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一种用于多谐波流动波动的傅里叶-累积量分析:采用多维生成函数方法。

A Fourier-cumulant analysis for multiharmonic flow fluctuation: by employing a multidimensional generating function approach.

作者信息

Taghavi Seyed Farid

机构信息

Physik Department E62, Technische Universität München, James Franck Str. 1, 85748 Garching, Germany.

出版信息

Eur Phys J C Part Fields. 2021;81(7):652. doi: 10.1140/epjc/s10052-021-09413-0. Epub 2021 Jul 23.

DOI:10.1140/epjc/s10052-021-09413-0
PMID:34776782
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8550610/
Abstract

The Fourier analysis of the final particle distribution followed by cumulant study of the Fourier coefficient event-by-event fluctuation is one of the main approaches for testing the collective evolution in the heavy-ion collision. Using a multidimensional generating function, we propose a method to extract any possible cumulant of multiharmonic flow fluctuations and classify them in terms of the order of cumulants and harmonics involved in them. In particular, we show that there are 33 distinct cumulants with order 2, 3, 4, 5 and harmonics 2, 3, 4, 5. We compute the normalized version of these cumulants from hydrodynamic simulation for Pb-Pb collisions based on T ENTo+VISH2+1+UrQMD. We compare the simulation with those normalized cumulants that the LHC has measured and predict the unmeasured ones. Comparing the initial and final state fluctuation normalized cumulants, we compute the linear and nonlinear hydrodynamic response couplings. We finally introduce the genuine three-particle correlation function containing information of all third-order cumulants.

摘要

对最终粒子分布进行傅里叶分析,然后逐事件波动地对傅里叶系数进行累积量研究,是检验重离子碰撞中集体演化的主要方法之一。利用多维生成函数,我们提出了一种提取多谐波流涨落任意可能累积量的方法,并根据累积量的阶数和其中涉及的谐波对它们进行分类。特别地,我们表明存在33个不同的累积量,其阶数为2、3、4、5,谐波为2、3、4、5。我们基于T ENTo+VISH2+1+UrQMD对铅-铅碰撞的流体动力学模拟计算了这些累积量的归一化版本。我们将模拟结果与大型强子对撞机测量的那些归一化累积量进行比较,并预测未测量的累积量。比较初态和末态涨落归一化累积量,我们计算了线性和非线性流体动力学响应耦合。我们最终引入了包含所有三阶累积量信息的真正三粒子关联函数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/758b7be8e0e2/10052_2021_9413_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/f2af863c0259/10052_2021_9413_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/58d76bd05499/10052_2021_9413_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/8a2af1ba04ae/10052_2021_9413_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/00b13a32026f/10052_2021_9413_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/e8c80dcdbe8e/10052_2021_9413_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/758b7be8e0e2/10052_2021_9413_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/f2af863c0259/10052_2021_9413_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/58d76bd05499/10052_2021_9413_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/8a2af1ba04ae/10052_2021_9413_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/00b13a32026f/10052_2021_9413_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/e8c80dcdbe8e/10052_2021_9413_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e55/8550610/758b7be8e0e2/10052_2021_9413_Fig6_HTML.jpg

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