Determining accurate redshift distributions for very large samples of objects has become increasingly important in cosmology. We investigate the impact of extending cross-correlation based redshift distribution recovery methods to include small scale
clustering information. The major concern in such work is the ability to disentangle the amplitude of the underlying redshift distribution from the influence of evolving galaxy bias. Using multiple simulations covering a variety of galaxy bias evolution scenarios, we demonstrate reliable redshift recoveries using linear clustering assumptions well into the non-linear regime for redshift distributions of narrow redshift width. Including information from intermediate physical scales balances the increased information available from clustering and the residual bias incurred from relaxing of linear constraints. We discuss how breaking a broad sample into tomographic bins can improve estimates of the redshift distribution, and present a simple bias removal technique using clustering information from the spectroscopic sample alone.
We present a global measurement of the integrated Sachs-Wolfe (ISW) effect obtained by cross-correlating all relevant large scale galaxy data sets with the cosmic microwave background radiation map provided by the Wilkinson Microwave Anisotropy Probe
. With these measurements, the overall ISW signal is detected at the ~ 4.5 sigma level. We also examine the cosmological implications of these measurements, particularly the dark energy equation of state w, its sound speed, and the overall curvature of the Universe. The flat LCDM model is a good fit to the data and, assuming this model, we find that the ISW data constrain Omega_m = 0.20 +0.19 -0.11 at the 95% confidence level. When we combine our ISW results with the latest baryon oscillation and supernovae measurements, we find that the result is still consistent with a flat LCDM model with w = -1 out to redshifts z > 1.
This is the first in a series of papers on the weak lensing effect caused by clusters of galaxies in Sloan Digital Sky Survey. The photometrically selected cluster sample, known as MaxBCG, includes ~130,000 objects between redshift 0.1 and 0.3, rangi
ng in size from small groups to massive clusters. We split the clusters into bins of richness and luminosity and stack the surface density contrast to produce mean radial profiles. The mean profiles are detected over a range of scales, from the inner halo (25 kpc/h) well into the surrounding large scale structure (30 Mpc/h), with a significance of 15 to 20 in each bin. The signal over this large range of scales is best interpreted in terms of the cluster-mass cross-correlation function. We pay careful attention to sources of systematic error, correcting for them where possible. The resulting signals are calibrated to the ~10% level, with the dominant remaining uncertainty being the redshift distribution of the background sources. We find that the profiles scale strongly with richness and luminosity. We find the signal within a given richness bin depends upon luminosity, suggesting that luminosity is more closely correlated with mass than galaxy counts. We split the samples by redshift but detect no significant evolution. The profiles are not well described by power laws. In a subsequent series of papers we invert the profiles to three-dimensional mass profiles, show that they are well fit by a halo model description, measure mass-to-light ratios and provide a cosmological interpretation.
Astronomy began as a visual science, first through careful observations of the sky using either an eyepiece or the naked eye, then on to the preservation of those images with photographic media and finally the digital encoding of that information via
CCDs. This last step has enabled astronomy to move into a fully automated era -- where data is recorded, analyzed and interpreted often without any direct visual inspection. Sky in Google Earth completes that circle by providing an intuitive visual interface to some of the largest astronomical imaging surveys covering the full sky. By streaming imagery, catalogs, time domain data, and ancillary information directly to a user, Sky can provide the general public as well as professional and amateur astronomers alike with a wealth of information for use in education and research. We provide here a brief introduction to Sky in Google Earth, focusing on its extensible environment, how it may be integrated into the research process and how it can bring astronomical research to a broader community. With an open interface available on Linux, Mac OS X and Windows, applications developed within Sky are accessible not just within the Google framework but through any visual browser that supports the Keyhole Markup Language. We present Sky as the embodiment of a virtual telescope.
