Extending the modeling of the anisotropic galaxy power spectrum to $k=0.4h{\mathrm{Mpc}}^{-1}$

Abstract

We present a new model for the redshift-space power spectrum of galaxies and demonstrate its accuracy in modeling the monopole, quadrupole, and hexadecapole of the galaxy density field down to scales of $k=0.4h{\mathrm{Mpc}}^{-1}$. The model describes the clustering of galaxies in the context of a halo model and the clustering of the underlying halos in redshift space using a combination of Eulerian perturbation theory and $N$-body simulations. The modeling of redshift-space distortions is done using the so-called distribution function approach. The final model has 13 free parameters, and each parameter is physically motivated rather than a nuisance parameter, which allows the use of well-motivated priors. We account for the Finger-of-God effect from centrals and both isolated and non-isolated satellites rather than using a single velocity dispersion to describe the combined effect. We test and validate the accuracy of the model on several sets of high-fidelity $N$-body simulations, as well as realistic mock catalogs designed to simulate the BOSS DR12 CMASS data set. The suite of simulations covers a range of cosmologies and galaxy bias models, providing a rigorous test of the level of theoretical systematics present in the model. The level of bias in the recovered values of $f{\sigma }_8$ is found to be small. When including scales to $k=0.4h{\mathrm{Mpc}}^{-1}$, we find 15-30\% gains in the statistical precision of $f{\sigma }_8$ relative to $k=0.2h{\mathrm{Mpc}}^{-1}$ and a roughly 10-15\% improvement for the perpendicular Alcock-Paczynski parameter ${\alpha }_{\perp }$. Using the BOSS DR12 CMASS mocks as a benchmark for comparison, we estimate an uncertainty on $f{\sigma }_8$ that is $\sim$10-20\% larger than other similar Fourier-space RSD models in the literature that use $k\le 0.2h{\mathrm{Mpc}}^{-1}$, suggesting that these models likely have a too-limited parametrization.

Submitted to JCAP

Cited by in corpus (28)

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