On the impact of the galaxy window function on cosmological parameter estimation

Understand

One important source of systematics in galaxy redshift surveys comes from the estimation of the galaxy window function.

• Up until now, the impact of the uncertainty in estimating the galaxy window function on parameter inference has not been properly studied.
• In this paper, we show that the uncertainty and the bias in estimating the galaxy window function will be salient for ongoing and next-generation galaxy surveys using a simulation-based approach.
• With a specific case study of cross-correlating Emission-line galaxies from the DESI Legacy Imaging Surveys and the Planck CMB lensing map, we show that neural network-based regression approaches to modelling the window function are superior in comparison to linear regression-based models.