Generating Log-Normal Mock Catalog of Galaxies in Redshift Space
Abstract
We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear bias relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.
Recommended Citation
A. Agrawal et al., "Generating Log-Normal Mock Catalog of Galaxies in Redshift Space," Journal of Cosmology and Astroparticle Physics, vol. 2017, no. 10, Institute of Physics - IOP Publishing, Oct 2017.
The definitive version is available at https://doi.org/10.1088/1475-7516/2017/10/003
Department(s)
Physics
Keywords and Phrases
cosmological simulations; dark matter simulations; power spectrum; redshift surveys
International Standard Serial Number (ISSN)
1475-7516
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Institute of Physics - IOP Publishing, All rights reserved.
Publication Date
01 Oct 2017