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Michael S. Vogeley

Publications and source records attributed to Michael S. Vogeley.

65 records · Page 4Linked to original sources
arXiv2001

Detecting Clusters of Galaxies in the Sloan Digital Sky Survey I : Monte Carlo Comparison of Cluster Detection Algorithms

We present a comparison of three cluster finding algorithms from imaging data using Monte Carlo simulations of clusters embedded in a 25 deg^2 region of Sloan Digital Sky Survey (SDSS) imaging data: the Matched Filter (MF; Postman et al. 1996), the Adaptive Matched Filter (AMF; Kepner et al. 1999) and a color-magnitude filtered Voronoi Tessellation Technique (VTT). Among the two matched filters, we find that the MF is more efficient in detecting faint clusters, whereas the AMF evaluates the redshifts and richnesses more accurately, therefore suggesting a hybrid method (HMF) that combines the two. The HMF outperforms the VTT when using a background that is uniform, but it is more sensitive to the presence of a non-uniform galaxy background than is the VTT; this is due to the assumption of a uniform background in the HMF model. We thus find that for the detection thresholds we determine to be appropriate for the SDSS data, the performance of both algorithms are similar; we present the selection function for each method evaluated with these thresholds as a function of redshift and richness. For simulated clusters generated with a Schechter luminosity function (M_r^* = -21.5 and alpha = -1.1) both algorithms are complete for Abell richness >= 1 clusters up to z ~ 0.4 for a sample magnitude limited to r = 21. While the cluster parameter evaluation shows a mild correlation with the local background density, the detection efficiency is not significantly affected by the background fluctuations, unlike previous shallower surveys.

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arXiv2001

KL Estimation of the Power Spectrum Parameters from the Angular Distribution of Galaxies in Early SDSS Data

We present measurements of parameters of the 3-dimensional power spectrum of galaxy clustering from 222 square degrees of early imaging data in the Sloan Digital Sky Survey. The projected galaxy distribution on the sky is expanded over a set of Karhunen-Loeve eigenfunctions, which optimize the signal-to-noise ratio in our analysis. A maximum likelihood analysis is used to estimate parameters that set the shape and amplitude of the 3-dimensional power spectrum. Our best estimates are Gamma=0.188 +/- 0.04 and sigma_8L = 0.915 +/- 0.06 (statistical errors only), for a flat Universe with a cosmological constant. We demonstrate that our measurements contain signal from scales at or beyond the peak of the 3D power spectrum. We discuss how the results scale with systematic uncertainties, like the radial selection function. We find that the central values satisfy the analytically estimated scaling relation. We have also explored the effects of evolutionary corrections, various truncations of the KL basis, seeing, sample size and limiting magnitude. We find that the impact of most of these uncertainties stay within the 2-sigma uncertainties of our fiducial result.

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arXiv2001

The 3D Power Spectrum from Angular Clustering of Galaxies in Early SDSS Data

Early photometric data from the Sloan Digital Sky Survey (SDSS) contain angular positions for 1.5 million galaxies. In companion papers, the angular correlation function $w(θ)$ and 2D power spectrum $C_l$ of these galaxies are presented. Here we invert Limber's equation to extract the 3D power spectrum from the angular results. We accomplish this using an estimate of $dn/dz$, the redshift distribution of galaxies in four different magnitude slices in the SDSS photometric catalog. The resulting 3D power spectrum estimates from $w(θ)$ and $C_l$ agree with each other and with previous estimates over a range in wavenumbers $0.03 < k/{\rm h Mpc}^{-1} < 1$. The galaxies in the faintest magnitude bin ($21 < \rstar < 22$, which have median redshift $z_m=0.43$) are less clustered than the galaxies in the brightest magnitude bin ($18 < \rstar < 19$ with $z_m=0.17$), especially on scales where nonlinearities are important. The derived power spectrum agrees with that of Szalay et al. (2001) who go directly from the raw data to a parametric estimate of the power spectrum. The strongest constraints on the shape parameter $Γ$ come from the faintest galaxies (in the magnitude bin $21 < \rstar < 22$), from which we infer $Γ= 0.14^{+0.11}_{-0.06}$ (95% C.L.).

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arXiv2001

Binned Cosmic Microwave Background Anisotropy Power Spectra: Peak Location

We use weighted mean and median statistics techniques to combine individual cosmic microwave background (CMB) anisotropy detections and determine binned, multipole-space, CMB anisotropy power spectra. The resultant power spectra are peaked. The derived weighted-mean CMB anisotropy power spectrum is not a good representation of the individual measurements in a number of multipole-space bins, if the CMB anisotropy is Gaussian and correlations between individual measurements are small. This could mean that some observational error bars are underestimated, possibly as a consequence of undetected systematic effects. Discarding the most discrepant 5% of the measurements alleviates but does not completely resolve this problem. The median-statistics power spectrum of this culled data set is not as constraining as the weighted-mean power spectrum. Nevertheless it indicates that there is more power at multipoles $\ell \sim 150-250$ than is expected in an open cold dark matter (CDM) model, and it is more consistent with a flat CDM model. Unlike the weighted-mean power spectrum, the median-statistics power spectrum at $\ell \sim 400-500$ does not exclude a second peak in the flat CDM model.

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arXiv2000

Median Statistics, H_0, and the Accelerating Universe

(Abridged) We develop median statistics that provide powerful alternatives to chi-squared likelihood methods and require fewer assumptions about the data. Applying median statistics to Huchra's compilation of nearly all estimates of the Hubble constant, we find a median value H_0=67 km/s/Mpc. Median statistics assume only that the measurements are independent and free of systematic errors. This estimate is arguably the best summary of current knowledge because it uses all available data and, unlike other estimates, makes no assumption about the distribution of measurement errors. The 95% range of purely statistical errors is +/- 2 km/s/Mpc. The statistical precision of this result leads us to analyze the range of possible systematic errors in the median, which we estimate to be roughly +/- 5 km/s/Mpc (95% limits), dominating over the statistical errors. A Bayesian median statistics treatment of high-redshift Type Ia supernovae (SNe Ia) apparent magnitude versus redshift data from Riess et al. yields a posterior probability that the cosmological constant Lambda > 0 of 70 or 89%, depending on the prior information used. The posterior probability of an open universe is about 47%. Analysis of the Perlmutter et al. high-redshift SNe Ia data show the best-fit flat-Lambda model favored over the best-fit Lambda = 0 open model by odds of 366:1; corresponding Riess et al. odds are 3:1 (assuming prior odds of 1:1).Median statistics analyses of the SNe Ia data do not rule out a time-variable Lambda model, and may even favor it over a time-independent Lambda and a Lambda = 0 open model.

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arXiv1998

Toward High-Precision Measures of Large-Scale Structure

I review some results of estimation of the power spectrum of density fluctuations from galaxy redshift surveys and discuss advances that may be possible with the Sloan Digital Sky Survey. I then examine the realities of power spectrum estimation in the presence of Galactic extinction, photometric errors, galaxy evolution, clustering evolution, and uncertainty about the background cosmology.

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arXiv1997

Fluctuations in the Extragalactic Background Light: Analysis of the Hubble Deep Field

(Abridged) Statistical analysis of the unresolved light in the Hubble Deep Field (HDF) strongly constrains possible sources of the optical Extragalactic Background Light (EBL). To test for the statistical signature of previously undetected sources, we estimate the auto, cross, and color correlations of the ``sky'' in the HDF that remains after masking objects brighter than I=30 mag. This measurement yields the most stringent limits to date on small-scale structure in the night sky; analysis of shallower imaging would be dominated by galaxies now detected by the HDF. Unless there is a truly uniform optical background, the mean EBL is likely to be within a small fraction of the surface brightness from detected galaxies. No currently plausible sources of additional EBL satisfy the constraints that they (1) would not have already been detected, (2) contribute EBL comparable to that from detected galaxies, and (3) do not produce EBL fluctuations in excess of the upper limits set by correlations in the HDF.

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arXiv1996

Eigenmode Analysis of Galaxy Redshift Surveys I. Theory and Methods

We describe a method for estimating the power spectrum of density fluctuations from galaxy redshift surveys that yields improvement in both accuracy and resolution over direct Fourier analysis. The key feature of this analysis is expansion of the observed density field in the unique set of statistically orthogonal spatial functions which obtains for a given survey's geometry and selection function and the known properties of galaxy clustering (the Karhunen-Loeve transform). Each of these eigenmodes of the observed density field optimally weights the data to yield the cleanest (highest signal/noise) possible measure of clustering power as a function of wavelength scale for any survey. Using Bayesian methods, we simultaneously estimate the mean density, power spectrum of density fluctuations, and redshift distortion parameters that best fit the observed data. This method is particularly important for analysis of surveys with small sky coverage, that are comprised of disjoint regions (e.g., an ensemble of pencil beams or slices), or that have large fluctuations in sampling density. We present algorithms for practical application of this technique to galaxy survey data.

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arXiv1995

The Power Spectrum of Galaxy Density Fluctuations: Current Results and Improved Techniques

The power spectrum of density fluctuations measured from galaxy redshift surveys provides important constraints on models for the formation of large-scale structure. I review current results for the 3-D power spectrum and examine the limitations of current measurements and estimation techniques. To span the decade of wavelength between the scales probed by galaxy surveys and COBE, measure the detailed shape of the power spectrum, and accurately examine the dependence of clustering on galaxy species, we require deeper samples with carefully controlled selection criteria and improved techniques for power spectrum estimation. I describe a new method for estimating the power spectrum that optimally treats survey data with arbitrary geometry and sampling.

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arXiv1994

Constraints on Cosmological Models from Once and Future Redshift Surveys

The power spectrum of density fluctuations measured from galaxy redshift surveys provides important constraints on models for the formation of large-scale structure. I present new results for a redshift sample of 15,000 galaxies, and review the limitations of current measurements. To span the decade of wavelength between the scales probed by galaxy surveys and COBE, measure the detailed shape of the power spectrum, and accurately examine the dependence of clustering on galaxy species, we require deeper samples with carefully controlled selection criteria and improved techniques for power spectrum estimation. I review plans for the Sloan Digital Sky Survey and describe a new method for estimating the power spectrum that optimally treats survey data with arbitrary geometry and sampling.

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