We measure cosmological parameters using the three-dimensional power spectrum P (k) from over 200,000 galaxies in the Sloan Digital Sky Survey (SDSS) in combination with WMAP and other data. Our results are consistent with a "vanilla" flat adiabatic ΛCDM model without tilt (ns = 1), running tilt, tensor modes or massive neutrinos. Adding SDSS information more than halves the WMAP-only error bars on some parameters, tightening 1σ constraints on the Hubble parameter from h ≈ 0.74−0.03 , on the matter density from Ωm ≈ 0.25 ± 0.10 to Ωm ≈ 0.30 ± 0.04 (1σ) and on neutrino masses from < 11 eV to < 0.6 eV (95%). SDSS helps even more when dropping prior assumptions about curvature, neutrinos, tensor modes and the equation of state. Our results are in substantial agreement with the joint analysis of WMAP and the 2dF Galaxy Redshift Survey, which is an impressive consistency check with independent redshift survey data and analysis techniques. In this paper, we place particular emphasis on clarifying the physical origin of the constraints, i.e., what we do and do not know when using different data sets and prior assumptions. For instance, dropping the assumption that space is perfectly flat, the WMAP-only constraint on the measured age of the Universe tightens from t0 ≈ 16.3 +2.3 −1.8 Gyr to t0 ≈ 14.1Gyr by adding SDSS and SN Ia data. Including tensors, running tilt, neutrino mass and equation of state in the list of free parameters, many constraints are still quite weak, but future cosmological measurements from SDSS and other sources should allow these to be substantially tightened.

The Sloan Digital Sky Survey (SDSS) is an imaging and spectroscopic survey that will eventually cover approximately one-quarter of the celestial sphere and collect spectra of %10 6 galaxies, 100,000 quasars, 30,000 stars, and 30,000 serendipity targets. In 2001 June, the SDSS released to the general astronomical community its early data release, roughly 462 deg 2 of imaging data including almost 14 million detected objects and 54,008 follow-up spectra. The imaging data were collected in drift-scan mode in five bandpasses (u, g, r, i, and z); our 95% completeness limits for stars are 22.0, 22.2, 22.2, 21.3, and 20.5, respectively. The photometric calibration is reproducible to 5%, 3%, 3%, 3%, and 5%, respectively. The spectra are flux-and wavelength-calibrated, with 4096 pixels from 3800 to 9200 Å at R % 1800. We present the means by which these data are distributed to the astronomical community, descriptions of the hardware used to obtain the data, the software used for processing the data, the measured quantities for each observed object, and an overview of the properties of this data set.

We present ACS, NICMOS, and Keck AO-assisted photometry of 20 Type Ia supernovae (SNe Ia) from the HST Cluster Supernova Survey. The SNe Ia were discovered over the redshift interval 0.623 < z < 1.415. Fourteen of these SNe Ia pass our strict selection cuts and are used in combination with the world's sample of SNe Ia to derive the best current constraints on dark energy. Ten of our new SNe Ia are beyond redshift z = 1, thereby nearly doubling the statistical weight of HST-discovered SNe Ia beyond this redshift. Our detailed analysis corrects for the recently identified correlation between SN Ia luminosity and host galaxy mass and corrects the NICMOS zeropoint at the count rates appropriate for very distant SNe Ia. Adding these supernovae improves the best combined constraint on dark energy density, ρ DE (z), at redshifts 1.0 < z < 1.6 by 18% (including systematic errors). For a flat ΛCDM universe, we find Ω Λ = 0.729 +0.014 −0.014 (68% CL including systematic errors). For a flat wCDM model, we measure a constant dark energy equation-of-state parameter w = −1.013 +0.068 −0.073 (68% CL). Curvature is constrained to ∼ 0.7% in the owCDM model and to ∼ 2% in a model in which dark energy is allowed to vary with parameters w 0 and w a . Tightening further the constraints on the time evolution of dark energy will require several improvements, including high-quality multi-passband photometry of a sample of several dozen z > 1 SNe Ia. We describe how such a sample could be efficiently obtained by targeting cluster fields with WFC3 on HST.The updated supernova Union2.1 compilation of 580 SNe is available at http://supernova.lbl.gov/Union ⋆ is less than the mass threshold. We begin by noting that.We can then integrate this probability over all true host masses less than the threshold:⋆ )P (m true ⋆ ) up to a normalization constant found by requiring the integral to be unity when integrating over all possible true masses. P (m true ⋆ ) is estimated from the observed distribution for each type of survey. The SNLS (Sullivan et al. 2010) and SDSS (Lampeitl et al. 2010) host masses were assumed to be representative of untargeted surveys, while the mass distribution in Kelly et al. (2010) was assumed typical of nearby targeted surveys. As these distributions are approximately log-normal, we use this model for P (m true ⋆) using the mean and RMS from the log of the host masses from these surveys (with the average measurement errors subtracted in quadrature), giving log 10 P (m true ⋆ ) = N (µ = 9.88, σ 2 = 0.92 2 ) for untargeted surveys and log 10 P (m true ⋆ ) = N (10.75, 0.66 2 ) for targeted surveys. When host mass measurements are available, P (m obs ⋆ |m true ⋆ ) is also modeled as a log-normal; when no measurement is available, a flat distribution is used.For a supernova from an untargeted survey with no host mass measurement (including supernovae presented in this paper which are not in a cluster), P (m trueis the integral of P (m true ⋆ ) up to the threshold mass: 0.55. Similarly, nearby supernovae from targeted surveys w...

We measure the large-scale real-space power spectrum P (k) using a sample of 205,443 galaxies from the Sloan Digital Sky Survey, covering 2417 effective square degrees with mean redshift z ≈ 0.1. We employ a matrix-based method using pseudo-Karhunen-Loève eigenmodes, producing uncorrelated minimumvariance measurements in 22 k-bands of both the clustering power and its anisotropy due to redshift-space distortions, with narrow and well-behaved window functions in the range 0.02 h/Mpc < k < 0.3 h/Mpc. We pay particular attention to modeling, quantifying and correcting for potential systematic errors, nonlinear redshift distortions and the artificial red-tilt caused by luminosity-dependent bias. Our results are robust to omitting angular and radial density fluctuations and are consistent between different parts of the sky. Our final result is a measurement of the real-space matter power spectrum P (k) up to an unknown overall multiplicative bias factor. Our calculations suggest that this bias factor is independent of scale to better than a few percent for k < 0.1 h/Mpc, thereby making our results useful for precision measurements of cosmological parameters in conjunction with data from other experiments such as the WMAP satellite. The power spectrum is not well-characterized by a single power law, but unambiguously shows curvature. As a simple characterization of the data, our measurements are well fit by a flat scaleinvariant adiabatic cosmological model with hΩ m = 0.213 ± 0.023 and σ 8 = 0.89 ± 0.02 for L * galaxies, when fixing the baryon fraction Ω b /Ω m = 0.17 and the Hubble parameter h = 0.72; cosmological interpretation is given in a companion paper.

We measure the large-scale real-space power spectrum P (k) using luminous red galaxies (LRGs) in the Sloan Digital Sky Survey (SDSS) and use this measurement to sharpen constraints on cosmological parameters from the Wilkinson Microwave Anisotropy Probe (WMAP). We employ a matrix-based power spectrum estimation method using Pseudo-Karhunen-Loève eigenmodes, producing uncorrelated minimum-variance measurements in 20 k-bands of both the clustering power and its anisotropy due to redshift-space distortions, with narrow and well-behaved window functions in the range 0.01 h/Mpc < k < 0.2 h/Mpc. Results from the LRG and main galaxy samples are consistent, with the former providing higher signal-to-noise. Our results are robust to omitting angular and radial density fluctuations and are consistent between different parts of the sky. They provide a striking confirmation of the predicted large-scale ΛCDM power spectrum. Combining only SDSS LRG and WMAP data places robust constraints on many cosmological parameters that complement prior analyses of multiple data sets. The LRGs provide independent cross-checks on Ωm and the baryon fraction in good agreement with WMAP. Within the context of flat ΛCDM models, our LRG measurements complement WMAP by sharpening the constraints on the matter density, the neutrino density and the tensor amplitude by about a factor of two, giving Ωm = 0.24±0.02 (1σ), mν ∼ < 0.9 eV (95%) and r < 0.3 (95%). Baryon oscillations are clearly detected and provide a robust measurement of the comoving distance to the median survey redshift z = 0.35 independent of curvature and dark energy properties. Within the ΛCDM framework, our power spectrum measurement improves the evidence for spatial flatness, sharpening the curvature constraint Ωtot = 1.05±0.05 from WMAP alone to Ωtot = 1.003 ± 0.010. Assuming Ωtot = 1, the equation of state parameter is constrained to w = −0.94 ± 0.09, indicating the potential for more ambitious future LRG measurements to provide precision tests of the nature of dark energy. All these constraints are essentially independent of scales k > 0.1h/Mpc and associated nonlinear complications, yet agree well with more aggressive published analyses where nonlinear modeling is crucial. k [h/Mpc] Power Pg 0.012 +0.005 −0.004 124884 ± 18775 0.015 +0.003 −0.002 118814 ± 29400 0.018 +0.004 −0.002 134291 ± 21638 0.021 +0.004 −0.003 58644 ± 16647 0.024 +0.004 −0.003 105253 ± 12736 0.028 +0.005 −0.003 77699 ± 9666 0.032 +0.005 −0.003 57870 ± 7264 0.037 +0.006 −0.004 56516 ± 5466 0.043 +0.008 −0.006 50125 ± 3991 0.049 +0.008 −0.007 45076 ± 2956 0.057 +0.009 −0.007 39339 ± 2214 0.065 +0.010 −0.008 39609 ± 1679 0.075 +0.011 −0.009 31566 ± 1284 0.087 +0.

We present a catalog of galaxy clusters selected using the maxBCG red-sequence method from Sloan Digital Sky Survey photometric data. This catalog includes 13,823 clusters with velocity dispersions greater than %400 km s À1 and is the largest galaxy cluster catalog assembled to date. They are selected in an approximately volume-limited way from a 0.5 Gpc 3 region covering 7500 deg 2 of sky between redshifts 0.1 and 0.3. Each cluster contains between 10 and 190 E/S0 ridgeline galaxies brighter than 0.4L Ã within a scaled radius R 200 . The tight relation between ridgeline color and redshift provides an accurate photometric redshift estimate for every cluster. Photometric redshift errors are shown by comparison to spectroscopic redshifts to be small (Á z ' 0:01), essentially independent of redshift, and well determined throughout the redshift range. Runs of maxBCG on realistic mock catalogs suggest that the sample is more than 90% pure and more than 85% complete for clusters with masses !1 ; 10 14 M . Spectroscopic measurements of cluster members are used to examine line-of-sight projection as a contaminant in the identification of brightest cluster galaxies and cluster member galaxies. Spectroscopic data are also used to demonstrate the correlation between optical richness and velocity dispersion. Comparison to the combined NORAS and REFLEX X-rayYselected cluster catalogs shows that X-rayYluminous clusters are found among the optically richer maxBCG clusters. This paper is the first in a series that will consider the properties of these clusters, their galaxy populations, and their implications for cosmology.

We present an algorithm to photometrically calibrate wide-field optical imaging surveys, which simultaneously solves for the calibration parameters and relative stellar fluxes using overlapping observations. The algorithm decouples the problem of ''relative'' calibrations from that of ''absolute'' calibrations; the absolute calibration is reduced to determining a few numbers for the entire survey. We pay special attention to the spatial structure of the calibration errors, allowing one to isolate particular error modes in downstream analyses. Applying this to the SDSS imaging data, we achieve $1% relative calibration errors across 8500 deg 2 in griz; the errors are $2% for the u band. These errors are dominated by unmodeled atmospheric variations at Apache Point Observatory. These calibrations, dubbed ''ubercalibration,'' are now public with SDSS Data Release 6 and will be a part of subsequent SDSS data releases.

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