We analyse the flux power spectrum and its covariance using simulated Lyα forests. We find that pseudo-hydro techniques are good approximations of hydrodynamical simulations at high redshift. However, the pseudo-hydro techniques fail at low redshift because they are insufficient for characterizing some components of the low-redshift intergalactic medium, notably the warm-hot intergalactic medium. Hence, to use the low-redshift Lyα flux power spectrum to constrain cosmology, one would need realistic hydrodynamical simulations. By comparing (one-dimensional) mass statistics with flux statistics, we show that the non-linear transform between density and flux quenches the fluctuations so that the flux power spectrum is much less sensitive to cosmological parameters than the one-dimensional mass power spectrum. The covariance of the flux power spectrum is nearly Gaussian. As such, the uncertainties of the underlying mass power spectrum could still be large, even though the flux power spectrum can be precisely determined from a small number of lines of sight.
With the largest spectroscopic galaxy survey volume drawn from the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS), we can extract cosmological constraints from the measurements of redshift and geometric distortions at quasi-linear scales (e.g. above 50 h−1 Mpc). We analyse the broad-range shape of the monopole and quadrupole correlation functions of the BOSS Data Release 12 (DR12) CMASS galaxy sample, at the effective redshift z = 0.59, to obtain constraints on the Hubble expansion rate H(z), the angular- diameter distance DA(z), the normalized growth rate f(z)σ8(z), and the physical matter density Ωm h2. We obtain robust measurements by including a polynomial as the model for the systematic errors, and find it works very well against the systematic effects, e.g. ones induced by stars and seeing. We provide accurate measurements {DA(0.59)rs,fid/rs, H(0.59)rs/rs,fid, f(0.59)σ8(0.59), Ωm h2} = {1427 ± 26 Mpc, 97.3 ± 3.3 km s−1 Mpc−1, 0.488 ± 0.060, 0.135 ± 0.016}, where rs is the comoving sound horizon at the drag epoch and rs,fid = 147.66 Mpc is the sound scale of the fiducial cosmology used in this study. The parameters which are not well constrained by our galaxy clustering analysis are marginalized over with wide flat priors. Since no priors from other data sets, e.g. cosmic microwave background (CMB), are adopted and no dark energy models are assumed, our results from BOSS CMASS galaxy clustering alone may be combined with other data sets, i.e. CMB, SNe, lensing or other galaxy clustering data to constrain the parameters of a given cosmological model. The uncertainty on the dark energy equation of state parameter, w, from CMB+CMASS is about 8 per cent. The uncertainty on the curvature fraction, Ωk, is 0.3 per cent. We do not find deviation from flat ΛCDM.
Extraction of the Baryon Acoustic Oscillations (BAO) to percent level accuracy is challenging and demands an understanding of many potential systematic to an accuracy well below 1 per cent, in order ensure that they do not combine significantly when compared to statistical error of the BAO measurement. Sloan Digital Sky Survey (SDSS)-III Baryon Oscillation Spectroscopic Survey (BOSS) SDSS Data Release Eleven (DR11) reaches a distance measurement with $\sim 1\%$ statistical error and this prompts an extensive search for all possible sub-percent level systematic errors which could be safely ignored previously. In this paper, we analyze the potential systematics in BAO fitting methodology using mocks and data from BOSS DR10 and DR11. We demonstrate the robustness of the fiducial multipole fitting methodology to be at $0.1\%-0.2\%$ level with a wide range of tests in mock galaxy catalogs pre- and post-reconstruction. We also find the DR10 and DR11 data from BOSS to be robust against changes in methodology at similar level. This systematic error budget is incorporated into the the error budget of Baryon Oscillation Spectroscopic Survey (BOSS) DR10 and DR11 BAO measurements. Of the wide range of changes we have investigated, we find that when fitting pre-reconstructed data or mocks, the following changes have the largest effect on the best fit values of distance measurements both parallel and perpendicular to the line of sight: (a) Changes in non-linear correlation function template; (b) Changes in fitting range of the correlation function; (c) Changes to the non-linear damping model parameters. The priors applied do not matter in the estimates of the fitted errors as long as we restrict ourselves to physically meaningful fitting regions.[abridged]