Impact of assembly bias on clustering plus weak lensing cosmological\n analysis Article Swipe
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· 2024
· Open Access
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· DOI: https://doi.org/10.1051/0004-6361/202449574
· OA: W4391799357
Analytical models of galaxy-halo connection such as the Halo Occupation\nDistribution (HOD) model have been widely used over the past decades as a means\nto intensively test perturbative models on quasi-linear scales. However, these\nmodels fail to reproduce the galaxy-galaxy lensing signal on non-linear scales,\nover-predicting the observed signal up to 40%. With ongoing Stage-IV galaxy\nsurveys such as DESI and EUCLID, it is now crucial to accurately model the\ngalaxy-halo connection up to intra-halo scales to accurately estimate\ntheoretical uncertainties of perturbative models. This paper compares the\nstandard HOD model to an extended HOD framework that incorporates as additional\nfeatures galaxy assembly bias and local environmental dependencies on halo\noccupation. These models have been calibrated against the observed clustering\nand galaxy-galaxy lensing signal of eBOSS Luminous Red Galaxies (LRG) and\nEmission Lines Galaxies (ELG) in the range 0.6 < z < 1.1. A combined\nclustering-lensing cosmological analysis is then performed on the simulated\ngalaxy samples of both standard and extended HOD frameworks to quantify the\nsystematic budget of perturbative models. The extended HOD model offers a more\ncomprehensive understanding of the connection between galaxies and their\nsurroundings. In particular, we found that the LRGs preferentially occupy\ndenser and more anisotropic environments. Our results highlight the importance\nof considering environmental factors in galaxy formation models, with an\nextended HOD framework that reproduces the observed signal within 20% on scales\nbelow 10 Mpc/h. Our cosmological analysis reveals that our perturbative model\nyields similar constraints regardless of the galaxy population, with a better\ngoodness of fit for the extended HOD. These results suggest that the extended\nHOD framework should be used to quantify modeling systematics.\n
