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We present the nonlinear 2D galaxy power spectrum, $P(k,\mu)$, in redshiftspace, measured from the Dark Sky simulations, using galaxy catalogsconstructed with both halo occupation distribution and subhalo abundancematching methods, chosen to represent an intermediate redshift sample ofluminous red galaxies. We find that the information content in individual $\mu$(cosine of the angle to the line of sight) bins is substantially richer thenmultipole moments, and show that this can be used to isolate the impact ofnonlinear growth and redshift space distortion (RSD) effects. Using the$\mu<0.2$ simulation data, which we show is not impacted by RSD effects, we cansuccessfully measure the nonlinear bias to an accuracy of $\sim 5$% at $k<0.6h$Mpc$^{-1}$. This use of individual $\mu $ bins to extract the nonlinear biassuccessfully removes a large parameter degeneracy when constraining the lineargrowth rate of structure. We carry out a joint parameter estimation, using thelow $\mu$ simulation data to constrain the nonlinear bias, and $\mu\ge0.2$ toconstrain 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 usinga simple dispersion model, for a range of galaxy models. Our analysis ofindividual $\mu $ bins also reveals interesting physical effects which arisesimply from different methods of populating halos with galaxies. We find aprominent turnaround scale, at which RSD damping effects are greater then thenonlinear growth, which differs not only for each $\mu$ bin but also for eachgalaxy model. These features may provide unique signatures which could be usedto shed light on the galaxy-dark matter connection.

Disentangling redshift-space distortions and nonlinear bias using the 2D power spectrum