Synergies between the COMAP CO Line Intensity Mapping mission and a Ly{\alpha} galaxy survey: How to probe the early universe with voxel based analysis of observational data

Line Intensity Mapping (LIM) offers a novel avenue to observe and characterize our universe. LIM data of CO spectral lines are becoming available, such as those obtained by the CO Mapping Array Project (COMAP). COMAP data can be used to probe the molecular gas content of the universe from the last stages of the Epoch of Reionization (EoR) ($z < 8.0$) to $z \sim 2.5$. In this work, we examine the prospects for deriving voxel-level statistical constraints on high-redshift galaxies from COMAP data by considering the additional information available from observations of LAEs galaxies using the Visible Integral-Field Replicable Unit Spectrograph (VIRUS) on the Hobby-Eberly Telescope (HET). We post-process the IllustrisTNG300 galaxy-formation simulation with a set of prescriptions to consistently determine CO and Ly$\alpha$ line luminosities. The different line prescriptions span the uncertainty in the CO line luminosity according to current observations by the VLA high-z CO surveys and set the Ly$\alpha$ emission to be compatible with observational LAE luminosity functions. We produce mock observations for the two surveys over a $(300\, {\rm Mpc})^3$ volume. These are then used to formulate and test methodologies for data analysis and to predict COMAP constraints on CO emission. We use combinations of masking, stacking, voxel intensity distribution (VID), and other statistics. We find that in combination with VIRUS/HET, a voxel-level analysis of the COMAP Pathfinder survey can detect and characterize the CO signal from $z\sim3$ and improve current constraints on the $z\sim6$ signal, identify individual voxels with bright CO(1-0) emission at $z\sim3$ and probe the redshift evolution of the CO emission. This study illustrates the potential of synergies between LIM and galaxy surveys both to improve the significance of a detection and to aid the interpretation of noisy LIM data.