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arXiv 2202.08435astro-ph.CO
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Lagrangian空间中的红移空间畸变与暗物质的线性大尺度速度场

Redshift space distortions in Lagrangian space and the linear large scale velocity field of dark matter

Emily Tyhurst, Hamsa Padmanabhan, Ue-Li Pen

AI总结:

本文研究了Lagrangian空间中的红移空间畸变与暗物质线性速度场,通过传递函数进行线性建模并分析单极-四极比率,发现Lagrangian方法使宇宙线性增长率$f$的误差改善3倍且无需非线性建模。

摘要:

解开红移空间坐标、速度测量与三维真实空间坐标之间的联系,是一个宇宙学问题,通常通过对速度-位置耦合的线性理解来建模。这种线性信息在物质密度场的Lagrangian空间图像中得到了更好的保留。通过Lagrangian空间测量,我们可以提取更多信息,并对宇宙的线性增长率做出更准确的估计。在本文中,我们通过传递函数探讨了物质粒子速度的线性建模,并借此研究了与初始条件相关性的下降在多大程度上可能受到基于速度的非线性效应的污染。通过对单极-四极比率的详尽分析,我们发现在使用Lorentzian finger-of-God阻尼因子时,Eulerian速度弥散的最佳拟合值为 $σ_p = 378.3$ km/s,而在使用Gaussian阻尼因子时为 $σ_p = 254.6$ km/s。我们分别在Eulerian和Lagrangian情况下估计了宇宙学线性增长率 $f$ 的协方差。通过对比Lagrangian和Eulerian情况,我们发现 $f$ 的误差改善了3倍,且无需进行非线性速度弥散建模。

英文摘要:

Untangling the connection between redshift space coordinates, a velocity measurement, and three dimensional real space coordinates, is a cosmological problem that is often modeled through a linear understanding of the velocity-position coupling. This linear information is better preserved in the Lagrangian space picture of the matter density field. Through Lagrangian space measurements, we can extract more information and make more accurate estimates of the linear growth rate of the universe. In this paper, we address the linear modelling of matter particle velocities through transfer functions, and in doing so examine to what degree the decrease in correlation with initial conditions may be contaminated by velocity-based nonlinearities. With a thorough analysis of the monopole-quadrupole ratio, we find the best-fit values for the Eulerian velocity dispersion, $σ_p = 378.3$ km/s for a Lorentzian finger-of-God damping factor and $σ_p = 254.6$ km/s for a Gaussian one. The covariance of the cosmological linear growth rate $f$, is estimated in the Eulerian and Lagrangian cases. Comparing Lagrangian and Eulerian, we find that the error in $f$ improves by a factor of 3, without the need for nonlinear velocity dispersion modelling.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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