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arXiv 1608.03293astro-ph.COastro-ph.GA
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AGN加热对低红移Lyα森林的影响

The Effect Of AGN Heating On The Low-Redshift Lyα Forest

Alex Gurvich, Blakesley Burkhart, Simeon Bird

摘要:

利用Illustris模拟研究了活动星系核加热和紫外背景对低红移Lyman- $α$森林柱密度分布的影响。我们表明,Illustris再现观测$z =0.1$在列密度范围$10^{12.5} - 10^{13.5}$ cm $^{-2}$,相关的“光子生产不足的危机。“我们将此归因于AGN反馈的包含,它改变了气体分布,以模拟额外光子的影响,以及Faucher-Giguère紫外背景的使用,它在$z=0.1$比以前考虑的Haardt & Madau背景更电离。我们表明,运行与平滑粒子流体动力学和模拟使用移动网格的模拟之间的差异是小的,在此列密度范围内,但可以更显着在较大的列密度。我们进一步考虑了超新星反馈、Voigt轮廓拟合和有限分辨率的影响,所有这些对CDD的影响都很小。最后,我们确定了我们的模拟和观测之间的差异,在柱密度$10^{14} - 10^{16}$ cm $^{-2}$,其中Illustris产生太少的吸收体,这表明活动星系核反馈模型应进一步完善。由于“光子生产不足危机”主要影响低柱密度系统,我们得出结论,活动星系核反馈和标准电离背景模型可以解决危机。

英文摘要:

We investigate the effects of AGN heating and the ultraviolet background on the low-redshift Lyman-$α$ forest column density distribution (CDD) using the Illustris simulation. We show that Illustris reproduces observations at $z =0.1$ in the column density range $10^{12.5} - 10^{13.5}$cm$^{-2}$, relevant for the "photon underproduction crisis." We attribute this to the inclusion of AGN feedback, which changes the gas distribution so as to mimic the effect of extra photons, as well as the use of the Faucher-Giguère ultraviolet background, which is more ionizing at $z=0.1$ than the Haardt & Madau background previously considered. We show that the difference between simulations run with smoothed particle hydrodynamics and simulations using a moving mesh is small in this column density range but can be more significant at larger column densities. We further consider the effect of supernova feedback, Voigt profile fitting and finite resolution, all of which we show to have little influence on the CDD. Finally, we identify a discrepancy between our simulations and observations at column densities $10^{14} - 10^{16}$cm$^{-2}$, where Illustris produces too few absorbers, which suggests the AGN feedback model should be further refined. Since the "photon underproduction crisis" primarily affects lower column density systems, we conclude that AGN feedback and standard ionizing background models can resolve the crisis.

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