Linear bias forecasts for emission line cosmological surveys

We forecast the linear bias for H${\rm \alpha}$-emitting galaxies at high redshift. To simulate a Euclid-like and a WFIRST-like survey, we place galaxies into a large-volume dark matter halo lightcone by sampling a library of luminosity-dependent halo occupation distributions (HODs), which is constructed using a physically motivated galaxy formation model. We calibrate the dust attenuation in the lightcones such that they are able to reproduce the H{\alpha} luminosity function or the H{\alpha} cumulative number counts. The angle-averaged galaxy correlation function is computed for each survey in redshift slices of width $\Delta z = 0.2$. In each redshift bin the linear bias can be fitted with a single, scale-independent value that increases with increasing redshift. Fitting for the evolution of linear bias with redshift, we find that our Euclid-like and WFIRST-like surveys are both consistent within error with the relation $b(z) = 0.7z + 0.7$. Our bias forecasts are consistent with bias measurements from the HiZELS survey. We find that the Euclid-like and WFIRST-like surveys yield linear biases that are broadly consistent within error, most likely due to the HOD for the WFIRST-like survey having a steeper power-law slope towards larger halo masses.