论文标题

在红移空间中用于星系聚类的灵活的subhalo丰度匹配模型

A flexible subhalo abundance matching model for galaxy clustering in redshift space

论文作者

Contreras, Sergio, Angulo, Raul, Zennaro, Matteo

论文摘要

我们开发了能够准确地重现最先进的流体动力学模拟中星系的真实和红移空间聚类的次何卢丰度匹配(假)的扩展。我们的方法使用低分辨率的仅重力模拟,它包括卫星星系的孤儿和潮汐破坏处方,以及柔性量的星系组装偏置。此外,它包括基于暗物质积聚率的恒星形成率(SFR)的食谱。我们测试了模型对TNG300流体动力模拟中恒星质量和SFR选择星系的目录的准确性。通过拟合少量的自由参数,我们的扩展假模具重现了数字密度的投影相关函数和红移空间的多极$ 10^{ - 3} - 10^{ - 2} { - 2} \,h^{3} {\ rm mpc} {\ rm mpc}^{ - 3}^{ - 3} $,在$ z = 1 $和$ z = 0 $ = 0 $和$ z = 0 0. h^{ - 1} {\ rm mpc} $。同时,假结果还检索了TNG300 Galaxy目录中存在的正确的光环占用分布,星系组装偏置的水平以及具有高阶统计。作为应用程序,我们表明我们的模型同时拟合了3个不相交的恒星质量箱中SDSS的投影相关函数,其精度与TNG300星系的准确性相似。即使使用低分辨率和中等分辨率模拟,该假伸展也可用于获得准确的聚类预测。

We develop an extension of subhalo abundance matching (SHAM) capable of accurately reproducing the real and redshift-space clustering of galaxies in a state-of-the-art hydrodynamical simulation. Our method uses a low-resolution gravity-only simulation and it includes orphan and tidal disruption prescriptions for satellite galaxies, and a flexible amount of galaxy assembly bias. Furthermore, it includes recipes for star formation rate (SFR) based on the dark matter accretion rate. We test the accuracy of our model against catalogues of stellar-mass- and SFR-selected galaxies in the TNG300 hydrodynamic simulation. By fitting a small number of free parameters, our extended SHAM reproduces the projected correlation function and redshift-space multipoles for number densities $10^{-3} - 10^{-2}\, h^{3}{\rm Mpc}^{-3}$, at $z=1$ and $z=0$, and for scales $r \in [0.3 - 20] h^{-1}{\rm Mpc}$. Simultaneously, the SHAM results also retrieve the correct halo occupation distribution, the level of galaxy assembly bias, and higher-order statistics present in the TNG300 galaxy catalogues. As an application, we show that our model simultaneously fits the projected correlation function of the SDSS in 3 disjoint stellar mass bins, with an accuracy similar to that of TNG300 galaxies. This SHAM extension can be used to get accurate clustering prediction even when using low and moderate-resolution simulations.

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