Toward Accurate Modeling of Galaxy Clustering on Small Scales: Halo Model Extensions and Lingering Tension
Gillian D. Beltz-Mohrmann, Adam O. Szewciw, Andreas A. Berlind,, Manodeep Sinha

TL;DR
This study enhances galaxy clustering models by incorporating assembly bias, velocity bias, and baryonic effects, successfully fitting low-luminosity galaxy data but revealing tensions with high-luminosity galaxy observations, questioning the current cosmological model.
Contribution
It introduces extended halo occupation models with assembly and velocity bias, improving small-scale galaxy clustering fits and testing Planck LCDM cosmology.
Findings
Low-luminosity galaxies show evidence for assembly and velocity bias.
Models fit low-luminosity data well without tension.
High-luminosity galaxies exhibit tension with the model.
Abstract
This paper represents an effort to provide robust constraints on the galaxy-halo connection and simultaneously test the Planck LCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this "decorated" HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering…
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Taxonomy
TopicsAdvanced Clustering Algorithms Research · Human Mobility and Location-Based Analysis
