Forecasts on neutrino mass constraints from the redshift-space two-point correlation function

We provide constraints on the accuracy with which the neutrino mass fraction, f\u3bd, can be estimated when exploiting measurements of redshift-space distortions, describing in particular how the error on neutrino mass depends on three fundamental parameters of a characteristic galaxy redshift survey: density, halo bias and volume. In doing this, we make use of a series of dark matter halo catalogues extracted from the BASICC simulation. The mock data are analysed via a Markov Chain Monte Carlo likelihood analysis. We find a fitting function that well describes the dependence of the error on bias, density and volume, showing a decrease in the error as the bias and volume increase, and a decrease with density down to an almost constant value for high-density values. This fitting formula allows us to produce forecasts on the precision achievable with future surveys on measurements of the neutrino mass fraction. For example, a Euclid-like spectroscopic survey should be able to measure the neutrino mass fraction with an accuracy of \u3b4f\u3bd 48 3.1 7 10-3 (which is equivalent to \u3b4 11m\u3bd 48 0.039eV), using redshift-space clustering once all the other cosmological parameters are kept fixed to the \u39bCDM case