Most of the recent observational efforts to understand galaxy evolution have been focused on determining the history of cosmic star formation, gas density evolution, metallicity evolution, and mass growth of the Universe (Daddi et al. 2004; Mannucci et al. 2010; Madau & Dickinson 2014; Tomczak et al. 2014; Bouwens et al. 2015). These multiwavelength observational constraints have usually been summarized as galaxy scaling relations that might or might not change with redshift (Mannucci et al. 2010; Elbaz et al. 2011; Bouwens et al. 2014; Troncoso et al. 2014), in high- or low-density environments, in extreme physical conditions (starburst, AGN galaxies), and in spatially resolved data due to internal variations of the galaxy properties (Sanchez et al. 2013). In parallel, theoretical works and simulations have tried to explain the physical mechanisms that reproduce the measured global properties  (Daddi et al. 2010; Davé et al. 2011; Lilly et al. 2013; Lagos et al. 2014; Padilla et al. 2014). Despite these efforts, the completeness and cleanness of the sample are still challenging problems that depend on the sample selection-method, instrument limits, and telescope time. These problems make the comparison between observational and theoretical works even more difficult. For example, Campbell et al. (2014) compared the stellar mass of GALFORM galaxies predicted by the model with those obtained through the fit of their predicted broad-band colors. They found that both quantities differ for an individual galaxy, hence the clustering of mass-selected samples can be affected by systematic biases. Therefore, mass-selected samples might provide erroneous conclusions regarding their progenitors and descendants. In addition, the evolution of scaling relations is constrained with observations of galaxy samples that are selected with luminosity or stellar-mass thresholds and are located at different redshifts, which does not necessarily constitute causally connected populations (i.e., they do not follow a progenitor-to-descendant relation). Clustering-selected samples overcome this problem because in a hierarchical clustering scenario, a correlation analysis allows us to estimate the bias and hence statistically determine the progenitors and descendants of galaxy samples. The bias parameter measures the clustering difference between the galaxy spatial distribution and underlying dark-matter distribution. Thus, it relates the typical mass of halos hosting the galaxies (Sheth et al. 2001). Hence, measuring it in galaxy samples at different redshifts determines whether we are following the evolution of baryonic processes occurring in halos of similar masses or not. This fact is of extreme importance because once it is determined, we can use the multiwavelength data to study the evolution of the baryonic processes at certain halo mass, establishing a direct link between observations and galaxy formation models. Padilla et al. (2011) selected early-type galaxies according to their clustering and luminosity function in the MUSYC survey. So far, no study that selects star-forming galaxies according their clustering and luminosity function has been reported.
Citation: Padilla et al. 2014
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