The multidimensional dependence of halo bias in the eye of a machine: a tale of halo structure, assembly, and environment

The multidimensional dependence of halo bias in the eye of a machine: a tale of halo structure, assembly, and environment
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机器眼中光环偏差的多维依赖性:光环结构、组装和环境的故事

DOI:
10.1093/mnras/sty2822
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发表时间:
2018-02
影响因子:
4.8
通讯作者:
Jiang Chunyan
Jiang Chunyan
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Han Jiaxin;Li Yin;Jing Yipeng;Nishimichi Takahiro;Wang Wenting;Jiang Chunyan

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我们提出了一种利用高斯过程回归研究晕偏与多晕性质联合依赖关系的新方法。利用$\Lambda$ CDM $N$ -体模拟,我们全面研究了光晕结构、形成历史和环境对联合偏倚的依赖。我们表明,偏差是一个多元函数的光环性质,落在三个政权。对于大质量的光晕,光晕质量解释了大部分的偏差变化。对于早期形成的晕,偏差敏感地取决于最近的质量吸积历史。对于低质量和晚形成的光晕,偏差更多地取决于光晕的结构,比如它的形状和旋转。我们的框架使我们能够令人信服地证明$V_\mathrm{max}/V_\mathrm{vir}$是偏差建模中地层时间的有耗代理,而质量、自旋、形状和地层时间变量彼此之间是不冗余的。质量与形成时间的结合在很大程度上解释了偏差对质量吸积史的依赖。综合所有内部光晕性质,充分解释了光晕内部的密度分布依赖性,并预测了单个光晕的聚类变化到$20\%$水平$\sim 10\mathrm{Mpc}h^{-1}$。当从光晕中心$1\mathrm{Mpc}h^{-1}$外测量环境密度时,它的性能优于并在很大程度上解释了对内部光晕结构的偏差依赖,从而解释了$30\%$以上水平的偏差变化。
We develop a novel approach in exploring the joint dependence of halo bias on multiple halo properties using Gaussian process regression. Using a $\Lambda$CDM $N$-body simulation, we carry out a comprehensive study of the joint bias dependence on halo structure, formation history and environment. We show that the bias is a multivariate function of halo properties that falls into three regimes. For massive haloes, halo mass explains the majority of bias variation. For early-forming haloes, bias depends sensitively on the recent mass accretion history. For low-mass and late-forming haloes, bias depends more on the structure of a halo such as its shape and spin. Our framework enables us to convincingly prove that $V_\mathrm{max}/V_\mathrm{vir}$ is a lossy proxy of formation time for bias modelling, whereas the mass, spin, shape and formation time variables are non-redundant with respect to each other. Combining mass and formation time largely accounts for the mass accretion history dependence of bias. Combining all the internal halo properties fully accounts for the density profile dependence inside haloes, and predicts the clustering variation of individual haloes to a $20\%$ level at $\sim 10\mathrm{Mpc}h^{-1}$. When an environmental density is measured outside $1\mathrm{Mpc}h^{-1}$ from the halo centre, it outperforms and largely accounts for the bias dependence on the internal halo structure, explaining the bias variation above a level of $30\%$.
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发表时间: 2006-10
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