First-year Sloan Digital Sky Survey-II (SDSS-II) Supernova Results: Hubble Diagram and Cosmological Parameters (0908.4274v1)

Abstract: 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.

• The paper demonstrates that SDSS-II type Ia supernova data effectively bridge the redshift gap, anchoring a continuous Hubble diagram.
• It employs MLCS2k2 and SALT2 light-curve models to derive cosmological parameters with notable differences, highlighting methodological sensitivities.
• The study addresses systematic uncertainties like dust extinction and calibration, guiding future surveys toward refining dark energy constraints.

Insights into First-Year SDSS-II Supernova Results and Cosmological Inferences

The paper entitled "First-year Sloan Digital Sky Survey-II (SDSS-II) Supernova Results: Hubble Diagram and Cosmological Parameters" provides a comprehensive analysis of the first-year findings from the SDSS-II supernova survey. It presents a detailed paper of type Ia supernovae (SNe Ia) and their implications for cosmological models, particularly focusing on determining the universe's expansion dynamics via Hubble diagrams.

Overview of the SDSS-II Supernova Survey

During the 2005 observing season, the SDSS-II supernova survey systematically discovered and analyzed 103 Type Ia supernovae within the redshift range of 0.04 to 0.42. The critical achievement of this work was providing a continuous redshift bridge between local and high-redshift supernova surveys, thus addressing the historical "redshift desert." This facilitated a more robust anchoring of the Hubble diagram across a wide range of redshifts, essential for reliable determination of cosmological parameters.

Methodology and Analysis

For light-curve analysis, the paper employs two distinct methods—MLCS2k2 and SALT2. These methods allow the researchers to contrast different assumptions about intrinsic SN color variations and reddening by dust in host galaxies.

1. MLCS2k2: This method assumes that all color variations for SNe Ia can be modeled via a one-parameter model (Δ) combined with host-galaxy extinction modeled by an exponential distribution with an assumed dust parameter $R_V = 2.18$.
2. SALT2: It utilizes a surface fitting method resulting in parameters $x_1$ (stretch) and $c$ (color), while the cosmological parameters are obtained through a simultaneous global fit.

Key Findings and Results

For the flat $w$-CDM cosmological model, combining the SN data with baryon acoustic oscillations (BAO) and CMB constraints yielded the following:

• Using MLCS2k2: $$w = -0.76 \pm 0.07 (\text{stat}) \pm 0.11 (\text{syst})$$ and $$\Omega_M = 0.307 \pm 0.019 (\text{stat}) \pm 0.023 (\text{syst})$$.
• Using SALT2: $$w = -0.96 \pm 0.06 (\text{stat}) \pm 0.12 (\text{syst})$$ and $$\Omega_M = 0.265 \pm 0.016 (\text{stat}) \pm 0.025 (\text{syst})$$.

The differences between these results underscore the sensitivity of cosmological inference to the modeling of supernova light curves and the assumptions about SN color variations and dust.

Addressing Systematic Uncertainties

The paper extensively scrutinizes systematic uncertainties associated with dust properties, instrument calibration, and light-curve modeling, all of which are crucial in supernova cosmology. Specifically, discrepancies linked to rest-frame U-band and challenges with accurate extinction modeling are discussed, reinforcing the need for refined modeling frameworks.

Implications and Future Outlook

The paper effectively illustrates the complexity and challenges in supernova cosmology, highlighting key areas where improvement is necessary. These findings imply a need for consistent training of light-curve models and more comprehensive SN surveys. Notably, the inclusion of photometric SNe Ia with host-galaxy redshifts can substantially enhance parameter constraints by mitigating biases from selection effects.

The work sets the premise for utilizing larger, more homogeneous future supernova samples from the full three-season SDSS-II data, as well as next-generation surveys such as LSST and DES, to further tighten constraints on dark energy and clarify the underlying nature of cosmic acceleration.