Relating the structure of dark matter halos to their assembly and environment. (arXiv:2003.05137v1 [astro-ph.GA])
<a href="http://arxiv.org/find/astro-ph/1/au:+Chen_Y/0/1/0/all/0/1">Yangyao Chen</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Mo_H/0/1/0/all/0/1">H.J. Mo</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Li_C/0/1/0/all/0/1">Cheng Li</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Wang_H/0/1/0/all/0/1">Huiyuan Wang</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Yang_X/0/1/0/all/0/1">Xiaohu Yang</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Zhang_Y/0/1/0/all/0/1">Youcai Zhang</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Wang_K/0/1/0/all/0/1">Kai Wang</a>

We use the ELUCID N-Body simulation to study the relation of structural
properties of dark matter halos to their assembly history and environment. We
find that the complexity of halo assembly histories can be well described by a
small number of principal components. Using decision trees built with the
random ensemble method, we find that the correlation between halo concentration
and assembly history is tight: more than 60% of the variance in halo
concentration can be explained by assembly history alone. Halo shape and spin
parameters are found to depend not only on assembly history, but also on
environment and initial condition, and these dependencies are not orthogonal.
The structures of more massive halos depend more strongly on higher-order
components of the assembly history. The relations between halo intrinsic
properties and environment are weak compared to their variances, with the
anisotropy of local tidal fields having the strongest correlation with halo
properties. Our method of dimension reduction and regression can help simplify
the characterization of the halo population and clarify the degeneracy among
halo properties.

We use the ELUCID N-Body simulation to study the relation of structural
properties of dark matter halos to their assembly history and environment. We
find that the complexity of halo assembly histories can be well described by a
small number of principal components. Using decision trees built with the
random ensemble method, we find that the correlation between halo concentration
and assembly history is tight: more than 60% of the variance in halo
concentration can be explained by assembly history alone. Halo shape and spin
parameters are found to depend not only on assembly history, but also on
environment and initial condition, and these dependencies are not orthogonal.
The structures of more massive halos depend more strongly on higher-order
components of the assembly history. The relations between halo intrinsic
properties and environment are weak compared to their variances, with the
anisotropy of local tidal fields having the strongest correlation with halo
properties. Our method of dimension reduction and regression can help simplify
the characterization of the halo population and clarify the degeneracy among
halo properties.

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