ﻻ يوجد ملخص باللغة العربية
Halo occupation distribution (HOD) models describe the number of galaxies that reside in different haloes, and are widely used in galaxy-halo connection studies using the halo model (HM). Here, we introduce and study HOD response functions $R_mathcal{O}^g$ that describe the response of the HODs to long-wavelength perturbations $mathcal{O}$. The linear galaxy bias parameters $b_mathcal{O}^g$ are a weighted version of $b_mathcal{O}^h + R_mathcal{O}^g$, where $b_mathcal{O}^h$ is the halo bias, but the contribution from $R_mathcal{O}^g$ is routinely ignored in the literature. We investigate the impact of this by measuring the $R_mathcal{O}^g$ in separate universe simulations of the IllustrisTNG model for three types of perturbations: total matter perturbations, $mathcal{O}=delta_m$; baryon-CDM compensated isocurvature perturbations, $mathcal{O}=sigma$; and potential perturbations with local primordial non-Gaussianity, $mathcal{O}propto f_{rm NL}phi$. Our main takeaway message is that the $R_mathcal{O}^g$ are not negligible in general and their size should be estimated on a case-by-case basis. For stellar-mass selected galaxies, the responses $R_phi^g$ and $R_sigma^g$ are sizeable and cannot be neglected in HM calculations of the bias parameters $b_phi^g$ and $b_sigma^g$; this is relevant to constrain inflation using galaxies. On the other hand, we do not detect a strong impact of the HOD response $R_1^g$ on the linear galaxy bias $b_1^g$. These results can be explained by the impact that the perturbations have on stellar-to-total-mass relations. We also look into the impact on the bias of the gas distribution and find similar conclusions. We show that a single extra parameter describing the overall amplitude of $R_mathcal{O}^g$ recovers the measured $b_mathcal{O}^g$ well, which indicates that $R_mathcal{O}^g$ can be easily added to HM/HOD studies as a new ingredient.
Understanding the impact of halo properties beyond halo mass on the clustering of galaxies (namely galaxy assembly bias) remains a challenge for contemporary models of galaxy clustering. We explore the use of machine learning to predict the halo occu
We study the impact of theoretical uncertainty in the dark matter halo mass function and halo bias on dark energy constraints from imminent galaxy cluster surveys. We find that for an optical cluster survey like the Dark Energy Survey, the accuracy r
Dark matter halo clustering depends not only on halo mass, but also on other properties such as concentration and shape. This phenomenon is known broadly as assembly bias. We explore the dependence of assembly bias on halo definition, parametrized by
It has been recently shown that any halo velocity bias present in the initial conditions does not decay to unity, in agreement with predictions from peak theory. However, this is at odds with the standard formalism based on the coupled fluids approxi
We measure the projected galaxy clustering and galaxy-galaxy lensing signals using the Galaxy And Mass Assembly (GAMA) survey and Kilo-Degree Survey (KiDS) to study galaxy bias. We use the concept of non-linear and stochastic galaxy biasing in the fr