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 di
scovered 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.
With upcoming all sky surveys such as LSST poised to generate a deep digital movie of the optical sky, variability-based AGN selection will enable the construction of highly-complete catalogs with minimum contamination. In this study, we generate $g$
-band difference images and construct light curves for QSO/AGN candidates listed in SDSS Stripe 82 public catalogs compiled from different methods, including spectroscopy, optical colors, variability, and X-ray detection. Image differencing excels at identifying variable sources embedded in complex or blended emission regions such as Type II AGNs and other low-luminosity AGNs that may be omitted from traditional photometric or spectroscopic catalogs. To separate QSOs/AGNs from other sources using our difference image light curves, we explore several light curve statistics and parameterize optical variability by the characteristic damping timescale ($tau$) and variability amplitude. By virtue of distinguishable variability parameters of AGNs, we are able to select them with high completeness of 93.4% and efficiency (i.e., purity) of 71.3%. Based on optical variability, we also select highly variable blazar candidates, whose infrared colors are consistent with known blazars. One third of them are also radio detected. With the X-ray selected AGN candidates, we probe the optical variability of X-ray detected optically-extended sources using their difference image light curves for the first time. A combination of optical variability and X-ray detection enables us to select various types of host-dominated AGNs. Contrary to the AGN unification model prediction, two Type II AGN candidates (out of 6) show detectable variability on long-term timescales like typical Type I AGNs. This study will provide a baseline for future optical variability studies of extended sources.
We present transit observations of the WASP-2 exoplanet system by the Apache Point Survey of Transit Lightcurves of Exoplanets (APOSTLE) program. Model fitting to these data allows us to improve measurements of the hot-Jupiter exoplanet WASP-2b and i
ts orbital parameters by a factor of ~2 over prior studies; we do not find evidence for transit depth variations. We do find reduced chi^2 values greater than 1.0 in the observed minus computed transit times. A sinusoidal fit to the residuals yields a timing semi-amplitude of 32 seconds and a period of 389 days. However, random rearrangements of the data provide similar quality fits, and we cannot with certainty ascribe the timing variations to mutual exoplanet interactions. This inconclusive result is consistent with the lack of incontrovertible transit timing variations (TTVs) observed in other hot-Jupiter systems. This outcome emphasizes that unique recognition of TTVs requires dense sampling of the libration cycle (e.g. continuous observations from space-based platforms). However, even in systems observed with the Kepler spacecraft, there is a noted lack of transiting companions and TTVs in hot-Jupiter systems. This result is more meaningful, and indicates that hot-Jupiter systems, while they are easily observable from the ground, do not appear to be currently configured in a manner favorable to the detection of TTVs. The future of ground-based TTV studies may reside in resolving secular trends, and/or implementation at extreme quality observing sites to minimize atmospheric red noise.
We present ground-based observations of the transiting Neptune-mass planet Gl 436b obtained with the 3.5-meter telescope at Apache Point Observatory and other supporting telescopes. Included in this is an observed transit in early 2005, over two year
s before the earliest reported transit detection. We have compiled all available transit data to date and perform a uniform modeling using the JKTEBOP code. We do not detect any transit timing variations of amplitude greater than ~1 minute over the ~3.3 year baseline. We do however find possible evidence for a self-consistent trend of increasing orbital inclination, transit width, and transit depth, which supports the supposition that Gl 436b is being perturbed by another planet of < 12 Earth Masses in a non-resonant orbit.
I provide an incomplete inventory of the astronomical variability that will be found by next-generation time-domain astronomical surveys. These phenomena span the distance range from near-Earth satellites to the farthest Gamma Ray Bursts. The surveys
that detect these transients will issue alerts to the greater astronomical community; this decision process must be extremely robust to avoid a slew of ``false alerts, and to maintain the communitys trust in the surveys. I review the functionality required of both the surveys and the telescope networks that will be following them up, and the role of VOEvents in this process. Finally, I offer some ideas about object and event classification, which will be explored more thoroughly by other articles in these proceedings.
We have developed an end-to-end photometric data processing pipeline to compare current photometric algorithms commonly used on ground-based imaging data. This testbed is exceedingly adaptable, and enables us to perform many research and development
tasks, including image subtraction and co-addition, object detection and measurements, the production of photometric catalogs, and the creation and stocking of database tables with time-series information. This testing has been undertaken to evaluate existing photometry algorithms for consideration by a next-generation image processing pipeline for the Large Synoptic Survey Telescope (LSST). We outline the results of our tests for four packages: The Sloan Digital Sky Surveys (SDSS) Photo package, Daophot and Allframe, DoPhot, and t
