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Register a new userMeasuring the Universe with galaxy redshift surveys
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Added by
Carmelita Carbone Dr
Publication date
2018
fields
Physics
and research's language is
English
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Galaxy redshift surveys are one of the pillars of the current standard cosmological model and remain a key tool in the experimental effort to understand the origin of cosmic acceleration. To this end, the next generation of surveys aim at achieving sub-percent precision in the measurement of the equation of state of dark energy $w(z)$ and the growth rate of structure $f(z)$. This however requires comparable control over systematic errors, stressing the need for improved modelling methods. In this contribution we review at the introductory level some highlights of the work done in this direction by the {it Darklight} project. Supported by an ERC Advanced Grant, {it Darklight} developed novel techniques for clustering analysis, which were tested through numerical simulations before being finally applied to galaxy data as in particular those of the recently completed VIPERS redshift survey. We focus in particular on: (a) advances on estimating the growth rate of structure from redshift-space distortions; (b) parameter estimation through global Bayesian reconstruction of the density field from survey data; (c) impact of massive neutrinos on large-scale structure measurements. Overall, {it Darklight} has contributed to paving the way for forthcoming high-precision experiments, such as {it Euclid}, the next ESA cosmological mission.
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Galaxy redshift surveys have achieved significant progress over the last couple of decades. Those surveys tell us in the most straightforward way what our local universe looks like. While the galaxy distribution traces the bright side of the universe, detailed quantitative analyses of the data have even revealed the dark side of the universe dominated by non-baryonic dark matter as well as more mysterious dark energy (or Einsteins cosmological constant). We describe several methodologies of using galaxy redshift surveys as cosmological probes, and then summarize the recent results from the existing surveys. Finally we present our views on the future of redshift surveys in the era of Precision Cosmology.
We study the applicability of several galaxy environment measures (n^th-nearest-neighbor distance, counts in an aperture, and Voronoi volume) within deep redshift surveys. Mock galaxy catalogs are employed to mimic representative photometric and spectroscopic surveys at high redshift (z ~ 1). We investigate the effects of survey edges, redshift precision, redshift-space distortions, and target selection upon each environment measure. We find that even optimistic photometric redshift errors (sigma_z = 0.02) smear out the line-of-sight galaxy distribution irretrievably on small scales; this significantly limits the application of photometric redshift surveys to environment studies. Edges and holes in a survey field dramatically affect the estimation of environment, with the impact of edge effects depending upon the adopted environment measure. These edge effects considerably limit the usefulness of smaller survey fields (e.g. the GOODS fields) for studies of galaxy environment. In even the poorest groups and clusters, redshift-space distortions limit the effectiveness of each environment statistic; measuring density in projection (e.g. using counts in a cylindrical aperture or a projected n^th-nearest-neighbor distance measure) significantly improves the accuracy of measures in such over-dense environments. For the DEEP2 Galaxy Redshift Survey, we conclude that among the environment estimators tested the projected n^th-nearest-neighbor distance measure provides the most accurate estimate of local galaxy density over a continuous and broad range of scales.
The peculiar motion of galaxies can be a particularly sensitive probe of gravitational collapse. As such, it can be used to measure the dynamics of dark matter and dark energy as well the nature of the gravitational laws at play on cosmological scales. Peculiar motions manifest themselves as an overall anisotropy in the measured clustering signal as a function of the angle to the line-of-sight, known as redshift-space distortion (RSD). Limiting factors in this measurement include our ability to model non-linear galaxy motions on small scales and the complexities of galaxy bias. The anisotropy in the measured clustering pattern in redshift-space is also driven by the unknown distance factors at the redshift in question, the Alcock-Paczynski distortion. This weakens growth rate measurements, but permits an extra geometric probe of the Hubble expansion rate. In this chapter we will briefly describe the scientific background to the RSD technique, and forecast the potential of the SKA phase 1 and the SKA2 to measure the growth rate using both galaxy catalogues and intensity mapping, assessing their competitiveness with current and future optical galaxy 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.
Survey observations of the three-dimensional locations of galaxies are a powerful approach to measure the distribution of matter in the universe, which can be used to learn about the nature of dark energy, physics of inflation, neutrino masses, etc. A competitive survey, however, requires a large volume (e.g., Vsurvey is roughly 10 Gpc3) to be covered, and thus tends to be expensive. A sparse sampling method offers a more affordable solution to this problem: within a survey footprint covering a given survey volume, Vsurvey, we observe only a fraction of the volume. The distribution of observed regions should be chosen such that their separation is smaller than the length scale corresponding to the wavenumber of interest. Then one can recover the power spectrum of galaxies with precision expected for a survey covering a volume of Vsurvey (rather than the volume of the sum of observed regions) with the number density of galaxies given by the total number of observed galaxies divided by Vsurvey (rather than the number density of galaxies within an observed region). We find that regularly-spaced sampling yields an unbiased power spectrum with no window function effect, and deviations from regularly-spaced sampling, which are unavoidable in realistic surveys, introduce calculable window function effects and increase the uncertainties of the recovered power spectrum. While we discuss the sparse sampling method within the context of the forthcoming Hobby-Eberly Telescope Dark Energy Experiment, the method is general and can be applied to other galaxy surveys.
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