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We present forecasts for the accuracy of determining the parameters of aminimal cosmological model and the total neutrino mass based on combined mockdata for a future Euclid-like galaxy survey and Planck. We consider twodifferent galaxy surveys: a spectroscopic redshift survey and a cosmic shearsurvey. We make use of the Monte Carlo Markov Chains (MCMC) technique andassume two sets of theoretical errors. The first error is meant to account foruncertainties in the modelling of the effect of neutrinos on the non-lineargalaxy power spectrum and we assume this error to be fully correlated inFourier space. The second error is meant to parametrize the overall residualuncertainties in modelling the non-linear galaxy power spectrum at smallscales, and is conservatively assumed to be uncorrelated and to increase withthe ratio of a given scale to the scale of non-linearity. It hence increaseswith wavenumber and decreases with redshift. With these two assumptions for theerrors and assuming further conservatively that the uncorrelated error risesabove 2% at k = 0.4 h/Mpc and z = 0.5, we find that a future Euclid-like cosmicshear/galaxy survey achieves a 1-sigma error on Mnu close to 32 meV/25 meV,sufficient for detecting the total neutrino mass with good significance. If theresidual uncorrelated errors indeed rises rapidly towards smaller scales in thenon-linear regime as we have assumed here then the data on non-linear scalesdoes not increase the sensitivity to the total neutrino mass. Assuming insteada ten times smaller theoretical error with the same scale dependence, the erroron the total neutrino mass decreases moderately from sigma(Mnu) = 18 meV to 14meV when mildly non-linear scales with 0.1 h/Mpc < k < 0.6 h/Mpc are includedin the analysis of the galaxy survey data.

Neutrino masses and cosmological parameters from a Euclid-like survey: Markov Chain Monte Carlo forecasts including theoretical errors