论文标题

AGN反馈对使用Horizo​​n-agn模拟套件从LY $α$ forest的一维功率谱的影响

The impact of AGN feedback on the 1D power spectra from the Ly$α$ forest using the Horizon-AGN suite of simulations

论文作者

Chabanier, Solène, Bournaud, Frédéric, Dubois, Yohan, Palanque-Delabrouille, Nathalie, Yèche, Christophe, Armengaud, Eric, Peirani, Sébastien, Beckmann, Ricarda S.

论文摘要

Lyman-$α$ Forest是对宇宙学的强大探测器,但它也受到星系进化的强烈影响,以及诸如主动银河核(AGN)反馈的重型过程,可以在大规模上重新分配质量和能量。我们使用适应性网状改进代码Ramses进行的一系列八种水溶液模拟模拟来限制AGN反馈的签名。该系列始于Horizo​​n-AGN模拟,并改变了AGN喂养,反馈和随机性的子网格参数。这些模拟涵盖了根据所得的星系特性,涵盖了整个合理的反馈和喂养参数。 AGN在全球范围内抑制Lyman-$α$功率在所有尺度上。在大尺度上,能量注射和电离在来自AGN驱动的银河风的气体质量上占主导地位,从而抑制了功率。在小尺度上,更快的冷却气体会减轻抑制作用。这种效果随着红移的减少而增加。我们在$ z = 4.25 $和$ z = 2.0 $之间提供该签名的下限和上限,这是可以在未来工作后进行后处理阶段对其进行核算的,因为没有AGN反馈的运行模拟可以节省大量计算资源。在宇宙推理分析中忽略AGN反馈会导致强烈的偏见,而$σ_8$上的2 \%变化,$ n_s $上的偏移为1 \%偏移,这是当前限制$ n_s $的标准偏差的两倍。

The Lyman-$α$ forest is a powerful probe for cosmology, but it is also strongly impacted by galaxy evolution and baryonic processes such as Active Galactic Nuclei (AGN) feedback, which can redistribute mass and energy on large scales. We constrain the signatures of AGN feedback on the 1D power spectrum of the Lyman-$α$ forest using a series of eight hydro-cosmological simulations performed with the Adaptative Mesh Refinement code RAMSES. This series starts from the Horizon-AGN simulation and varies the sub-grid parameters for AGN feeding, feedback and stochasticity. These simulations cover the whole plausible range of feedback and feeding parameters according to the resulting galaxy properties. AGNs globally suppress the Lyman-$α$ power at all scales. On large scales, the energy injection and ionization dominate over the supply of gas mass from AGN-driven galactic winds, thus suppressing power. On small scales, faster cooling of denser gas mitigates the suppression. This effect increases with decreasing redshift. We provide lower and upper limits of this signature at nine redshifts between $z=4.25$ and $z=2.0$, making it possible to account for it at post-processing stage in future work given that running simulations without AGN feedback can save considerable amounts of computing resources. Ignoring AGN feedback in cosmological inference analyses leads to strong biases with 2\% shift on $σ_8$ and 1\% shift on $n_s$, which represents twice the standards deviation of the current constraints on $n_s$.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源