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arXiv 2407.04473astro-ph.COphysics.comp-ph
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ACCEL$^2$项目:在大体积流体动力学模拟中模拟Lyman-$α$森林

The ACCEL$^2$ project: simulating Lyman-$α$ forest in large-volume hydrodynamical simulations

Solène Chabanier, Corentin Ravoux, Lucas Latrille, Jean Sexton, Éric Armengaud, Julian Bautista, Tyann Dumerchat, Zarija Lukić

AI总结:

ACCEL$^2$项目通过大体积流体动力学模拟研究Lyman-$α$森林,发现大尺度模式收敛性受模拟盒分辨率影响,并首次明确探测到BAO信号。

摘要:

从Lyman-$α$森林相关性中提取宇宙学信息,通常要么使用通过线性理论解释的大尺度信息,要么使用通过昂贵的流体动力学模拟解释的小尺度信息。对所有可测量尺度上的3D相关性进行完整的宇宙学解释面临着挑战,这需要更真实的模型,包含非线性的小尺度复杂增长,而这只能在大体积流体动力学模拟中研究。过去的工作通常受限于模拟的宇宙学体积与Lyman-$α$信号起源的低密度星系际介质分辨率之间的权衡。我们进行了一系列星系际介质的流体动力学模拟,其中包括有史以来在体积上(640 $h^{-1}\mathrm{Mpc}$)进行的最大规模的Lyman-$α$模拟之一,同时在较小体积中进行了分辨率高达25 $h^{-1}\mathrm{kpc}$的模拟,这将在未来的研究中进一步改进以展示分辨率收敛性。我们将这些模拟预测的3D Lyman-$α$功率谱与不同的非线性模型进行比较。推断出的Lyman-$α$偏置和红移空间畸变(RSD)参数$b_α$和$β_α$与在SDSS和DESI数据中测量到的结果高度一致。我们发现,与直觉相反,决定$β_α$的3D Lyman-$α$功率谱大尺度模式的收敛性,主要通过模式耦合受到模拟盒分辨率的影响,而不是盒体积本身。最后,我们研究了编码在3D Lyman-$α$功率谱中的BAO信号。首次在流体动力学模拟中,我们明确探测到了BAO信号,但我们仅勉强探测到了与结构非线性增长相关的阻尼。

英文摘要:

Cosmological information is usually extracted from the Lyman-$α$ forest correlations using only either large-scale information interpreted through linear theory or using small-scale information interpreted by means of expensive hydrodynamical simulations. A complete cosmological interpretation of the 3D correlations at all measurable scales is challenged by the need of more realistic models including the complex growth of non-linear small scales that can only be studied within large hydrodynamical simulations. Past work were often limited by the trade off between the simulated cosmological volume and the resolution of the low-density intergalactic medium from which the Lyman-$α$ signal originates. We conduct a suite of hydrodynamical simulations of the intergalactic medium, including one of the largest Lyman-$α$ simulations ever performed in terms of volume (640 $h^{-1}\mathrm{Mpc}$), alongside simulations in smaller volumes with resolutions up to 25 $h^{-1}\mathrm{kpc}$, which will be further improved to show resolution convergence in future studies. We compare the 3D Lyman-$α$ power spectra predicted by those simulations to different non-linear models. The inferred Lyman-$α$ bias and redshift space distortion (RSD) parameters, $b_α$ and $β_α$ are in remarkable agreement with those measured in SDSS and DESI data. We find that, contrary to intuition, the convergence of large-scale modes of the 3D Lyman-$α$ power spectra, which determines $β_α$, is primarily influenced by the resolution of the simulation box through mode coupling, rather than the box size itself. Finally, we study the BAO signal encoded in the 3D Lyman-$α$ power spectra. For the first time with a hydrodynamical simulation, we clearly detect the BAO signal, however we only marginally detect its damping, associated with the non-linear growth of the structures.

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