Abstract We forecast the future constraints on scale-dependent parametrizations of galaxy bias and their impact on the estimate of cosmological parameters from the power spectrum of galaxies measured in a spectroscopic redshift survey. For the latter we assume a wide survey at relatively large redshifts, similar to the planned Euclid survey, as the baseline for future experiments. To assess the impact of the bias we perform a Fisher matrix analysis, and we adopt two different parametrizations of scale-dependent bias. The fiducial models for galaxy bias are calibrated using mock catalogs of H α emitting galaxies mimicking the expected properties of the objects that will be targeted by the Euclid survey. In our analysis we have obtained two main results. First of all, allowing for a scale-dependent bias does not significantly increase the errors on the other cosmological parameters apart from the rms amplitude of density fluctuations, σ8 , and the growth index γ , whose uncertainties increase by a factor up to 2, depending on the bias model adopted. Second, we find that the accuracy in the linear bias parameter b0 can be estimated to within 1%-2% at various redshifts regardless of the fiducial model. The nonlinear bias parameters have significantly large errors that depend on the model adopted. Despite this, in the more realistic scenarios departures from the simple linear bias prescription can be detected with a ˜2 σ significance at each redshift explored. Finally, we use the Fisher matrix formalism to assess the impact od assuming an incorrect bias model and find that the systematic errors induced on the cosmological parameters are similar or even larger than the statistical ones.
Amendola, L., Menegoni, E., Di Porto, C., Corsi, M., & Branchini, E. (2017). Constraints on a scale-dependent bias from galaxy clustering. PHYSICAL REVIEW D, 95(2).
|Titolo:||Constraints on a scale-dependent bias from galaxy clustering|
|Data di pubblicazione:||2017|
|Citazione:||Amendola, L., Menegoni, E., Di Porto, C., Corsi, M., & Branchini, E. (2017). Constraints on a scale-dependent bias from galaxy clustering. PHYSICAL REVIEW D, 95(2).|
|Appare nelle tipologie:||1.1 Articolo in rivista|