Astronomy and Astrophysics – Astrophysics
Scientific paper
2008-08-21
Astrophys.J.698:967-985,2009
Astronomy and Astrophysics
Astrophysics
19 pages, 15 figures, submitted to The Astrophysical Journal
Scientific paper
10.1088/0004-637X/698/2/967
The shape of the primordial matter power spectrum Plin(k) encodes critical information on cosmological parameters. At large scales, the observable galaxy power spectrum Pobs(k) is expected to follow the shape of Plin(k), but on smaller scales the effects of nonlinearity and galaxy bias make the ratio Pobs(k)/Plin(k) scale-dependent. We develop a method that can extend the dynamic range of the Plin(k) recovery by incorporating constraints on the galaxy halo occupation distribution (HOD) from the projected galaxy correlation function wp. We devise an analytic model to calculate Pobs(k) in real-space and redshift-space. Once HOD parameters are determined by matching wp for a given cosmological model, galaxy bias is completely specified, and our analytic model predicts both the shape and normalization of Pobs(k). Applying our method to SDSS main galaxy samples, we find that the real-space Pobs(k) follows the shape of the nonlinear matter power spectrum at the 1-2% level up to k=0.2 h/Mpc. When we apply our method to SDSS LRG samples, the linear bias approximation is accurate to 5% at k<0.08 h/Mpc, but the scale-dependence of LRG bias prevents the use of linear theory at k>0.08 h/Mpc. Our HOD model prediction is in good agreement with the recent SDSS LRG Pobs(k) measurements at all measured scales (k<0.2 h/Mpc), naturally explaining the shape of Pobs(k). The "Q-model" prescription is a poor description of galaxy bias for the LRG samples, and it can lead to biased cosmological parameter estimates when measurements at k>0.1 h/Mpc are included in the analysis. We quantify the potential bias and constraints on cosmological parameters that arise from applying linear theory and Q-model fitting, and we demonstrate the utility of HOD modeling of future high precision measurements of Pobs(k) on quasi-linear scales.
Tinker Jeremy L.
Warren Michael S.
Weinberg David H.
Yoo Jaiyul
Zheng Zheng
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