Disentangling redshift-space distortions and nonlinear bias using the 2D
  power spectrum
  We present the nonlinear 2D galaxy power spectrum, $P(k,\mu)$, in redshift
space, measured from the Dark Sky simulations, using galaxy catalogs
constructed with both halo occupation distribution and subhalo abundance
matching methods, chosen to represent an intermediate redshift sample of
luminous red galaxies. We find that the information content in individual $\mu$
(cosine of the angle to the line of sight) bins is substantially richer then
multipole moments, and show that this can be used to isolate the impact of
nonlinear growth and redshift space distortion (RSD) effects. Using the
$\mu<0.2$ simulation data, which we show is not impacted by RSD effects, we can
successfully measure the nonlinear bias to an accuracy of $\sim 5$% at $k<0.6
h$Mpc$^{-1}$. This use of individual $\mu $ bins to extract the nonlinear bias
successfully removes a large parameter degeneracy when constraining the linear
growth rate of structure. We carry out a joint parameter estimation, using the
low $\mu$ simulation data to constrain the nonlinear bias, and $\mu\ge0.2$ to
constrain the growth rate and show that $f$ can be constrained to $\sim 26\,
(22)$% to a $k_{\rm max}< 0.4\, (0.6) h$Mpc$^{-1}$ from clustering alone using
a simple dispersion model, for a range of galaxy models. Our analysis of
individual $\mu $ bins also reveals interesting physical effects which arise
simply from different methods of populating halos with galaxies. We find a
prominent turnaround scale, at which RSD damping effects are greater then the
nonlinear growth, which differs not only for each $\mu$ bin but also for each
galaxy model. These features may provide unique signatures which could be used
to shed light on the galaxy-dark matter connection.
