[Abridged] In this paper, we carry out a detailed analysis of the performance of two different methods to identify the diffuse stellar light in cosmological hydrodynamical simulations of galaxy clusters. One method is based on a dynamical analysis of
the stellar component. The second method is closer to techniques commonly employed in observational studies. Both the dynamical method and the method based on the surface brightness limit criterion are applied to the same set of hydrodynamical simulations for a large sample about 80 galaxy clusters. We find significant differences between the ICL and DSC fractions computed with the two corresponding methods, which amounts to about a factor of two for the AGN simulations, and a factor of four for the CSF set. We also find that the inclusion of AGN feedback boosts the DSC and ICL fractions by a factor of 1.5-2, respectively, while leaving the BCG+ICL and BCG+DSC mass fraction almost unchanged. The sum of the BCG and DSC mass stellar mass fraction is found to decrease from ~80 per cent in galaxy groups to ~60 per cent in rich clusters, thus in excess of what found from observational analysis. We identify the average surface brightness limits that yields the ICL fraction from the SBL method close to the DSC fraction from the dynamical method. These surface brightness limits turn out to be brighter in the CSF than in the AGN simulations. This is consistent with the finding that AGN feedback makes BCGs to be less massive and with shallower density profiles than in the CSF simulations. The BCG stellar component, as identified by both methods, are slightly older and more metal-rich than the stars in the diffuse component.
We present a new parallel implementation of the PINpointing Orbit Crossing-Collapsed HIerarchical Objects (PINOCCHIO) algorithm, a quick tool, based on Lagrangian Perturbation Theory, for the hierarchical build-up of Dark Matter halos in cosmological
volumes. To assess its ability to predict halo correlations on large scales, we compare its results with those of an N-body simulation of a 3 Gpc/h box sampled with 2048^3 particles taken from the MICE suite, matching the same seeds for the initial conditions. Thanks to the FFTW libraries and to the relatively simple design, the code shows very good scaling properties. The CPU time required by PINOCCHIO is a tiny fraction (~1/2000) of that required by the MICE simulation. Varying some of PINOCCHIO numerical parameters allows one to produce a universal mass function that lies in the range allowed by published fits, although it underestimates the MICE mass function of FoF halos in the high mass tail. We compare the matter-halo and the halo-halo power spectra with those of the MICE simulation and find that these 2-point statistics are well recovered on large scales. In particular, when catalogs are matched in number density, agreement within ten per cent is achieved for the halo power spectrum. At scales k>0.1 h/Mpc, the inaccuracy of the Zeldovich approximation in locating halo positions causes an underestimate of the power spectrum that can be modeled as a Gaussian factor with a damping scale of d=3 Mpc/h at z=0, decreasing at higher redshift. Finally, a remarkable match is obtained for the reduced halo bispectrum, showing a good description of nonlinear halo bias. Our results demonstrate the potential of PINOCCHIO as an accurate and flexible tool for generating large ensembles of mock galaxy surveys, with interesting applications for the analysis of large galaxy redshift surveys.
