4.7 Article

Quantification of discreteness effects in cosmological N-body simulations:: Initial conditions

期刊

PHYSICAL REVIEW D
卷 75, 期 6, 页码 -

出版社

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.75.063516

关键词

-

向作者/读者索取更多资源

The relation between the results of cosmological N-body simulations, and the continuum theoretical models they simulate, is currently not understood in a way which allows a quantification of N dependent effects. In this first of a series of papers on this issue, we consider the quantification of such effects in the initial conditions of such simulations. A general formalism developed in [A. Gabrielli, Phys. Rev. E 70, 066131 (2004).] allows us to write down an exact expression for the power spectrum of the point distributions generated by the standard algorithm for generating such initial conditions. Expanded perturbatively in the amplitude of the input (i.e. theoretical, continuum) power spectrum, we obtain at linear order the input power spectrum, plus two terms which arise from discreteness and contribute at large wave numbers. For cosmological type power spectra, one obtains as expected, the input spectrum for wave numbers k smaller than that characteristic of the discreteness. The comparison of real space correlation properties is more subtle because the discreteness corrections are not as strongly localized in real space. For cosmological type spectra the theoretical mass variance in spheres and two-point correlation function are well approximated above a finite distance. For typical initial amplitudes this distance is a few times the interparticle distance, but it diverges as this amplitude (or, equivalently, the initial redshift of the cosmological simulation) goes to zero, at fixed particle density. We discuss briefly the physical significance of these discreteness terms in the initial conditions, in particular, with respect to the definition of the continuum limit of N-body simulations.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据