A Galaxy Photometric Redshift Catalog for the Sloan Digital Sky Survey Data Release 6

We present and describe a catalog of galaxy photometric redshifts (photo-z's) for the Sloan Digital Sky Survey (SDSS) Data Release 6 (DR6). We use the Artificial Neural Network (ANN) technique to calculate photo-z's and the Nearest Neighbor Error (NNE) method to estimate photo-z errors for ~ 77 million objects classified as galaxies in DR6 with r < 22. The photo-z and photo-z error estimators are trained and validated on a sample of ~ 640,000 galaxies that have SDSS photometry and spectroscopic redshifts measured by SDSS, 2SLAQ, CFRS, CNOC2, TKRS, DEEP, and DEEP2. For the two best ANN methods we have tried, we find that 68% of the galaxies in the validation set have a photo-z error smaller than sigma_{68} =0.021 or $0.024. After presenting our results and quality tests, we provide a short guide for users accessing the public data.Comment: 16 pages, 12 figure

Nonlinear Evolution of ƒ(\u3cem\u3eR\u3c/em\u3e) Cosmologies. III. Halo Statistics

The statistical properties of dark matter halos, the building blocks of cosmological observables associated with structure in the Universe, offer many opportunities to test models for cosmic acceleration, especially those that seek to modify gravitational forces. We study the abundance, bias, and profiles of halos in cosmological simulations for one such model: the modified action ƒ(R) theory. The effects of ƒ(R) modified gravity can be separated into a large- and small-field limit. In the large-field limit, which is accessible to current observations, enhanced gravitational forces raise the abundance of rare massive halos and decrease their bias but leave their (lensing) mass profiles largely unchanged. This regime is well described by scaling relations based on a modification of spherical collapse calculations. In the small-field limit, the enhancement of the gravitational force is suppressed inside halos and the effects on halo properties are substantially reduced for the most massive halos. Nonetheless, the scaling relations still retain limited applicability for the purpose of establishing conservative upper limits on the modification to gravity

Non-linear evolution of f(R) cosmologies I: methodology

We introduce the method and the implementation of a cosmological simulation of a class of metric-variation f(R) models that accelerate the cosmological expansion without a cosmological constant and evade solar-system bounds of small-field deviations to general relativity. Such simulations are shown to reduce to solving a non-linear Poisson equation for the scalar degree of freedom introduced by the f(R) modifications. We detail the method to efficiently solve the non-linear Poisson equation by using a Newton-Gauss-Seidel relaxation scheme coupled with multigrid method to accelerate the convergence. The simulations are shown to satisfy tests comparing the simulated outcome to analytical solutions for simple situations, and the dynamics of the simulations are tested with orbital and Zeldovich collapse tests. Finally, we present several static and dynamical simulations using realistic cosmological parameters to highlight the differences between standard physics and f(R) physics. In general, we find that the f(R) modifications result in stronger gravitational attraction that enhances the dark matter power spectrum by ~20% for large but observationally allowed f(R) modifications. More detailed study of the non-linear f(R) effects on the power spectrum are presented in a companion paper.Comment: 15 pages, 11 figure

Non-linear Evolution of f(R) Cosmologies III: Halo Statistics

The statistical properties of dark matter halos, the building blocks of cosmological observables associated with structure in the universe, offer many opportunities to test models for cosmic acceleration, especially those that seek to modify gravitational forces. We study the abundance, bias and profiles of halos in cosmological simulations for one such model: the modified action f(R) theory. In the large field regime that is accessible to current observations, enhanced gravitational forces raise the abundance of rare massive halos and decrease their bias but leave their (lensing) mass profiles largely unchanged. This regime is well described by scaling relations based on a modification of spherical collapse calculations. In the small field regime, enhanced forces are suppressed inside halos and the effects on halo properties are substantially reduced for the most massive halos. Nonetheless, the scaling relations still retain limited applicability for the purpose of establishing conservative upper limits on the modification to gravity.Comment: 12 pages, 10 figures; v2: revised version accepted by Phys. Rev.

Photometric Redshift Error Estimators

Photometric redshift (photo-z) estimates are playing an increasingly important role in extragalactic astronomy and cosmology. Crucial to many photo-z applications is the accurate quantification of photometric redshift errors and their distributions, including identification of likely catastrophic failures in photo-z estimates. We consider several methods of estimating photo-z errors and propose new training-set based error estimators based on spectroscopic training set data. Using data from the Sloan Digital Sky Survey and simulations of the Dark Energy Survey as examples, we show that this method provides a robust, relatively unbiased estimate of photo-z errors. We show that culling objects with large, accurately estimated photo-z errors from a sample can reduce the incidence of catastrophic photo-z failures.Comment: 10 pages, 11 figures, submitted to Ap

Cross-correlation Weak Lensing of SDSS Galaxy Clusters I: Measurements

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, ranging 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.Comment: Paper I in a series; v2.0 includes ApJ referee's suggestion

Estimating the redshift distribution of photometric galaxy samples – II. Applications and tests of a new method

In Lima et al. we presented a new method for estimating the redshift distribution, N ( z ) , of a photometric galaxy sample, using photometric observables and weighted sampling from a spectroscopic subsample of the data. In this paper, we extend this method and explore various applications of it, using both simulations and real data from the Sloan Digital Sky Survey (SDSS). In addition to estimating the redshift distribution for an entire sample, the weighting method enables accurate estimates of the redshift probability distribution, p ( z ) , for each galaxy in a photometric sample. Use of p ( z ) in cosmological analyses can substantially reduce biases associated with traditional photometric redshifts, in which a single redshift estimate is associated with each galaxy. The weighting procedure also naturally indicates which galaxies in the photometric sample are expected to have accurate redshift estimates, namely those that lie in regions of photometric-observable space that are well sampled by the spectroscopic subsample. In addition to providing a method that has some advantages over standard photo- z estimates, the weights method can also be used in conjunction with photo- z estimates e.g. by providing improved estimation of N ( z ) via deconvolution of N ( z phot ) and improved estimates of photo- z scatter and bias. We present a publicly available p ( z ) catalogue for ∼78 million SDSS DR7 galaxies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75507/1/j.1365-2966.2009.14908.x.pd

Estimating the Redshift Distribution of Faint Galaxy Samples

We present an empirical method for estimating the underlying redshift distribution N(z) of galaxy photometric samples from photometric observables. The method does not rely on photometric redshift (photo-z) estimates for individual galaxies, which typically suffer from biases. Instead, it assigns weights to galaxies in a spectroscopic subsample such that the weighted distributions of photometric observables (e.g., multi-band magnitudes) match the corresponding distributions for the photometric sample. The weights are estimated using a nearest-neighbor technique that ensures stability in sparsely populated regions of color-magnitude space. The derived weights are then summed in redshift bins to create the redshift distribution. We apply this weighting technique to data from the Sloan Digital Sky Survey as well as to mock catalogs for the Dark Energy Survey, and compare the results to those from the estimation of photo-z's derived by a neural network algorithm. We find that the weighting method accurately recovers the underlying redshift distribution, typically better than the photo-z reconstruction, provided the spectroscopic subsample spans the range of photometric observables covered by the photometric sample.Comment: 14 pages, 9 figures, submitted to MNRA

The Fifth Data Release of the Sloan Digital Sky Survey

This paper describes the Fifth Data Release (DR5) of the Sloan Digital Sky Survey (SDSS). DR5 includes all survey quality data taken through June 2005 and represents the completion of the SDSS-I project (whose successor, SDSS-II will continue through mid-2008). It includes five-band photometric data for 217 million objects selected over 8000 square degrees, and 1,048,960 spectra of galaxies, quasars, and stars selected from 5713 square degrees of that imaging data. These numbers represent a roughly 20% increment over those of the Fourth Data Release; all the data from previous data releases are included in the present release. In addition to "standard" SDSS observations, DR5 includes repeat scans of the southern equatorial stripe, imaging scans across M31 and the core of the Perseus cluster of galaxies, and the first spectroscopic data from SEGUE, a survey to explore the kinematics and chemical evolution of the Galaxy. The catalog database incorporates several new features, including photometric redshifts of galaxies, tables of matched objects in overlap regions of the imaging survey, and tools that allow precise computations of survey geometry for statistical investigations.Comment: ApJ Supp, in press, October 2007. This paper describes DR5. The SDSS Sixth Data Release (DR6) is now public, available from http://www.sdss.or