Modeling color-dependent galaxy clustering in cosmological simulations
Shogo Masaki, Yen-Ting Lin, Naoki Yoshida

TL;DR
This paper extends the subhalo abundance matching method to assign galaxy colors based on secondary subhalo properties, successfully reproducing observed galaxy clustering and lensing signals without baryonic physics.
Contribution
It introduces a new approach using local dark matter density as a proxy for galaxy color, enhancing the modeling of color-dependent galaxy clustering in cosmological simulations.
Findings
The model accurately reproduces observed galaxy two-point correlation functions.
Using local dark matter density improves agreement with galaxy-galaxy lensing data.
Scatter in the density-color relation enhances model accuracy.
Abstract
We extend the subhalo abundance matching method to assign galaxy color to subhalos. We separate a luminosity-binned subhalo sample into two groups by a secondary subhalo property which is presumed to be correlated with galaxy color. The two subsamples then represent red and blue galaxy populations. We explore two models for the secondary property, namely subhalo assembly time and local dark matter density around each subhalo. The model predictions for the galaxy two-point correlation functions are compared with the recent results from the Sloan Digital Sky Survey. We show that the observed color dependence of galaxy clustering can be reproduced well by our method applied to cosmological N-body simulations without baryonic processes. We then compare the model predictions for the color-dependent galaxy-mass cross correlation functions with the results from gravitational lensing…
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