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We compare the measurements of the bispectrum and the estimate of its covariance obtained from a set of different methods for the efficient generation of approximate dark matter halo catalogues to the same quantities obtained from full N -body simulations. To this purpose we employ a large set of 300 realizations of the same cosmology for each method, run with matching initial conditions in order to reduce the contribution of cosmic variance to the comparison. In addition, we compare how the error on cosmological parameters such as linear and non-linear bias parameters depends on the approximate method used for the determination of the bispectrum variance. As general result, most methods provide errors within 10 per cent of the errors estimated from N -body simulations. Exceptions are those methods requiring calibration of the clustering amplitude but restrict this to 2-point statistics. Finally we test how our results are affected by being limited to a few hundreds measurements from N -body simulation by comparing with a larger set of several thousands of realizations performed with one approximate method. [ABSTRACT FROM AUTHOR]

We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point (power spectrum and two-point correlation function in real and redshift space), and the three-point clustering statistics (bispectrum and three-point correlation function). The reference catalogues are drawn from the BigMultiDark N-body simulation. Both friend-of-friends (including distinct haloes only) and spherical over-density (including distinct haloes and subhalos) catalogues have been used with the typical number density of a large volume galaxy surveys. We demonstrate that a proper biasing model is essential for reproducing the power spectrum at quasi-linear and even smaller scales. With respect to various clustering statistics, a methodology based on perturbation theory and a realistic biasing model leads to very good agreement with N-body simulations. However, for the quadrupole of the correlation function or the power spectrum, only the method based on semi-N-body simulation could reach high accuracy (1 per cent level) at small scales, i.e. r < 25 h-1 Mpc or k > 0.15 h Mpc-1. Full N-body solutions will remain indispensable to produce reference catalogues. Nevertheless, we have demonstrated that the more efficient approximate solvers can reach a few per cent accuracy in terms of clustering statistics at the scales interesting for the large-scale structure analysis. This makes them useful for massive production aimed at covariance studies, to scan large parameter spaces, and to estimate uncertainties in data analysis techniques, such as baryon acoustic oscillation reconstruction, redshift distortion measurements, etc. [ABSTRACT FROM AUTHOR]

We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point (power spectrum and two-point correlation function in real and redshift space), and the three-point clustering statistics (bispectrum and three-point correlation function). The reference catalogues are drawn from the BigMultiDark N-body simulation. Both friend-of-friends (including distinct haloes only) and spherical overdensity (including distinct haloes and subhalos) catalogues have been used with the typical number density of a large volume galaxy surveys. We demonstrate that a proper biasing model is essential for reproducing the power spectrum at quasi-linear and even smaller scales. With respect to various clustering statistics, a methodology based on perturbation theory and a realistic biasing model leads to very good agreement with N-body simulations. However, for the quadrupole of the correlation function or the power spectrum, only the method based on semi-N-body simulation could reach high accuracy (1 per cent level) at small scales, i.e. r < 25 h-1 Mpc or k > 0.15 h Mpc-1. Full N-body solutions will remain indispensable to produce reference catalogues. Nevertheless, we have demonstrated that the more efficient approximate solvers can reach a few per cent accuracy in terms of clustering statistics at the scales interesting for the large-scale structure analysis. This makes them useful for massive production aimed at covariance studies, to scan large parameter spaces, and to estimate uncertainties in data analysis techniques, such as baryon acoustic oscillation reconstruction, redshift distortion measurements, etc. [ABSTRACT FROM AUTHOR]