15 research outputs found
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