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

TL;DR

The SDSS-II Supernova Survey Data Release presents a comprehensive time-domain dataset for 10,258 transients discovered in Stripe 82, including multi-band light curves, spectroscopy, classifications, and host-galaxy properties to support SN cosmology and galaxy evolution studies. It introduces a photometric SN Ia classification framework (PSNID/NN) and provides SALT2-based distance moduli for 1443 spectroscopically confirmed and 677 purely photometric SN Ia, along with a new host-matching method and host-property measurements derived from FSPS and PÉGASE.2. The release includes 1360 spectra from 11 telescopes and extensive photometric calibration details (AB offsets, u-band uncertainties), enabling robust cosmological analyses and cross-survey comparisons. Cosmological fits to the spectroscopic SN Ia subset in a flat-$\Lambda$CDM cosmology yield $\Omega_M = 0.315 \pm 0.093$, with evidence for a nonzero cosmological constant at $5.7\sigma$, demonstrating the dataset’s impact on SN cosmology and host-galaxy science. This work provides a benchmark data set and analysis framework for current and future wide-field SN surveys such as Pan-STARRS, DES, and LSST.

Abstract

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 deg2 area along the celestial equator. This data release is comprised of all transient sources brighter than r~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. 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 1443 SN Ia with spectroscopic redshifts as well as photometric redshifts for a further 677 purely-photometric SN Ia candidates. Using the spectroscopically confirmed subset of the three-year SDSS-II SN Ia sample and assuming a flat Lambda-CDM cosmology, we determine Omega_M = 0.315 +/- 0.093 (statistical error only) and detect a non-zero cosmological constant at 5.7 sigmas.

Figures (23)

• Figure 1: Number of scans versus right ascension (shown in degrees) of the SDSSSN equatorial stripe (Stripe 82) is shown along with the mean cadence for each year (2005-2007) of the survey. The coverage in right ascension increased slightly as the template image coverage increased while the mean cadence was approximately four days for all three observing seasons.
• Figure 2: The distribution of number of epochs observed per SN is shown. An epoch consists of one night of observation in all 5 SDSS filters without any requirement that there was a detectable signal in any of the filters. There are typically about 20 epochs in an observing season, but a small fraction of SN lie in the overlap region and are observed with twice the cadence or up to 40 times per season.
• Figure 3: The peak $r$-band magnitude observed is shown as a function of redshift. Black points shown are for all candidates classified as SN Ia. All other SN candidates are shown in blue.
• Figure 4: Regions occupied by SN Ia (black), SN Ibc (red) and SN II (blue) in $\Delta m_{15}(B)$ -- $A_V$ space in different redshift slices for a simulated SDSS-II SN Survey. The panels are $z<0.1$ (top left), $0.1 < z < 0.2$ (top right), $0.2 < z < 0.3$ (middle left), $0.3 < z < 0.4$ (middle right), $z > 0.4$ (bottom left), and all $z$ (bottom right).
• Figure 5: The SN Ia photometric classification efficiency (black), purity (red), and figure of merit (product of the efficiency and purity; blue) as a function of the $P_{\mathrm{Ia}}$ probability cut for simulated SDSS-II SN data. The top panels show results from Bayesian-only (left) and with the nearest-neighbor extension (PSNID/NN) for a flat redshift prior. The bottom panels show the same for a spectroscopic redshift prior. We required $\log$($P_{\mathrm{fit}}$) $>-4.0$. Note that the purity using the Bayesian-only method is never above $\sim 93$%.