1. nIFTy Cosmology: Galaxy/halo mock catalogue comparison project on clustering statistics
- Author
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Chuang, Chia-Hsun, Zhao, Cheng, Prada, Francisco, Munari, Emiliano, Avila, Santiago, Izard, Albert, Kitaura, Francisco-Shu, Manera, Marc, Monaco, Pierluigi, Murray, Steven, Knebe, Alexander, Scoccola, Claudia G., Yepes, Gustavo, Garcia-Bellido, Juan, Marin, Felipe A., Muller, Volker, Skibba, Ramin, Crocce, Martin, Fosalba, Pablo, Gottlober, Stefan, Klypin, Anatoly A., Power, Chris, Tao, Charling, and Turchaninov, Victor
- Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point and the three-point clustering statistics. The reference catalogues are drawn from the BigMultiDark N-body simulation. Both friend-of-friends (including distinct halos only) and spherical overdensity (including distinct halos and subhalos) catalogs 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 quasilinear 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% level) at small scales, i.e., r<25 Mpc/h or k>0.15 h/Mpc. Full N-body solutions will remain indispensable to produce reference catalogues. Nevertheless, we have demonstrated that the far more efficient approximate solvers can reach a few percent accuracy in terms of clustering statistics at the scales interesting for the large-scale structure analysis after calibration with a few reference N-body calculations. 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., Comment: 16 pages, 15 figures; matches the version accepted by MNRAS; a bug in PINOCCHIO code has been fixed; no major modification from previous version
- Published
- 2014
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