arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1906.04262astro-ph.CO
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Halo基模拟星系表中声学标度变化的检验

Tests of Acoustic Scale Shifts in Halo-based Mock Galaxy Catalogues

Duan Yutong, Daniel Eisenstein

摘要:

我们利用模拟目录从高精度的宇宙学$N$体模拟,以量化的变化,可能会导致从星系聚类偏差的声学尺度的恢复。星系和暗物质晕之间的关系在现代红移巡天中是一个复杂的系统误差来源,特别是当宇宙学测量的精度低于百分之一时。除了解释物质示踪剂与真实物质分布之间的密度对比度的标量线性偏差参数之外,其他类型的星系偏差,例如聚集和速度偏差,也可能显着改变从小到大尺度的聚集信号。我们创建模拟的基础上广义晕占领人口的36个周期性框从\abacuscosmos释放。在$48 \, h^{-3} \mathrm{Gpc}^3$的总体积中,我们测试了各种有偏模型以及无偏基本情况。两种重建方法被应用到星系样本和表观声学尺度通过拟合两点关联函数多极。相对于基线,我们发现一个$0.3\%$转移的视线声学尺度的卫星星系人口的变化,我们发现一个$0.7\%$转移的极端水平的速度偏差的中央星系。所有其他偏倚模型在重建后均与$0.2\%$水平的零偏移一致。我们注意到,探索的偏差模型是相对较大的变化,在小规模聚类中产生相当大的和可能可区分的变化,其建模将进一步校准BAO标准标尺。

英文摘要:

We utilise mock catalogues from high-accuracy cosmological $N$-body simulations to quantify shifts in the recovery of the acoustic scale that could potentially result from galaxy clustering bias. The relationship between galaxies and dark matter halos presents a complicated source of systematic errors in modern redshift surveys, particularly when aiming to make cosmological measurements to sub-percent precision. Apart from a scalar, linear bias parameter accounting for the density contrast ratio between matter tracers and the true matter distribution, other types of galaxy bias, such as assembly and velocity biases, may also significantly alter clustering signals from small to large scales. We create mocks based on generalised halo occupation populations of 36 periodic boxes from the \abacuscosmos release with. In a total volume of $48 \, h^{-3} \mathrm{Gpc}^3$, we test various biased models along with an unbiased base case. Two reconstruction methods are applied to galaxy samples and the apparent acoustic scale is derived by fitting the two-point correlation function multipoles. With respect to the baseline, we find a $0.3\%$ shift in the line-of-sight acoustic scale for one variation in the satellite galaxy population, and we find an $0.7\%$ shift for an extreme level of velocity bias of the central galaxies. All other bias models are consistent with zero shift at the $0.2\%$ level after reconstruction. We note that the bias models explored are relatively large variations, producing sizeable and likely distinguishable changes in small-scale clustering, the modelling of which would further calibrate the BAO standard ruler.

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