Removing Imaging Systematics from Galaxy Clustering Measurements with
  Obiwan : Application to the SDSS-IV extended Baryon Oscillation Spectroscopic
  Survey Emission Line Galaxy Sample
  This work presents the application of a new tool, Obiwan , which uses image
simulations to determine the selection function of a galaxy redshift survey and
calculate 3-dimensional (3D) clustering statistics. This is a forward model of
the process by which images of the night sky are transformed into a 3D
large--scale structure catalog. The photometric pipeline automatically detects
and models galaxies and then generates a catalog of such galaxies with detailed
information for each one of them, including their location, redshift and so on.
Systematic biases in the imaging data are therefore imparted into the catalogs
and must be accounted for in any scientific analysis of their information
content.
  Obiwan simulates this process for samples selected from the Legacy Surveys
imaging data. This imaging data will be used to select target samples for the
next-generation Dark Energy Spectroscopic Instrument (DESI) experiment. Here,
we apply Obiwan to a portion of the SDSS-IV extend Baryon Oscillation
Spectroscopic Survey Emission Line Galaxies (ELG) sample. Systematic biases in
the data are clearly identified and removed. We compare the 3D clustering
results to those obtained by the map--based approach applied to the full eBOSS
sample. We find the results are consistent, thereby validating the eBOSS ELG
catalogs, presented in Raichoor(2020), used to obtain cosmological results.
