We present measurements of the Hubble diagram for 103 Type Ia supernovae (SNe) with redshifts 0.04 < z < 0.42, discovered during the first season (Fall 2005) of the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey. These data fill in the redshift "desert" between low-and high-redshift SN Ia surveys. Within the framework of the mlcs2k2 light-curve fitting method, we use the SDSS-II SN sample to infer the mean reddening parameter for host galaxies, R V = 2.18 ± 0.14 stat ± 0.48 syst , and find that the intrinsic distribution of host-galaxy extinction is well fitted by an exponential function, P (A V) = exp(−A V /τ V), with τ V = 0.334 ± 0.088 mag. We combine the SDSS-II measurements with new distance estimates for published SN data from the ESSENCE survey, the Supernova Legacy Survey (SNLS), the Hubble Space Telescope (HST), and a compilation of Nearby SN Ia measurements. A new feature in our analysis is the use of detailed Monte Carlo simulations of all surveys to account for selection biases, including those from spectroscopic targeting. Combining the SN Hubble diagram with measurements of baryon acoustic oscillations from the SDSS Luminous Red Galaxy sample and with cosmic microwave background temperature anisotropy measurements from the Wilkinson Microwave Anisotropy Probe, we estimate the cosmological parameters w and Ω M , assuming a spatially flat cosmological model (FwCDM) with constant dark energy equation of state parameter, w. We also consider constraints upon Ω M and Ω Λ for a cosmological constant model (ΛCDM) with w = −1 and non-zero spatial curvature. For the FwCDM model and the combined sample of 288 SNe Ia,

We present constraints on the dark energy equation-of-state parameter, w ¼ P/( c 2 ), using 60 SNe Ia from the ESSENCE supernova survey. We derive a set of constraints on the nature of the dark energy assuming a flat universe. By including constraints on ( M , w) from baryon acoustic oscillations, we obtain a value for a static equation-of-state parameter w ¼ À1:05 þ0:13 À0:12 (stat 1 ) AE 0:13 (sys) and M ¼ 0:274 þ0:033 À0:020 (stat 1 ) with a bestfit 2 /dof of 0.96. These results are consistent with those reported by the Supernova Legacy Survey from the first year of a similar program measuring supernova distances and redshifts. We evaluate sources of systematic error that afflict supernova observations and present Monte Carlo simulations that explore these effects. Currently, the largest systematic with the potential to affect our measurements is the treatment of extinction due to dust in the supernova host galaxies. Combining our set of ESSENCE SNe Ia with the first-results Supernova Legacy Survey SNe Ia, we obtain a joint constraint of w ¼ À1:07 þ0:09 À0:09 (stat 1 ) AE 0:13 (sys), M ¼ 0:267 þ0:028 À0:018 (stat 1 ) with a best-fit 2 /dof of 0.91. The current global SN Ia data alone rule out empty ( M ¼ 0), matter-only M ¼ 0:3, and M ¼ 1 universes at >4.5 . The current SN Ia data are fully consistent with a cosmological constant.

In addition to optical photometry of unprecedented quality, the Sloan Digital Sky Survey (SDSS) is producing a massive spectroscopic database which already contains over 280,000 stellar spectra. Using effective temperature and metallicity derived from SDSS spectra for ∼60,000 F and G type main sequence stars (0.2 < g − r < 0.6), we develop polynomial models, reminiscent of traditional methods based on the U BV photometry, for estimating these parameters from the SDSS u−g and g−r colors. These estimators reproduce SDSS spectroscopic parameters with a root-mean-square scatter of 100 K for effective temperature, and 0.2 dex for metallicity (limited by photometric errors), which are similar to random and systematic uncertainties in spectroscopic determinations. We apply this method to a photometric catalog of coadded SDSS observations and study the photometric metallicity distribution of ∼200,000 F and G type stars observed in 300 deg 2 of high Galactic latitude sky. These deeper (g < 20.5) and photometrically precise (∼0.01 mag) coadded data enable an accurate measurement of the unbiased metallicity distribution for a complete volume-limited sample of stars at distances between 500 pc and 8 kpc. The metallicity distribution can be exquisitely modeled using two components with a spatially varying number ratio, that correspond to disk and halo. The best-fit number ratio of the two components is consistent with that implied by the decomposition of stellar counts profiles into exponential disk and power-law halo components by Jurić et al. (2008). The two components also possess the kinematics expected for disk and halo stars. The metallicity of the halo component can be modeled as a spatially invariant Gaussian distribution with a mean of [F e/H] = −1.46 and a standard deviation of ∼0.3 dex. The disk metallicity distribution is non-Gaussian, with a remarkably small scatter (rms∼0.16 dex) and the median smoothly decreasing with distance from the plane from −0.6 at 500 pc to −0.8 beyond several kpc. Similarly, we find using proper motion measurements that a non-Gaussian rotational velocity distribution of disk stars shifts by ∼50 km/s as the distance from the plane increases from 500 pc to several kpc. Despite this similarity, the metallicity and rotational velocity distributions of disk stars are not correlated (Kendall's τ = 0.017 ± 0.018). This absence of a correlation between metallicity and kinematics for disk stars is in a conflict with the traditional decomposition in terms of thin and thick disks, which predicts a strong correlation (τ = −0.30 ± 0.04) at ∼1 kpc from the mid-plane. Instead, the variation of the metallicity and rotational velocity distributions can be modeled using non-Gaussian functions that retain their shapes and only shift as the distance from the mid-plane increases. We also study the metallicity distribution using a shallower (g < 19.5) but much larger sample of close to three million stars in 8500 sq. deg. of sky included in SDSS Data Release 6. The large sky coverage enables the detection of...