A Prescription for Galaxy Biasing Evolution as a Nuisance Parameter

There is currently no consistent approach to modelling galaxy bias evolution in cosmological inference. This lack of a common standard makes the rigorous comparison or combination of probes difficult. We show that the choice of biasing model has a significant impact on cosmological parameter constraints for a survey such as the Dark Energy Survey (DES), considering the 2-point correlations of galaxies in five tomographic redshift bins. We find that modelling galaxy bias with a free biasing parameter per redshift bin gives a Figure of Merit (FoM) for Dark Energy equation of state parameters w_0, w_a smaller by a factor of 10 than if a constant bias is assumed. An incorrect bias model will also cause a shift in measured values of cosmological parameters. Motivated by these points and focusing on the redshift evolution of linear bias, we propose the use of a generalised galaxy bias which encompasses a range of bias models from theory, observations and simulations, b(z) = c + (b_0 - c)/D(z)^alpha, where parameters c, b_0 and alpha depend on galaxy properties such as halo mass. For a DES-like galaxy survey we find that this model gives an unbiased estimate of w_0, w_a with the same number or fewer nuisance parameters and a higher FoM than a simple b(z) model allowed to vary in z-bins. We show how the parameters of this model are correlated with cosmological parameters. We fit a range of bias models to two recent datasets, and conclude that this generalised parameterisation is a sensible benchmark expression of galaxy bias on large scales.