The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: N-body Mock Challenge for the eBOSS Emission Line Galaxy Sample
astro-ph.CO
/ Authors
Shadab Alam, Arnaud de Mattia, Amélie Tamone, S. Ávila, John A. Peacock, V. Gonzalez-Perez, Alex Smith, Anand Raichoor, Ashley J. Ross, Julian E. Bautista
and 20 more authors
Etienne Burtin, Johan Comparat, Kyle S. Dawson, Hélion du Mas des Bourboux, Stéphanie Escoffier, Héctor Gil-Marín, Salman Habib, Katrin Heitmann, Jiamin Hou, Faizan G. Mohammad, Eva-Maria Mueller, Richard Neveux, Romain Paviot, Will J. Percival, Graziano Rossi, Vanina Ruhlmann-Kleider, Rita Tojeiro, Mariana Vargas Magaña, Cheng Zhao, Gong-Bo Zhao
/ Abstract
Cosmological growth can be measured in the redshift space clustering of galaxies targeted by spectroscopic surveys. Accurate prediction of clustering of galaxies will require understanding galaxy physics which is a very hard and highly non-linear problem. Approximate models of redshift space distortion (RSD) take a perturbative approach to solve the evolution of dark matter and galaxies in the universe. In this paper we focus on eBOSS emission line galaxies (ELGs) which live in intermediate mass haloes. We create a series of mock catalogues using haloes from the Multidark and {\sc Outer Rim} dark matter only N-body simulations. Our mock catalogues include various effects inspired by baryonic physics such as assembly bias and the characteristics of satellite galaxies kinematics, dynamics and statistics deviating from dark matter particles. We analyse these mocks using the TNS RSD model in Fourier space and the CLPT in configuration space. We conclude that these two RSD models provide an unbiased measurement of redshift space distortion within the statistical error of our mocks. We obtain the conservative theoretical systematic uncertainty of $3.3\%$, $1.8\%$ and $1.5\%$ in $fσ_8$, $α_{\parallel}$ and $α_{\bot}$ respectively for the TNS and CLPT models. We note that the estimated theoretical systematic error is an order of magnitude smaller than the statistical error of the eBOSS ELG sample and hence are negligible for the purpose of the current eBOSS ELG analysis.