Cosmic Structure Formation with Kinetic Field Theory
Cosmic Structure Formation with Kinetic Field Theory
复制标题
用动场论研究宇宙结构的形成
DOI：
10.1002/andp.201800446
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发表时间：
2019
影响因子：
2.4
通讯作者：
Daniel Geiss
中科院分区：
文献类型：
--
作者：
M. Bartelmann;E. Kozlikin;R. Lilow;C. Littek;F. Fabis;I. Kostyuk;C. Viermann;Lavinia Heisenberg;Sara Konrad;Daniel Geiss
动力学场论（英语：Kinetic field theory，KFT）是一种统计场论，用于研究处于或不处于平衡状态的经典点粒子系综。综述了它在宇宙结构形成中的应用。从生成泛函的构建开始，详细描述了该理论需要如何适应不断扩大的空间背景和宇宙结构的均匀性和各向同性，相关的初始条件。基于生成泛函，我们提出了三种研究非线性宇宙结构的方法，它们分别基于相互作用算符的展开、相互作用项的平均和微扰项的简化。给出了非线性宇宙功率谱的一个无参数的解析方程。解释了如何从理论中导出束缚结构的密度分布和速度功率谱。它澄清了KFT与BBGKY层次结构的关系。然后将动力场理论应用于流体，重新制定KFT的宏观量。由此产生的再膨胀方案被用来描述气体和暗物质的混合物。最后讨论了KFT如何与修正的引力理论相结合。作为一个非宇宙学应用的例子，结果显示来自KFT的冷里德伯原子的空间相关函数。
Kinetic field theory (KFT) is a statistical field theory for an ensemble of classical point particles in or out of equilibrium. Its application to cosmological structure formation is reviewed. Beginning with the construction of a generating functional, it is described in detail how the theory needs to be adapted to an expanding spatial background and the homogeneous and isotropic, correlated initial conditions for cosmic structures. Based on the generating functional, three approaches are developed to nonlinear cosmic structures, which rest either on expanding an interaction operator, averaging the interaction term, or resumming perturbation terms. An analytic, parameter‐free equation for the nonlinear cosmic power spectrum is presented. It is explained how density profiles of bound structures and velocity power spectra can be derived from the theory. It is clarified how KFT relates to the BBGKY hierarchy. Kinetic field theory is then applied to fluids, reformulating KFT in terms of macroscopic quantities. The resulting resummation scheme is used to describe mixtures of gas and dark matter. Finally, it is discussed how KFT can be combined with modified theories of gravity. As an example for a noncosmological application, results are shown on the spatial correlation function of cold Rydberg atoms derived from KFT.
影响因子：
6.4
作者：
M. Pietroni
通讯作者：
M. Pietroni