Measuring H0 from the 6dF Galaxy Survey and future low-redshift surveys

Baryon acoustic oscillations (BAO) at low redshift provide a precise and largely model-independent way to measure the Hubble constant, H0. The 6dF Galaxy Survey measurement of the BAO scale gives a value of H0 = 67 +/- 3.2 km/s/Mpc, achieving a 1-sigma precision of 5%. With improved analysis techniques, the planned WALLABY (HI) and TAIPAN (optical) redshift surveys are predicted to measure H0 to 1-3% precision.Comment: Proceedings of IAU Symposium 289, "Advancing the Physics of Cosmic Distances", Richard de Grijs & Giuseppe Bono (eds), 2012, 4p

Constraining the relative velocity effect using the Baryon Oscillation Spectroscopic Survey

We analyse the power spectrum of the Baryon Oscillation Spectroscopic Survey (BOSS), Data Release 12 (DR12) to constrain the relative velocity effect, which represents a potential systematic for measurements of the Baryon Acoustic Oscillation (BAO) scale. The relative velocity effect is sourced by the different evolution of baryon and cold dark matter perturbations before decoupling. Our power spectrum model includes all $1$-loop redshift-space terms corresponding to $v_{\rm bc}$ parameterised by the bias parameter $b_{v^2}$. We also include the linear terms proportional to the relative density, $\delta_{\rm bc}$, and relative velocity dispersion, $\theta_{\rm bc}$, which we parameterise with the bias parameters $b^{\rm bc}_{\delta}$ and $b^{\rm bc}_{\theta}$. Our data does not support a detection of the relative velocity effect in any of these parameters. Combining the low and high redshift bins of BOSS, we find limits of $b_{v^2} = 0.012 \pm 0.015\;(\pm 0.031)$, $b^{\rm bc}_{\delta} = -1.0 \pm 2.5\;(\pm 6.2)$ and $b^{\rm bc}_{\theta} = -114 \pm 55\;(\pm 175)$ with $68\%$ ($95\%$) confidence levels. These constraints restrict the potential systematic shift in $D_A(z)$, $H(z)$ and $f\sigma_8$, due to the relative velocity, to $1\%$, $0.8\%$ and $2\%$, respectively. Given the current uncertainties on the BAO measurements of BOSS these shifts correspond to $0.53\sigma$, $0.5\sigma$ and $0.22\sigma$ for $D_A(z)$, $H(z)$ and $f\sigma_8$, respectively

Extending the modeling of the anisotropic galaxy power spectrum to k=0.4 hMpc−1k = 0.4 \ h\mathrm{Mpc}^{-1}

We present a new model for the redshift-space power spectrum of galaxies and demonstrate its accuracy in modeling the monopole, quadrupole, and hexadecapole of the galaxy density field down to scales of $k = 0.4 \ h\mathrm{Mpc}^{-1}$. The model describes the clustering of galaxies in the context of a halo model and the clustering of the underlying halos in redshift space using a combination of Eulerian perturbation theory and $N$-body simulations. The modeling of redshift-space distortions is done using the so-called distribution function approach. The final model has 13 free parameters, and each parameter is physically motivated rather than a nuisance parameter, which allows the use of well-motivated priors. We account for the Finger-of-God effect from centrals and both isolated and non-isolated satellites rather than using a single velocity dispersion to describe the combined effect. We test and validate the accuracy of the model on several sets of high-fidelity $N$-body simulations, as well as realistic mock catalogs designed to simulate the BOSS DR12 CMASS data set. The suite of simulations covers a range of cosmologies and galaxy bias models, providing a rigorous test of the level of theoretical systematics present in the model. The level of bias in the recovered values of $f \sigma_8$ is found to be small. When including scales to $k = 0.4 \ h\mathrm{Mpc}^{-1}$, we find 15-30\% gains in the statistical precision of $f \sigma_8$ relative to $k = 0.2 \ h\mathrm{Mpc}^{-1}$ and a roughly 10-15\% improvement for the perpendicular Alcock-Paczynski parameter $\alpha_\perp$. Using the BOSS DR12 CMASS mocks as a benchmark for comparison, we estimate an uncertainty on $f \sigma_8$ that is $\sim$10-20\% larger than other similar Fourier-space RSD models in the literature that use $k \leq 0.2 \ h\mathrm{Mpc}^{-1}$, suggesting that these models likely have a too-limited parametrization.Comment: Submitted to JCA

Modeling the reconstructed BAO in Fourier space

The density field reconstruction technique, which was developed to partially reverse the nonlinear degradation of the Baryon Acoustic Oscillation (BAO) feature in the galaxy redshift surveys, has been successful in substantially improving the cosmology constraints from recent galaxy surveys such as Baryon Oscillation Spectroscopic Survey (BOSS). We estimate the efficiency of the reconstruction method as a function of various reconstruction details. To directly quantify the BAO information in nonlinear density fields before and after reconstruction, we calculate the cross-correlations (i.e., propagators) of the pre(post)-reconstructed density field with the initial linear field using a mock galaxy sample that is designed to mimic the clustering of the BOSS CMASS galaxies. The results directly provide the BAO damping as a function of wavenumber that can be implemented into the Fisher matrix analysis. We focus on investigating the dependence of the propagator on a choice of smoothing filters and on two major different conventions of the redshift-space density field reconstruction that have been used in literature. By estimating the BAO signal-to-noise for each case, we predict constraints on the angular diameter distance and Hubble parameter using the Fisher matrix analysis. We thus determine an optimal Gaussian smoothing filter scale for the signal-to-noise level of the BOSS CMASS. We also present appropriate BAO fitting models for different reconstruction methods based on the first and second order Lagrangian perturbation theory in Fourier space. Using the mock data, we show that the modified BAO fitting model can substantially improve the accuracy of the BAO position in the best fits as well as the goodness of the fits.Comment: 21 pages, 7 figures, 1 table. Minor revisions. Matches version accepted by MNRA

A complete FFT-based decomposition formalism for the redshift-space bispectrum

To fully extract cosmological information from nonlinear galaxy distribution in redshift space, it is essential to include higher-order statistics beyond the two-point correlation function. In this paper, we propose a new decomposition formalism for computing the anisotropic bispectrum in redshift space and for measuring it from galaxy samples. Our formalism uses tri-polar spherical harmonic decomposition with zero total angular momentum to compress the 3D modes distribution in the redshift-space bispectrum. This approach preserves three fundamental properties of the Universe: statistical homogeneity, isotropy, and parity-symmetry, allowing us to efficiently separate the anisotropic signal induced by redshift-space distortions (RSDs) and the Alcock-Paczy\'{n}ski (AP) effect from the isotropic bispectrum. The relevant expansion coefficients in terms of the anisotropic signal are reduced to one multipole index $L$, and the $L> 0$ modes are induced only by the RSD or AP effects. Our formalism has two advantages: (1) we can make use of Fast Fourier Transforms (FFTs) to measure the bispectrum; (2) it gives a simple expression to correct for the survey geometry, i.e., the survey window function. As a demonstration, we measure the decomposed bispectrum from the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12, and, for the first time, present a $14\sigma$ detection of the anisotropic bispectrum in the $L=2$ mode.Comment: 23 pages, 13 figure

Eulerian BAO Reconstructions and N-Point Statistics

As galaxy surveys begin to measure the imprint of baryonic acoustic oscillations (BAO) on large-scale structure at the sub-percent level, reconstruction techniques that reduce the contamination from nonlinear clustering become increasingly important. Inverting the nonlinear continuity equation, we propose an Eulerian growth-shift reconstruction algorithm that does not require the displacement of any objects, which is needed for the standard Lagrangian BAO reconstruction algorithm. In real-space DM-only simulations the algorithm yields 95% of the BAO signal-to-noise obtained from standard reconstruction. The reconstructed power spectrum is obtained by adding specific simple 3- and 4-point statistics to the pre-reconstruction power spectrum, making it very transparent how additional BAO information from higher-point statistics is included in the power spectrum through the reconstruction process. Analytical models of the reconstructed density for the two algorithms agree at second order. Based on similar modeling efforts, we introduce four additional reconstruction algorithms and discuss their performance.Comment: 20+10 pages, 12 figures, included minor improvements to match version accepted for publicatio