Journal
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 465, Issue 4, Pages 4658-4677Publisher
OXFORD UNIV PRESS
DOI: 10.1093/mnras/stw3085
Keywords
methods: numerical; surveys; cosmology: theory; dark matter
Categories
Funding
- Consorzio per la Fisica di Trieste
- PRIN MIUR [J91J12000450001, 01278X4FL]
- University of Trieste
- PRIN-INAF
- F.R.A. grant by the University of Trieste
- 'InDark' INFN Grant
- Department of Energy [de-sc0009946]
- NSF-AST [0908241]
Ask authors/readers for more resources
We present the latest version of PINOCCHIO, a code that generates catalogues of dark matter haloes in an approximate but fast way with respect to an N-body simulation. This code version implements a new on-the-fly production of halo catalogue on the past light cone with continuous time sampling, and the computation of particle and halo displacements are extended up to third-order Lagrangian perturbation theory (LPT), in contrast with previous versions that used Zel'dovich approximation. We run PINOCCHIO on the same initial configuration of a reference N-body simulation, so that the comparison extends to the object-by-object level. We consider haloes at redshifts 0 and 1, using different LPT orders either for halo construction or to compute halo final positions. We compare the clustering properties of PINOCCHIO haloes with those from the simulation by computing the power spectrum and two-point correlation function in real and redshift space (monopole and quadrupole), the bispectrum and the phase difference of halo distributions. We find that 2LPT and 3LPT give noticeable improvement. 3LPT provides the best agreement with N-body when it is used to displace haloes, while 2LPT gives better results for constructing haloes. At the highest orders, linear bias is typically recovered at a few per cent level. In Fourier space and using 3LPT for halo displacements, the halo power spectrum is recovered to within 10 per cent up to k(max) similar to 0.5 h Mpc(-1). The results presented in this paper have interesting implications for the generation of large ensemble of mock surveys for the scientific exploitation of data from big surveys.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available