Jennifer J. Mosher

Improved cosmological constraints from a joint analysis of the SDSS-II and SNLS supernova samples

Aims. We present cosmological constraints from a joint analysis of type Ia supernova (SN Ia) observations obtained by the SDSS-II and SNLS collaborations. The dataset includes several low-redshift samples (z< 0.1), all three seasons from the SDSS-II (0.05 <z< 0.4), and three years from SNLS (0.2 <z< 1), and it totals 740 spectroscopically confirmed type Ia supernovae with high-quality light curves. Methods. We followed the methods and assumptions of the SNLS three-year data analysis except for the following important improvements: 1) the addition of the full SDSS-II spectroscopically-confirmed SN Ia sample in both the training of the SALT2 light-curve model and in the Hubble diagram analysis (374 SNe); 2) intercalibration of the SNLS and SDSS surveys and reduced systematic uncertainties in the photometric calibration, performed blindly with respect to the cosmology analysis; and 3) a thorough investigation of systematic errors associated with the SALT2 modeling of SN Ia light curves. Results. We produce recalibrated SN Ia light curves and associated distances for the SDSS-II and SNLS samples. The large SDSS-II sample provides an effective, independent, low-z anchor for the Hubble diagram and reduces the systematic error from calibration systematics in the low-z SN sample. For a flat ΛCDM cosmology, we find Ωm =0.295 ± 0.034 (stat+sys), a value consistent with the most recent cosmic microwave background (CMB) measurement from the Planck and WMAP experiments. Our result is 1.8σ (stat+sys) different than the previously published result of SNLS three-year data. The change is due primarily to improvements in the SNLS photometric calibration. When combined with CMB constraints, we measure a constant dark-energy equation of state parameter w =−1.018 ± 0.057 (stat+sys) for a flat universe. Adding baryon acoustic oscillation distance measurements gives similar constraints: w =−1.027 ± 0.055. Our supernova measurements provide the most stringent constraints to date on the nature of dark energy.

A More General Model for the Intrinsic Scatter in Type Ia Supernova Distance Moduli

We describe a new formalism to fit the parametersandthat are used in the SALT2 model to determine the standard magnitudes of Type Ia supernovae. The new formalism describes the intrinsic scatter in Type Ia supernovae by a covariance matrix in place of the single parameter normally used. We have applied this formalism to the Sloan Digital Sky Survey Supernova Survey (SDSS-II) data and conclude that the data are best described by � = 0.135 +.033 −.017 and � = 3.19 +0.14 −0.24, where the error is dominated by the uncertainty in the form of the intrinsic scatter matrix. Our result depends on the introduction of a more general form for the intrinsic scatter of the distance moduli of Type Ia supernovae than is conventional, resulting in a larger value ofand a larger uncertainty than the conventional approach. Although this analysis results in a larger value ofand a larger error, the SDSS data differ (at a 98% confidence level) with � = 4.1, the value expected for extinction by the type of dust found in the Milky Way. We have modeled the distribution of supernovae Ia in terms of their color and conclude that there is strong evidence that variation in color is a significant contributor to the scatter of supernovae Ia around their standard candle magnitude.

Cosmological Parameter Uncertainties from SALT-II Type Ia Supernova Light Curve Models

We use simulated type Ia supernova (SN Ia) samples, including both photometry and spectra, to perform the first direct validation of cosmology analysis using the SALT-II light curve model. This validation includes residuals from the light curve training process, systematic biases in SN Ia distance measurements, and a bias on the dark energy equation of state parameter w. Using the SN-analysis package SNANA, we simulate and analyze realistic samples corresponding to the data samples used in the SNLS3 analysis: ∼120 low-redshift (z < 0.1) SNe Ia, ∼255 Sloan Digital Sky Survey SNe Ia (z < 0.4), and ∼290 SNLS SNe Ia (z ≤ 1). To probe systematic uncertainties in detail, we vary the input spectral model, the model of intrinsic scatter, and the smoothing (i.e., regularization) parameters used during the SALT-II model training. Using realistic intrinsic scatter models results in a slight bias in the ultraviolet portion of the trained SALT-II model, and w biases (w {sub input} – w {sub recovered}) ranging from –0.005 ± 0.012 to –0.024 ± 0.010. These biases are indistinguishable from each other within the uncertainty; the average bias on w is –0.014 ± 0.007.

Testing Models of Intrinsic Brightness Variations in Type Ia Supernovae, and their Impact on Measuring Cosmological Parameters

For spectroscopically confirmed Type Ia supernovae we evaluate models of intrinsic brightness variations with detailed data/Monte Carlo comparisons of the dispersion in the following quantities: Hubble-diagram scatter, color difference (B – V – c) between the true B – V color and the fitted color (c) from the SALT-II light curve model, and photometric redshift residual. The data sample includes 251 ugriz light curves from the three-season Sloan Digital Sky Survey-II and 191 griz light curves from the Supernova Legacy Survey 3 year data release. We find that the simplest model of a wavelength-independent (coherent) scatter is not adequate, and that to describe the data the intrinsic-scatter model must have wavelength-dependent variations resulting in a ~0.02 mag scatter in B – V – c. Relatively weak constraints are obtained on the nature of intrinsic scatter because a variety of different models can reasonably describe this photometric data sample. We use Monte Carlo simulations to examine the standard approach of adding a coherent-scatter term in quadrature to the distance-modulus uncertainty in order to bring the reduced χ2 to unity when fitting a Hubble diagram. If the light curve fits include model uncertainties with the correct wavelength dependence of the scatter, we find that this approach is valid and that the bias on the dark energy equation-of-state parameter w is much smaller (~0.001) than current systematic uncertainties. However, incorrect model uncertainties can lead to a significant bias on the distance moduli, with up to ~0.05 mag redshift-dependent variation. This bias is roughly reduced in half after applying a Malmquist bias correction. For the recent SNLS3 cosmology results, we estimate that this effect introduces an additional systematic uncertainty on w of ~0.02, well below the total uncertainty. This uncertainty depends on the choice of viable scatter models and the choice of supernova (SN) samples, and thus this small w-uncertainty is not guaranteed in future cosmology results. For example, the w-uncertainty for SDSS+SNLS (dropping the nearby SNe) increases to ~0.04.

A PRECISION PHOTOMETRIC COMPARISON BETWEEN SDSS-II AND CSP TYPE Ia SUPERNOVA DATA

Consistency between Carnegie Supernova Project (CSP) and SDSS-II Supernova Survey ugri measurements has been evaluated by comparing Sloan Digital Sky Survey (SDSS) and CSP photometry for nine spectroscopically confirmed Type Ia supernova observed contemporaneously by both programs. The CSP data were transformed into the SDSS photometric system. Sources of systematic uncertainty have been identified, quantified, and shown to be at or below the 0.023 mag level in all bands. When all photometry for a given band is combined, we find average magnitude differences of equal to or less than 0.011 mag in ugri, with rms scatter ranging from 0.043 to 0.077 mag. The u-band agreement is promising, with the caveat that only four of the nine supernovae are well observed in u and these four exhibit an 0.038 mag supernova-to-supernova scatter in this filter.

The Data Release of the Sloan Digital Sky Survey-II Supernova Survey

This paper describes the data release of the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey conducted between 2005 and 2007. Light curves, spectra, classifications, and ancillary data are presented for 10,258 variable and transient sources discovered through repeat ugriz imaging of SDSS Stripe 82, a 300 deg(2) area along the celestial equator. This data release is comprised of all transient sources brighter than r similar or equal to 22.5 mag with no history of variability prior to 2004. Dedicated spectroscopic observations were performed on a subset of 889 transients, as well as spectra for thousands of transient host galaxies using the SDSS-III BOSS spectrographs. Photometric classifications are provided for the candidates with good multi-color light curves that were not observed spectroscopically, using host galaxy redshift information when available. From these observations, 4607 transients are either spectroscopically confirmed, or likely to be, supernovae, making this the largest sample of supernova candidates ever compiled. We present a new method for SN host-galaxy identification and derive host-galaxy properties including stellar masses, star formation rates, and the average stellar population ages from our SDSS multi-band photometry. We derive SALT2 distance moduli for a total of 1364 SN. Ia with spectroscopic redshifts as well as photometric redshifts for a further 624 purely photometric SN. Ia candidates. Using the spectroscopically confirmed subset of the three-year SDSS-II SN. Ia sample and assuming a flat.CDM cosmology, we determine Omega(M) = 0.315 +/- 0.093 (statistical error only) and detect a non-zero cosmological constant at 5.7 sigma.