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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.
We present an accurate and fast framework for generating mock catalogues including low-mass halos, based on an implementation of the COmoving Lagrangian Acceleration (COLA) technique. Multiple realisations of mock catalogues are crucial for analyses
We investigate the correlation between nine different dark matter halo properties using a rank correlation analysis and a Principal Component Analysis for a sample of haloes spanning five orders of magnitude in mass. We consider mass and dimensionles
We perform an ensemble of $N$-body simulations with $2048^3$ particles for 101 flat $w$CDM cosmological models sampled based on a maximin-distance Sliced Latin Hypercube Design. By using the halo catalogs extracted at multiple redshifts in the range
Cross-correlating gamma-ray maps with locations of galaxies in the low-redshift Universe vastly increases sensitivity to signatures of annihilation of dark matter particles. Low-redshift galaxies are ideal targets, as the largest contribution to anis
We present a study of unprecedented statistical power regarding the halo-to-halo variance of dark matter substructure. Using a combination of N-body simulations and a semi-analytical model, we investigate the variance in subhalo mass fractions and su