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Register a new userType II-P Supernovae from the SDSS-II Supernova Survey and the Standardized Candle Method
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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. (2009). 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.
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We present the cosmological analysis of 752 photometrically-classified Type Ia Supernovae (SNe Ia) obtained from the full Sloan Digital Sky Survey II (SDSS-II) Supernova (SN) Survey, supplemented with host-galaxy spectroscopy from the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). Our photometric-classification method is based on the SN typing technique of Sako et al. (2011), aided by host galaxy redshifts (0.05<z<0.55). SNANA simulations of our methodology estimate that we have a SN Ia typing efficiency of 70.8%, with only 3.9% contamination from core-collapse (non-Ia) SNe. We demonstrate that this level of contamination has no effect on our cosmological constraints. We quantify and correct for our selection effects (e.g., Malmquist bias) using simulations. When fitting to a flat LambdaCDM cosmological model, we find that our photometric sample alone gives omega_m=0.24+0.07-0.05 (statistical errors only). If we relax the constraint on flatness, then our sample provides competitive joint statistical constraints on omega_m and omega_lambda, comparable to those derived from the spectroscopically-confirmed three-year Supernova Legacy Survey (SNLS3). Using only our data, the statistics-only result favors an accelerating universe at 99.96% confidence. Assuming a constant wCDM cosmological model, and combining with H0, CMB and LRG data, we obtain w=-0.96+0.10-0.10, omega_m=0.29+0.02-0.02 and omega_k=0.00+0.03-0.02 (statistical errors only), which is competitive with similar spectroscopically confirmed SNe Ia analyses. Overall this comparison is re-assuring, considering the lower redshift leverage of the SDSS-II SN sample (z<0.55) and the lack of spectroscopic confirmation used herein. These results demonstrate the potential of photometrically-classified SNe Ia samples in improving cosmological constraints.
We revisit the observed correlation between Hbeta and FeII velocities for Type II-P supernovae (SNe~II-P) using 28 optical spectra of 13 SNe II-P and demonstrate that it is well modeled by a linear relation with a dispersion of about 300 km/s. Using this correlation, we reanalyze the publicly available sample of SNe II-P compiled by DAndrea et al. and find a Hubble diagram with an intrinsic scatter of 11% in distance, which is nearly as tight as that measured before their sample is added to the existing set. The larger scatter reported in their work is found to be systematic, and most of it can be alleviated by measuring Hbeta rather than FeII velocities, due to the low signal-to-noise ratios and early epochs at which many of the optical spectra were obtained. Their sample, while supporting the mounting evidence that SNe II-P are good cosmic rulers, is biased toward intrinsically brighter objects and is not a suitable set to improve upon SN II-P correlation parameters. This will await a dedicated survey.
We present an analysis of the host galaxy dependencies of Type Ia Supernovae (SNe Ia) from the full three year sample of the SDSS-II Supernova Survey. We rediscover, to high significance, the strong correlation between host galaxy typeand the width of the observed SN light curve, i.e., fainter, quickly declining SNe Ia favor passive host galaxies, while brighter, slowly declining Ias favor star-forming galaxies. We also find evidence (at between 2 to 3 sigma) that SNe Ia are ~0.1 magnitudes 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, while SNe Ia in star-forming hosts require R_V ~2. 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.
The standard candle method for Type II plateau supernovae produces a Hubble diagram with a dispersion of 0.3 mag, which implies that this technique can produce distances with a precision of 15%. Using four nearby supernovae with Cepheid distances I find Ho(V)=75+/-7, and Ho(I)=65+/-12.
We present a measurement 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 lesssim 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 % 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 a 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+0.34+0.21-0.30-0.01) x10^{-5} SNe yr^{-1} Mpc-3 (H0 /(70 km s^{-1} Mpc^{-1}))^{3} at a mean redshift of ~ 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, r_V(z) = A_p x ((1 + z)/(1 + z0))^{ u}, over the redshift range 0.0 < z < 0.3 with z0 = 0.21, results in A_p = (3.43+0.15-0.15) x 10^{-5} SNe yr^{-1} Mpc-3 (H0 /(70 km s^{-1} Mpc^{-1}))^{3} and u = 2.04+0.90-0.89.
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