  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.
