Extended fast action minimization method: application to SDSS-DR12 combined sample

Abstract

ABSTRACT We present the first application of the extended Fast Action Minimization method (eFAM) to a real data set, the SDSS-DR12 Combined Sample, to reconstruct galaxies orbits back-in-time, their two-point correlation function (2PCF) in real-space, and enhance the baryon acoustic oscillation (BAO) peak. For this purpose, we introduce a new implementation of eFAM that accounts for selection effects, survey footprint, and galaxy bias. We use the reconstructed BAO peak to measure the angular diameter distance, $D_\mathrm{A}(z)r^\mathrm{fid}_\mathrm{s}/r_\mathrm{s}$, and the Hubble parameter, $H(z)r_\mathrm{s}/r^\mathrm{fid}_\mathrm{s}$, normalized to the sound horizon scale for a fiducial cosmology $r^\mathrm{fid}_\mathrm{s}$, at the mean redshift of the sample z = 0.38, obtaining $D_\mathrm{A}(z=0.38)r^\mathrm{fid}_\mathrm{s}/r_\mathrm{s}=1090\pm 29$(Mpc)−1, and $H(z=0.38)r_\mathrm{s}/r^\mathrm{fid}_\mathrm{s}=83\pm 3$(km s−1 Mpc−1), in agreement with previous measurements on the same data set. The validation tests, performed using 400 publicly available SDSS-DR12 mock catalogues, reveal that eFAM performs well in reconstructing the 2PCF down to separations of ∼25h−1Mpc, i.e. well into the non-linear regime. Besides, eFAM successfully removes the anisotropies due to redshift-space distortion (RSD) at all redshifts including that of the survey, allowing us to decrease the number of free parameters in the model and fit the full-shape of the back-in-time reconstructed 2PCF well beyond the BAO peak. Recovering the real-space 2PCF, eFAM improves the precision on the estimates of the fitting parameters. When compared with the no-reconstruction case, eFAM reduces the uncertainty of the Alcock-Paczynski distortion parameters α⊥ and α∥ of about 40 per cent and that on the non-linear damping scale Σ∥ of about 70 per cent. These results show that eFAM can be successfully applied to existing redshift galaxy catalogues and should be considered as a reconstruction tool for next-generation surveys alternative to popular methods based on the Zel’dovich approximation.