A 2% Distance to z=0.35 by Reconstructing Baryon Acoustic Oscillations -   I : Methods and Application to the Sloan Digital Sky Survey
  We apply the reconstruction technique to the clustering of galaxies from the SDSS DR7 LRG sample, sharpening the baryon acoustic oscillation (BAO) feature and achieving a 1.9% measurement of the distance to z=0.35. This is the first application of reconstruction of the BAO feature in a galaxy redshift survey. We update the reconstruction algorithm of Eisenstein et al, 2007 to account for the effects of survey geometry as well as redshift-space distortions and validate it on 160 LasDamas simulations. We demonstrate that reconstruction sharpens the BAO feature in the angle averaged galaxy correlation function, reducing the nonlinear smoothing scale \Sigma_nl from 8.1 Mpc/h to 4.4 Mpc/h. Reconstruction also significantly reduces the effects of redshift-space distortions at the BAO scale, isotropizing the correlation function. This sharpened BAO feature yields an unbiased distance estimate (< 0.2%) and reduces the scatter from 3.3% to 2.1%. We demonstrate the robustness of these results to the various reconstruction parameters, including the smoothing scale, the galaxy bias and the linear growth rate. Applying this reconstruction algorithm to the SDSS LRG DR7 sample improves the significance of the BAO feature in these data from 3.3 sigma for the unreconstructed correlation function, to 4.2 sigma after reconstruction. We estimate a relative distance scale D_V/r_s to z=0.35 of 8.88+/-0.17, where r_s is the sound horizon and D_V = (D_A^2/H)^{1/3} is a combination of the angular diameter distance D_A and Hubble parameter H. Assuming a sound horizon of 154.25 Mpc, this translates into a distance measurement D_V (z=0.35) = 1.356+/-0.025 Gpc. We find that reconstruction reduces the distance error in the DR7 sample from 3.5% to 1.9%, equivalent to a survey with three times the volume of SDSS. 
Nikhil Padmanabhan, Xiaoying Xu, Daniel J. Eisenstein, Richard Scalzo,   Antonio J. Cuesta, Kushal T. Mehta, Eyal Kazin
astro-ph.CO