Using data from the Sloan Digital Sky Supernova Survey-II (SDSS-II SN Survey), we measure the rate of Type Ia supernovae (SNe Ia) as a function of galaxy properties at intermediate redshift. A sample of 342 SNe Ia with 0.05 < z < 0.25 is constructed. Using broadband photometry and redshifts, we use the PEGASE. 2 spectral energy distributions to estimate host galaxy stellar masses and recent star formation rates (SFRs). We find that the rate of SNe Ia per unit stellar mass is significantly higher (by a factor of similar to 30) in highly star-forming galaxies compared to passive galaxies. When parameterizing the SN Ia rate (SNRIa) based on host galaxy properties, we find that the rate of SNe Ia in passive galaxies is not linearly proportional to the stellar mass; instead an SNRIa proportional to M-0.68 is favored. However, such a parameterization does not describe the observed SNRIa in star-forming galaxies. The SNRIa in star-forming galaxies is well fitted by SNRIa = (0.41 +/- 0.15) x 10(-10) M0.72+/-0.15 + (0.65 +/- 0.25) x 10(-3) SFR1.01+/-0.22 (statistical errors only), where M is the host galaxy stellar mass (in M-circle dot) and SFR is the SFR (in M-circle dot yr(-1)). We show that our results, for SNe Ia in passive galaxies, are consistent with those at higher redshifts (favoring SNRIa proportional to M) when accounting for the difference in the ages of our galaxies. This suggests that the rate of SNe Ia is correlated with the age of the stellar population. The MLCS extinction parameter, A(V), is similar in passive and moderately star-forming galaxies, but we find indications that it is smaller, on average, in highly star-forming galaxies. This result appears to be driven by a deficit of the reddest (A(V) > 0.15) SNe Ia in highly star-forming galaxies. We consider that the high levels of dust in these systems may be obscuring the reddest and faintest SNe Ia.

Type Ia supernovae have been used empirically as 'standard candles' to demonstrate the acceleration of the expansion of the Universe even though fundamental details, such as the nature of their progenitor systems and how the stars explode, remain a mystery. There is consensus that a white dwarf star explodes after accreting matter in a binary system, but the secondary body could be anything from a main-sequence star to a red giant, or even another white dwarf. This uncertainty stems from the fact that no recent type Ia supernova has been discovered close enough to Earth to detect the stars before explosion. Here we report early observations of supernova SN 2011fe in the galaxy M101 at a distance from Earth of 6.4 megaparsecs. We find that the exploding star was probably a carbon-oxygen white dwarf, and from the lack of an early shock we conclude that the companion was probably a main-sequence star. Early spectroscopy shows high-velocity oxygen that slows rapidly, on a timescale of hours, and extensive mixing of newly synthesized intermediate-mass elements in the outermost layers of the supernova. A companion paper uses pre-explosion images to rule out luminous red giants and most helium stars as companions to the progenitor.

We analyze the three-year SDSS-II Superernova (SN) Survey data and identify a sample of 1070 photometric SN Ia candidates based on their multi-band light curve data. This sample consists of SN candidates with no spectroscopic confirmation, with a subset of 210 candidates having spectroscopic redshifts of their host galaxies measured, while the remaining 860 candidates are purely photometric in their identification. We describe a method for estimating the efficiency and purity of photometric SN Ia classification when spectroscopic confirmation of only a limited sample is available, and demonstrate that SN Ia candidates from SDSS-II can be identified photometrically with ~91% efficiency and with a contamination of ~6%. Although this is the largest uniform sample of SN candidates to date for studying photometric identification, we find that a larger spectroscopic sample of contaminating sources is required to obtain a better characterization of the background events. A Hubble diagram using SN candidates with no spectroscopic confirmation, but with host galaxy spectroscopic redshifts, yields a distance modulus dispersion that is only ~20 - 40% larger than that of the spectroscopically-confirmed SN Ia sample alone with no significant bias. A Hubble diagram with purely photometric classification and redshift-distance measurements, however, exhibit biases that require further investigation for precision cosmology.

We present measurements of the Type Ia supernova (SN) rate in galaxy clusters based on data from the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey. The cluster SN Ia rate is determined from 9 SN events in a set of 71 C4 clusters at z <= 0.17 and 27 SN events in 492 maxBCG clusters at 0.1 <= z <= 0.3. We find values for the cluster SN Ia rate of (0.37(-0.12-0.01)(+0.17+0.01)) SNur h(2) and (0.55(-0.11-0.01)(+0.13+0.02)) SNur h(2) (SNux = 10(-12) Lx(circle dot)(-1)yr(-1)) in C4 and maxBCG clusters, respectively, where the quoted errors are statistical and systematic, respectively. The SN rate for early-type galaxies is found to be (0.31(-0.12-0.01)(+0.18+0.01)) SNur h(2) and (0.49(-0.11-0.01)(+0.15+0.02)) SNur h(2) in C4 and maxBCG clusters, respectively. The SN rate for the brightest cluster galaxies (BCG) is found to be (2.04(-1.11-0.04)(+1.99+0.07)) SNur h(2) and (0.36(-0.30-0.01)(+0.84+0.01)) SNur h(2) in C4 and maxBCG clusters, respectively. The ratio of the SN Ia rate in cluster early-type galaxies to that of the SN Ia rate in field early-type galaxies is 1.94(-0.91-0.015)(+1.31+0.043) and 3.02(-1.03-0.048)(+1.31+0.062), for C4 and maxBCG clusters, respectively. The SN rate in galaxy clusters as a function of redshift, which probes the late time SN Ia delay distribution, shows only weak dependence on redshift. Combining our current measurements with previous measurements, we fit the cluster SN Ia rate data to a linear function of redshift, and find r(L) =[(0.49(-0.14)(+0.15))+(0.91(-0.81)(+0.85)) x z] SNuB h(2). A comparison of the radial distribution of SNe in cluster to field early-type galaxies shows possible evidence for an enhancement of the SN rate in the cores of cluster early-type galaxies. With an observation of at most three hostless, intra-cluster SNe Ia, we estimate the fraction of cluster SNe that are hostless to be (9.4(-5.1)(+8.3))%.

We present an analysis of the host galaxy dependences of Type Ia Supernovae (SNe Ia) from the full three year sample of the SDSS-II Supernova Survey. We re-discover, to high significance, the strong correlation between host galaxy type and the width of the observed SN light curve, i. e., fainter, quickly declining SNe Ia favor passive host galaxies, while brighter, slowly declining Ia's favor star-forming galaxies. We also find evidence (at between 2 sigma and 3 sigma) that SNe Ia are similar or equal to 0.1 +/- 0.04 mag brighter in passive host galaxies than in star-forming hosts, after the SN Ia light curves have been standardized using the light-curve shape and color variations. This difference in brightness is present in both the SALT2 and MCLS2k2 light-curve fitting methodologies. We see evidence for differences in the SN Ia color relationship between passive and star-forming host galaxies, e.g., for the MLCS2k2 technique, we see that SNe Ia in passive hosts favor a dust law of R(V) = 1.0 +/- 0.2, while SNe Ia in star-forming hosts require R(V) = 1.8+(0.2)(0.4). The significance of these trends depends on the range of SN colors considered. We demonstrate that these effects can be parameterized using the stellar mass of the host galaxy (with a confidence of > 4 sigma) and including this extra parameter provides a better statistical fit to our data. Our results suggest that future cosmological analyses of SN Ia samples should include host galaxy information.

We apply the Standardized Candle Method (SCM) for Type II Plateau supernovae (SNe II-P), which relates the velocity of the ejecta of a SN to its luminosity during the plateau, to 15 SNe II-P discovered over the three season run of the Sloan Digital Sky Survey-II Supernova Survey. The redshifts of these SNe-0.027 < z < 0.144-cover a range hitherto sparsely sampled in the literature; in particular, our SNe II-P sample contains nearly as many SNe in the Hubble flow (z > 0.01) as all of the current literature on the SCM combined. We find that the SDSS SNe have a very small intrinsic I-band dispersion (0.22 mag), which can be attributed to selection effects. When the SCM is applied to the combined SDSS-plus-literature set of SNe II-P, the dispersion increases to 0.29 mag, larger than the scatter for either set of SNe separately. We show that the standardization cannot be further improved by eliminating SNe with positive plateau decline rates, as proposed in Poznanski et al. We thoroughly examine all potential systematic effects and conclude that for the SCM to be useful for cosmology, the methods currently used to determine the Fe II velocity at day 50 must be improved, and spectral templates able to encompass the intrinsic variations of Type II-P SNe will be needed.

We present ameasurement of the volumetric Type Ia supernova (SN Ia) rate based on data from the Sloan Digital Sky Survey II (SDSS-II) Supernova Survey. The adopted sample of supernovae (SNe) includes 516 SNe Ia at redshift z less than or similar to 0.3, of which 270(52%) are spectroscopically identified as SNe Ia. The remaining 246 SNe Ia were identified through their light curves; 113 of these objects have spectroscopic redshifts from spectra of their host galaxy, and 133 have photometric redshifts estimated from the SN light curves. Based on consideration of 87 spectroscopically confirmed non-Ia SNe discovered by the SDSS-II SN Survey, we estimate that 2.04+(1.61%)(-0.95) -0.95% of the photometric SNe Ia may be misidentified. The sample of SNe Ia used in this measurement represents an order of magnitude increase in the statistics for SN Ia rate measurements in the redshift range covered by the SDSS-II Supernova Survey. If we assume an SN Ia rate that is constant at low redshift (z < 0.15), then the SN observations can be used to infer a value of the SN rate of rV = (2.69(-0.30-0.01)(+ 0.34+ 0.21)) x 10(-5) SNe yr(-1) Mpc(-3) (H-0/(70 km s(-1) Mpc(-1)))(3) at a mean redshift of similar to 0.12, based on 79 SNe Ia of which 72 are spectroscopically confirmed. However, the large sample of SNe Ia included in this study allows us to place constraints on the redshift dependence of the SN Ia rate based on the SDSS-II Supernova Survey data alone. Fitting a power-law model of the SN rate evolution, rV (z) = A(p) x((1 + z)/(1 + z(0)))(nu), over the redshift range 0.0 < z < 0.3 with z0 = 0.21, results in A(p) = (3.43+(+0.15)(-.015) SNe yr-1 Mpc-3 (H-0/(70 km s(-1) Mpc(-1)))(3) and nu = 2.04(-0.89)(+0.89).

From the set of nearly 500 spectroscopically confirmed type~Ia supernovae and around 10,000 unconfirmed candidates from SDSS-II, we select a subset of 108 confirmed SNe Ia with well-observed early-time light curves to search for signatures from shock interaction of the supernova with a companion star. No evidence for shock emission is seen; however, the cadence and photometric noise could hide a weak shock signal. We simulate shocked light curves using SN Ia templates and a simple, Gaussian shock model to emulate the noise properties of the SDSS-II sample and estimate the detectability of the shock interaction signal as a function of shock amplitude, shock width, and shock fraction. We find no direct evidence for shock interaction in the rest-frame $B$-band, but place an upper limit on the shock amplitude at 9% of supernova peak flux ($M_B > -16.6$ mag). If the single degenerate channel dominates type~Ia progenitors, this result constrains the companion stars to be less than about 6 $M_{\odot}$ on the main sequence, and strongly disfavors red giant companions.

We analyze the rise and fall times of type Ia supernova (SN Ia) light curves discovered by the SDSS-II Supernova Survey. From a set of 391 light curves k-corrected to the rest frame B and V bands, we find a smaller dispersion in the rising portion of the light curve compared to the decline. This is in qualitative agreement with computer models which predict that variations in radioactive nickel yield have less impact on the rise than on the spread of the decline rates. The differences we find in the rise and fall properties suggest that a single 'stretch' correction to the light curve phase does not properly model the range of SN Ia light curve shapes. We select a subset of 105 light curves well-observed in both rise and fall portions of the light curves and develop a '2-stretch' fit algorithm which estimates the rise and fall times independently. We find the average time from explosion to B-band peak brightness is 17.38 +/- 0.17 days. Our average rise time is shorter than the 19.5 days found in previous studies; this reflects both the different light curve template used and the application of the 2-stretch algorithm. We find that slow declining events tend to have fast rise times, but that the distribution of rise minus fall time is broad and single-peaked. This distribution is in contrast to the bimodality in this parameter that was first suggested by Strovink (2007) from an analysis of a small set of local SNe Ia. We divide the SDSS-II sample in half based on the rise minus fall value, tr-tf <= 2 days and tr-tf>2 days, to search for differences in their host galaxy properties and Hubble residuals; we find no difference in host galaxy properties or Hubble residuals in our sample.

Large planned photometric surveys will discover hundreds of thousands of supernovae (SNe), outstripping the resources available for spectroscopic follow-up and necessitating the development of purely photometric methods to exploit these events for cosmological study. We present a light-curve fitting technique for SN Ia photometric redshift (photo-z) estimation in which the redshift is determined simultaneously with the other fit parameters. We implement this "LCFIT+Z" technique within the frameworks of the MLCS2k2 and SALT-II light-curve fit methods and determine the precision on the redshift and distance modulus. This method is applied to a spectroscopically confirmed sample of 296 SNe Ia from the SDSS-II Supernova Survey and 37 publicly available SNe Ia from the Supernova Legacy Survey (SNLS). We have also applied the method to a large suite of realistic simulated light curves for existing and planned surveys, including SDSS, SNLS, and LSST. When intrinsic SN color fluctuations are included, the photo-z precision for the simulation is consistent with that in the data. Finally, we compare the LCFIT+Z photo-z precision with previous results using color-based SN photo-z estimates.

We describe a general analysis package for supernova (SN) light curves, called SNANA, that contains a simulation, a light-curve fitter, and a cosmology fitter. The software is designed with the primary goal of using SNe Ia as distance indicators for the determination of cosmological parameters, but it can also be used to study efficiencies for analyses of SN rates, estimate contamination from non-Ia SNe, and optimize future surveys. Several SN models are available within the same software architecture, allowing technical features such as K-corrections to be consistently used among multiple models, and thus making it easier to make detailed comparisons between models. New and improved light-curve models can be easily added. The software works with arbitrary surveys and telescopes and has already been used by several collaborations, leading to more robust and easy-to-use code. This software is not intended as a final product release, but rather it is designed to undergo continual improvements from the community as more is learned about SNe. We give an overview of the SNANA capabilities, as well as some of its limitations.

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. We combine the SDSS-II measurements with new distance estimates for published SN data from the ESSENCE survey, the Supernova Legacy Survey, the Hubble Space Telescope, and a compilation of nearby SN Ia measurements. Combining the SN Hubble diagram with measurements of Baryon Acoustic Oscillations from the SDSS Luminous Red Galaxy sample and with CMB temperature anisotropy measurements from WMAP, we estimate the cosmological parameters w and Omega_M, assuming a spatially flat cosmological model (FwCDM) with constant dark energy equation of state parameter, w. For the FwCDM model and the combined sample of 288 SNe Ia, we find w = -0.76 +- 0.07(stat) +- 0.11(syst), Omega_M = 0.306 +- 0.019(stat) +- 0.023(syst) using MLCS2k2 and w = -0.96 +- 0.06(stat) +- 0.12(syst), Omega_M = 0.265 +- 0.016(stat) +- 0.025(syst) using the SALT-II fitter. We trace the discrepancy between these results to a difference in the rest-frame UV model combined with a different luminosity correction from color variations; these differences mostly affect the distance estimates for the SNLS and HST supernovae. We present detailed discussions of systematic errors for both light-curve methods and find that they both show data-model discrepancies in rest-frame $U$-band. For the SALT-II approach, we also see strong evidence for redshift-dependence of the color-luminosity parameter (beta). Restricting the analysis to the 136 SNe Ia in the Nearby+SDSS-II samples, we find much better agreement between the two analysis methods but with larger uncertainties.

We report the discovery of a minor planet (2006 SQ372) on an orbit with a perihelion of 24 AU and a semimajor axis of 796 AU. Dynamical simulations show that this is a transient orbit and is unstable on a timescale of ∼200 Myr. Falling near the upper semimajor axis range of the scattered disk and the lower semimajor axis range of the Oort Cloud, previous membership in either class is possible. By modeling the production of similar orbits from the Oort Cloud as well as from the scattered disk, we find that the Oort Cloud produces 16 times as many objects on SQ372-like orbits as the scattered disk. Given this result, we believe this to be the most distant long-period comet (LPC) ever discovered. Furthermore, our simulation results also indicate that 2000 OO67 has had a similar dynamical history. Unaffected by the "Jupiter–Saturn Barrier," these two objects are most likely LPCs from the inner Oort Cloud.