Mind the gap: the power of combining photometric surveys with intensity mapping

TL;DR

This paper demonstrates that combining photometric and spectroscopic galaxy surveys with 21-cm intensity mapping enhances the recovery of large-scale modes and improves initial density field reconstruction, leveraging non-linear gravitational coupling.

Contribution

It introduces a method to improve large-scale mode recovery in 21-cm surveys by integrating external galaxy data, highlighting the benefits of survey synergy and the importance of smoothing in bias modeling.

Findings

Galaxy data improves large-scale mode reconstruction over 21-cm alone.

Spectroscopic samples outperform photometric ones despite lower density.

Combined surveys yield better initial density field reconstruction.

Abstract

The long wavelength modes lost to bright foregrounds in the interferometric 21-cm surveys can partially be recovered using a forward modeling approach that exploits the non-linear coupling between small and large scales induced by gravitational evolution. In this work, we build upon this approach by considering how adding external galaxy distribution data can help to fill in these modes. We consider supplementing the 21-cm data at two different redshifts with a spectroscopic sample (good radial resolution but low number density) loosely modeled on DESI-ELG at $z=1$ and a photometric sample (high number density but poor radial resolution) similar to LSST sample at $z=1$ and $z=4$ respectively. We find that both the galaxy samples are able to reconstruct the largest modes better than only using 21-cm data, with the spectroscopic sample performing significantly better than the photometric sample despite much lower number density. We demonstrate the synergies between surveys by showing that the primordial initial density field is reconstructed better with the combination of surveys than using either of them individually. Methodologically, we also explore the importance of smoothing the density field when using bias models to forward model these tracers for reconstruction.