http://arxiv.org/abs/1704.06634
Motivated by recent developments in perturbative calculations of the nonlinear evolution of large-scale structure, we present an iterative algorithm to reconstruct the initial conditions in a given volume starting from the dark matter distribution in real space. In our algorithm, objects are first iteratively moved back along estimated potential gradients until a nearly uniform catalog is obtained. The linear initial density is then estimated as the divergence of the cumulative displacement, with an optional second-order correction. This algorithm should undo non-linear effects up to one-loop order, including the higher-order infrared resummation piece. We test the method using dark matter simulations in real space. At redshift $z=0$, we find that after eight iterations the reconstructed density is more than $95\%$ correlated with the initial density at $k\le 0.35\; h\mathrm{Mpc}^{-1}$. The reconstruction also reduces the power in the difference between reconstructed and initial fields by more than two orders of magnitude at $k\le 0.2\; h\mathrm{Mpc}^{-1}$, and it extends the range of scales where the full broad-band shape of the power spectrum matches linear theory by a factor 2-3. As a specific application, we consider measurements of the Baryonic Acoustic Oscillation (BAO) scale that can be improved by reducing the degradation effects of large-scale flows. We find that the method improves the BAO signal-to-noise by a factor 2.7 at redshift $z=0$ and by a factor 2.5 at $z=0.6$ in our idealistic simulations. This improves standard BAO reconstruction by $70\%$ at $z=0$ and $30\%$ at $z=0.6$, and matches the optimal BAO signal and signal-to-noise of the linear density in the same volume.
M. Schmittfull, T. Baldauf and M. Zaldarriaga
Mon, 24 Apr 17
52/54
Comments: 26 pages, 14 figures, comments welcome