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Register a new userRecovering the real-space correlation function from photometric redshift surveys
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Measurements of clustering in large-scale imaging surveys that make use of photometric redshifts depend on the uncertainties in the redshift determination. We have used light-cone simulations to show how the deprojection method successfully recovers the real space correlation function when applied to mock photometric redshift surveys. We study how the errors in the redshift determination affect the quality of the recovered two-point correlation function. Considering the expected errors associated to the planned photometric redshift surveys, we conclude that this method provides information on the clustering of matter useful for the estimation of cosmological parameters that depend on the large scale distribution of galaxies.
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We outline how redshift-space distortions (RSD) can be measured from the angular correlation function w({theta}), of galaxies selected from photometric surveys. The natural degeneracy between RSD and galaxy bias can be minimized by comparing results from bins with top-hat galaxy selection in redshift, and bins based on the radial position of galaxy pair centres. This comparison can also be used to test the accuracy of the photometric redshifts. The presence of RSD will be clearly detectable with the next generation of photometric redshift surveys. We show that the Dark Energy Survey (DES) will be able to measure f(z){sigma}_8(z) to a 1{sigma} accuracy of (17 {times} b)%, using galaxies drawn from a single narrow redshift slice centered at z = 1. Here b is the linear bias, and f is the logarithmic rate of change of the linear growth rate with respect to the scale factor. Extending to measurements of w({theta}) for a series of bins of width 0.02(1 + z) over 0.5 < z < 1.4 will measure {gamma} to a 1{sigma} accuracy of 25%, given the model f = {Omega}_m(z)^{gamma}, and assuming a linear bias model that evolves such that b = 0.5 + z (and fixing other cosmological parameters). The accuracy of our analytic predictions is confirmed using mock catalogs drawn from simulations conducted by the MICE collaboration.
We investigate a new method to recover (if any) a possible varying speed of light (VSL) signal from cosmological data. It comes as an upgrade of [1,2], where it was argued that such signal could be detected at a single redshift location only. Here, we show how it is possible to extract information on a VSL signal on an extended redshift range. We use mock cosmological data from future galaxy surveys (BOSS, DESI, emph{WFirst-2.4} and SKA): the sound horizon at decoupling imprinted in the clustering of galaxies (BAO) as an angular diameter distance, and the expansion rate derived from those galaxies recognized as cosmic chronometers. We find that, given the forecast sensitivities of such surveys, a $sim1%$ VSL signal can be detected at $3sigma$ confidence level in the redshift interval $z in [0.,1.55]$. Smaller signals $(sim0.1%)$ will be hardly detected (even if some lower possibility for a $1sigma$ detection is still possible). Finally, we discuss the degeneration between a VSL signal and a non-null spatial curvature; we show that, given present bounds on curvature, any signal, if detected, can be attributed to a VSL signal with a very high confidence. On the other hand, our method turns out to be useful even in the classical scenario of a constant speed of light: in this case, the signal we reconstruct can be totally ascribed to spatial curvature and, thus, we might have a method to detect a $0.01$-order curvature in the same redhift range with a very high confidence.
We analyze the quasar two-point correlation function (2pCF) within the redshift interval $0.8<z<2.2$ using a sample of 52303 quasars selected from the recent 7th Data Release of the Sloan Digital Sky Survey. Our approach to 2pCF uses a concept of locally Lorentz (Fermi) frame for determination of the distance between objects and permutation method of the random catalogue generation. Assuming the spatially flat cosmological model with given $Omega_{Lambda}=0.726$, we found that the real-space 2pCF is fitted well with the power-low model within the distance range $1<sigma<35$ $h^{-1}$ Mpc with the correlation length $r_{0}=5.85pm0.33$ $h^{-1}$ Mpc and the slope $gamma=1.87pm0.07$. The redshift-space 2pCF is approximated with $s_{0}=6.43pm0.63$ $h^{-1}$ Mpc and $gamma=1.21pm0.24$ for $1<s<10$ $h^{-1}$ Mpc, and $s_{0}=7.37pm0.81$ $h^{-1}$ Mpc and $gamma=1.90pm0.24$ for $10<s<35$ $h^{-1}$ Mpc. For distances $s>10,h^{-1}$ Mpc the parameter describing the large-scale infall to density inhomogeneities is $beta=0.63pm0.10$ with the linear bias $b=1.44pm0.22$ that marginally (within 2$sigma$) agrees with the linear theory of cosmological perturbations. We discuss possibilities to obtain a statistical estimate of the random component of quasars velocities (different from the large-scale infall). We note rather slight dependence of quasars velocity dispersion upon the 2pCF parameters in the region $r<2$ Mpc.
Cosmological galaxy surveys aim at mapping the largest volumes to test models with techniques such as cluster abundance, cosmic shear correlations or baryon acoustic oscillations (BAO), which are designed to be independent of galaxy bias. Here we explore an alternative route to constrain cosmology: sampling more moderate volumes with the cross-correlation of photometric and spectroscopic surveys. We consider the angular galaxy-galaxy autocorrelation in narrow redshift bins and its combination with different probes of weak gravitational lensing (WL) and redshift space distortions (RSD). Including the cross-correlation of these surveys improves by factors of a few the constraints on both the dark energy equation of state w(z) and the cosmic growth history, parametrized by gamma. The additional information comes from using many narrow redshift bins and from galaxy bias, which is measured both with WL probes and RSD, breaking degeneracies that are present when using each method separately. We show forecasts for a joint w(z) and gamma figure of merit using linear scales over a deep (i<24) photometric survey and a brighter (i<22.5) spectroscopic or very accurate (0.3%) photometric redshift survey. Magnification or shear in the photometric sample produce FoM that are of the same order of magnitude of those of RSD or BAO over the spectroscopic sample. However, the cross-correlation of these probes over the same area yields a FoM that is up to a factor 100 times larger. Magnification alone, without shape measurements, can also be used for these cross-correlations and can produce better results than using shear alone. For a spectroscopic follow-up survey strategy, measuring the spectra of the foreground lenses to perform this cross-correlation provides 5 times better FoM than targeting the higher redshift tail of the galaxy distribution to study BAO over a 2.5 times larger volume.
We provide constraints on the accuracy with which the neutrino mass fraction, $f_{ u}$, can be estimated when exploiting measurements of redshift-space distortions, describing in particular how the error on neutrino mass depends on three fundamental parameters of a characteristic galaxy redshift survey: density, halo bias and volume. In doing this, we make use of a series of dark matter halo catalogues extracted from the BASICC simulation. The mock data are analysed via a Markov Chain Monte Carlo likelihood analysis. We find a fitting function that well describes the dependence of the error on bias, density and volume, showing a decrease in the error as the bias and volume increase, and a decrease with density down to an almost constant value for high density values. This fitting formula allows us to produce forecasts on the precision achievable with future surveys on measurements of the neutrino mass fraction. For example, a Euclid-like spectroscopic survey should be able to measure the neutrino mass fraction with an accuracy of $delta f_{ u} approx 6.7times10^{-4}$, using redshift-space clustering once all the other cosmological parameters are kept fixed to the $Lambda$CDM case.
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