Precision redshift-space galaxy power spectra using Zel'dovich control variates

Numerical simulations in cosmology require trade-offs between volume, resolution and run-time that limit the volume of Universe can be simulated, leading to sample variance predictions ensemble-average quantities such as power spectrum or correlation function(s). Sample is particularly acute at large scales, which also where analytic techniques highly reliable. This provides an opportunity combine numerical a principled way improve dynamic range reliability for clustering statistics. In this paper we extend technique Zel'dovich control variates, previously demonstrated 2-point functions real space, reduce measurements statistics biased tracers redshift space. We demonstrate with technique, these down their shot-noise out $k \sim 0.2\, h\rm Mpc^{-1}$. allows better matching perturbative models improved e.g.~quasars, galaxies neutral Hydrogen measured spectroscopic surveys very modest computational expense. discuss implementation ZCV, give some examples provide forecasts efficacy method under various conditions.