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In hierarchical models, density fluctuations on different scales are correlated. This induces correlations between dark halo masses, their formation histories, and their larger-scale environments. In turn, this produces a correlation between galaxy properties and environment. This correlation is entirely statistical in nature. We show how the observed clustering of galaxies can be used to quantify the importance of this statistical correlation relative to other physical effects which may also give rise to correlations between the properties of galaxies and their surroundings. We also develop a halo model description of this environmental dependence of clustering.
The main ingredients of recent semi-analytic models of galaxy formation are summarised. We present predictions for the galaxy clustering properties of a well specified LCDM model whose parameters are constrained by observed local galaxy properties. W
A generic prediction of hierarchical clustering models is that the mass function of dark haloes in dense regions in the Universe should be top-heavy. We provide a novel test of this prediction using a sample of galaxies drawn from the Sloan Digital S
We compare state-of-the-art semi-analytic models of galaxy formation as well as advanced sub-halo abundance matching models with a large sample of early-type galaxies from SDSS at z < 0.3. We focus our attention on the dependence of median sizes of c
We investigate the star formation activity in galaxy pairs in chemical hydrodynamical simulations consistent with a Lambda-CDM scenario. A statistical analysis of the effects of galaxy interactions on the star formation activity as a function of orbi
Recently, Hierarchical Clustering (HC) has been considered through the lens of optimization. In particular, two maximization objectives have been defined. Moseley and Wang defined the emph{Revenue} objective to handle similarity information given by