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We study how well we can reconstruct the 2-point clustering of galaxies on linear scales, as a function of mass and luminosity, using the halo occupation distribution (HOD) in several semi-analytical models (SAMs) of galaxy formation from the Millennium Simulation. We find that HOD with Friends of Friends groups can reproduce galaxy clustering better than gravitationally bound haloes. This indicates that Friends of Friends groups are more directly related to the clustering of these regions than the bound particles of the overdensities. In general we find that the reconstruction works at best to 5% accuracy: it underestimates the bias for bright galaxies. This translates to an overestimation of 50% in the halo mass when we use clustering to calibrate mass. We also found a degeneracy on the mass prediction from the clustering amplitude that affects all the masses. This effect is due to the clustering dependence on the host halo substructure, an indication of assembly bias. We show that the clustering of haloes of a given mass increases with the number of subhaloes, a result that only depends on the underlying matter distribution. As the number of galaxies increases with the number of subhaloes in SAMs, this results in a low bias for the HOD reconstruction. We expect this effect to apply to other models of galaxy formation, including the real universe, as long as the number of galaxies incresases with the number of subhaloes. We have also found that the reconstructions of galaxy bias from the HOD model fails for low mass haloes with M = 3-5x10^11 Msun/h. We find that this is because galaxy clustering is more strongly affected by assembly bias for these low masses.
Using dark matter simulations we show how halo bias is determined by local density and not by halo mass. This is not totally surprising, as according to the peak-background split model, local density is the property that constraints bias at large sca
We use a large dark matter simulation of a LambdaCDM model to investigate the clustering and environmental dependence of the number of substructures in a halo. Focusing on redshift z=1, we find that the halo occupation distribution is sensitive at th
We combine the most precise small scale ($< 100, rm h^{-1}kpc$) quasar clustering constraintsto date with recent measurements at large scales ($> 1, rm h^{-1}Mpc$) from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) to better constrain
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 use the projected correlation function w_p(r_p) of a volume-limited subsample of the Sloan Digital Sky Survey (SDSS) main galaxy redshift catalogue to measure the halo occupation distribution (HOD) of the galaxies of the sample. Simultaneously, we