;S. Bass;L. Du;C. Gale;M. Heffernan;U. Heinz;

Recent development of hydrodynamic modeling in heavy-ion collisions