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Register a new userScale-Dependent Bias of Galaxies from Baryonic Acoustic Oscillations
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Rennan Barkana
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Baryonic acoustic oscillations (BAOs) modulate the density ratio of baryons to dark matter across large regions of the Universe. We show that the associated variation in the mass-to-light ratio of galaxies should generate an oscillatory, scale-dependent bias of galaxies relative to the underlying distribution of dark matter. A measurement of this effect would calibrate the dependence of the characteristic mass-to-light ratio of galaxies on the baryon mass fraction in their large scale environment. This bias, though, is unlikely to significantly affect measurements of BAO peak positions.
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We report five measurements of the transverse baryonic acoustic scale, $theta_{BAO}$, obtained from the angular two-point correlation function calculation for Luminous Red Galaxies of the eleventh data release of the Sloan Digital Sky Survey (SDSS). Each measurement has been obtained by considering a thin redshift shell ($delta z = 0.01$ and $0.02$) in the interval $ z in [0.565, 0.660] $, which contains a large density of galaxies ($sim 20,000$ galaxies/redshift shell). Differently from the three-dimensional Baryon Acoustic Oscillations (BAO) measurements, these data points are obtained almost model-independently and provide a Cosmic Microwave Background (CMB)-independent way to estimate the sound horizon $ r_s $. Assuming a time-dependent equation-of-state parameter for the dark energy, we also discuss constraints on the main cosmological parameters from $theta_{BAO}$ and CMB data.
NoAM for No Action Method is a framework for reconstructing the past orbits of observed tracers of the large scale mass density field. It seeks exact solutions of the equations of motion (EoM), satisfying initial homogeneity and the final observed particle (tracer) positions. The solutions are found iteratively reaching a specified tolerance defined as the RMS of the distance between reconstructed and observed positions. Starting from a guess for the initial conditions, NoAM advances particles using standard N-body techniques for solving the EoM. Alternatively, the EoM can be replaced by any approximation such as Zeldovich and second order perturbation theory (2LPT). NoAM is suitable for billions of particles and can easily handle non-regular volumes, redshift space, and other constraints. We implement NoAM to systematically compare Zeldovich, 2LPT, and N-body dynamics over diverse configurations ranging from idealized high-res periodic simulation box to realistic galaxy mocks. Our findings are (i) Non-linear reconstructions with Zeldovich, 2LPT, and full dynamics perform better than linear theory only for idealized catalogs in real space. For realistic catalogs, linear theory is the optimal choice for reconstructing velocity fields smoothed on scales > 5 Mpc/h. (ii) all non-linear back-in-time reconstructions tested here, produce comparable enhancement of the baryonic oscillation signal in the correlation function.
We quantitatively investigate the possibility of detecting baryonic acoustic oscillations (BAO) using single-dish 21cm intensity mapping observations in the post-reionization era. We show that the telescope beam smears out the isotropic BAO signature and, in the case of the Square Kilometer Array (SKA) instrument, makes it undetectable at redshifts $zgtrsim1$. We however demonstrate that the BAO peak can still be detected in the radial 21cm power spectrum and describe a method to make this type of measurements. By means of numerical simulations, containing the 21cm cosmological signal as well as the most relevant Galactic and extra-Galactic foregrounds and basic instrumental effect, we quantify the precision with which the radial BAO scale can be measured in the 21cm power spectrum. We systematically investigate the signal-to-noise and the precision of the recovered BAO signal as a function of cosmic variance, instrumental noise, angular resolution and foreground contamination. We find that the expected noise levels of SKA would degrade the final BAO errors by $sim5%$ with respect to the cosmic-variance limited case at low redshifts, but that the effect grows up to $sim65%$ at $zsim2-3$. Furthermore, we find that the radial BAO signature is robust against foreground systematics, and that the main effect is an increase of $sim20%$ in the final uncertainty on the standard ruler caused by the contribution of foreground residuals as well as the reduction in sky area needed to avoid high-foreground regions. We also find that it should be possible to detect the radial BAO signature with high significance in the full redshift range. We conclude that a 21cm experiment carried out by the SKA should be able to make direct measurements of the expansion rate $H(z)$ with competitive per-cent level precision on redshifts $zlesssim2.5$.
We show that it is possible to build effective matter density power spectra in tomographic cosmic shear observations that exhibit the Baryonic Acoustic Oscillations (BAO) features once a nulling transformation has been applied to the data. The precision with which the amplitude and position of these features can be reconstructed is quantified in terms of sky coverage, intrinsic shape noise, median source redshift and number density of sources. BAO detection in Euclid or LSST like wide surveys will be possible with a modest signal-to-noise ratio. It would improve dramatically for slightly deeper surveys.
Primordial non-Gaussianity introduces a scale-dependent variation in the clustering of density peaks corresponding to rare objects. This variation, parametrized by the bias, is investigated on scales where a linear perturbation theory is sufficiently accurate. The bias is obtained directly in real space by comparing the one- and two-point probability distributions of density fluctuations. We show that these distributions can be reconstructed using a bivariate Edgeworth series, presented here up to an arbitrarily high order. The Edgeworth formalism is shown to be well-suited for local cubic-order non-Gaussianity parametrized by g_NL. We show that a strong scale-dependence in the bias can be produced by g_NL of order 10,000, consistent with CMB constraints. On correlation length of ~100 Mpc, current constraints on g_NL still allow the bias for the most massive clusters to be enhanced by 20-30% of the Gaussian value. We further examine the bias as a function of mass scale, and also explore the relationship between the clustering and the abundance of massive clusters in the presence of g_NL. We explain why the Edgeworth formalism, though technically challenging, is a very powerful technique for constraining high-order non-Gaussianity with large-scale structures.
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