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arXiv 1102.0641astro-ph.CO
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微扰理论与晕模型相结合的物质双谱

Combining perturbation theories with halo models for the matter bispectrum

Patrick Valageas, Takahiro Nishimichi

摘要:

我们研究如何建立统一的模型,以能够预测的物质密度双谱(和功率谱)从非常大到小的尺度,并在同一时间符合微扰理论在低$k$和晕模型在高$k$。我们使用拉格朗日框架分解的双谱成“3-halo”,“2-halo”,和“1-halo”的贡献,相关的“微扰”和“非微扰”条款。我们描述了一个简单的实现这种方法,并提出了详细的比较数值模拟。我们发现,1-halo和2-halo的贡献包含计数项,以确保其衰减在低$k$,所需的物理约束,并允许更好地匹配模拟。与功率谱相反,标准的1-回路微扰理论可用于微扰3-晕贡献,因为它在高$k$下不会增长太快。而且,它比本文所研究的两种重定格式简单得多,精度也高得多。我们得到了很好的协议,在大尺度和小尺度上的数值模拟,但过渡尺度描述不佳的最简单的实现。这不能通过简单的修改晕参数进行修正,但我们展示了如何通过一个简单的插值方案,这是限制在这个中间政权的功率谱和双谱进行校正。然后,我们在轻度和高度非线性尺度上达到了10%的精度,而在较大的弱非线性尺度上获得了1%的精度。这也适用于实空间两点关联函数。

英文摘要:

We investigate how unified models should be built to be able to predict the matter-density bispectrum (and power spectrum) from very large to small scales and that are at the same time consistent with perturbation theory at low $k$ and with halo models at high $k$. We use a Lagrangian framework to decompose the bispectrum into "3-halo", "2-halo", and "1-halo" contributions, related to "perturbative" and "non-perturbative" terms. We describe a simple implementation of this approach and present a detailed comparison with numerical simulations. We show that the 1-halo and 2-halo contributions contain counterterms that ensure their decay at low $k$, as required by physical constraints, and allow a better match to simulations. Contrary to the power spectrum, the standard 1-loop perturbation theory can be used for the perturbative 3-halo contribution because it does not grow too fast at high $k$. Moreover, it is much simpler and more accurate than two resummation schemes investigated in this paper. We obtain a good agreement with numerical simulations on both large and small scales, but the transition scales are poorly described by the simplest implementation. This cannot be amended by simple modifications to the halo parameters, but we show how it can be corrected for the power spectrum and the bispectrum through a simple interpolation scheme that is restricted to this intermediate regime. Then, we reach an accuracy on the order of 10% on mildly and highly nonlinear scales, while an accuracy on the order of 1% is obtained on larger weakly nonlinear scales. This also holds for the real-space two-point correlation function.

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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