We report on work to increase the number of well-measured Type Ia supernovae (SNe Ia) at high redshifts. Light curves, including high signal-to-noise HST data, and spectra of six SNe Ia that were discovered during 2001 are presented. Additionally, for the two SNe with z > 1, we present groundbased J-band photometry from Gemini and the VLT. These are among the most distant SNe Ia for which ground based near-IR observations have been obtained. We add these six SNe Ia together with other data sets that have recently become available in the literature to the Union compilation (Kowalski et al. 2008). We have made a number of refinements to the Union analysis chain, the most important ones being the refitting of all light curves with the SALT2 fitter and an improved handling of systematic errors. We call this new compilation, consisting of 557 supernovae, the Union2 compilation. The flat concordance ΛCDM model remains an excellent fit to the Union2 data with the best fit constant equation of state parameter w = −0.997 +0.050 −0.054 (stat)+0.077 −0.082 (stat + sys together) for a flat universe, or w = −1.035 +0.055 −0.059 (stat)+0.093 −0.097 (stat + sys together) with curvature. We also present improved constraints on w(z). While no significant change in w with redshift is detected, there is still considerable room for evolution in w. The strength of the constraints depend strongly on redshift. In particular, at z 1, the existence and nature of dark energy are only weakly constrained by the data.

We present ACS, NICMOS, and Keck AO-assisted photometry of 20 Type Ia supernovae (SNe Ia) from the HST Cluster Supernova Survey. The SNe Ia were discovered over the redshift interval 0.623 < z < 1.415. Fourteen of these SNe Ia pass our strict selection cuts and are used in combination with the world's sample of SNe Ia to derive the best current constraints on dark energy. Ten of our new SNe Ia are beyond redshift z = 1, thereby nearly doubling the statistical weight of HST-discovered SNe Ia beyond this redshift. Our detailed analysis corrects for the recently identified correlation between SN Ia luminosity and host galaxy mass and corrects the NICMOS zeropoint at the count rates appropriate for very distant SNe Ia. Adding these supernovae improves the best combined constraint on dark energy density, ρ DE (z), at redshifts 1.0 < z < 1.6 by 18% (including systematic errors). For a flat ΛCDM universe, we find Ω Λ = 0.729 +0.014 −0.014 (68% CL including systematic errors). For a flat wCDM model, we measure a constant dark energy equation-of-state parameter w = −1.013 +0.068 −0.073 (68% CL). Curvature is constrained to ∼ 0.7% in the owCDM model and to ∼ 2% in a model in which dark energy is allowed to vary with parameters w 0 and w a . Tightening further the constraints on the time evolution of dark energy will require several improvements, including high-quality multi-passband photometry of a sample of several dozen z > 1 SNe Ia. We describe how such a sample could be efficiently obtained by targeting cluster fields with WFC3 on HST.The updated supernova Union2.1 compilation of 580 SNe is available at http://supernova.lbl.gov/Union ⋆ is less than the mass threshold. We begin by noting that.We can then integrate this probability over all true host masses less than the threshold:⋆ )P (m true ⋆ ) up to a normalization constant found by requiring the integral to be unity when integrating over all possible true masses. P (m true ⋆ ) is estimated from the observed distribution for each type of survey. The SNLS (Sullivan et al. 2010) and SDSS (Lampeitl et al. 2010) host masses were assumed to be representative of untargeted surveys, while the mass distribution in Kelly et al. (2010) was assumed typical of nearby targeted surveys. As these distributions are approximately log-normal, we use this model for P (m true ⋆) using the mean and RMS from the log of the host masses from these surveys (with the average measurement errors subtracted in quadrature), giving log 10 P (m true ⋆ ) = N (µ = 9.88, σ 2 = 0.92 2 ) for untargeted surveys and log 10 P (m true ⋆ ) = N (10.75, 0.66 2 ) for targeted surveys. When host mass measurements are available, P (m obs ⋆ |m true ⋆ ) is also modeled as a log-normal; when no measurement is available, a flat distribution is used.For a supernova from an untargeted survey with no host mass measurement (including supernovae presented in this paper which are not in a cluster), P (m trueis the integral of P (m true ⋆ ) up to the threshold mass: 0.55. Similarly, nearby supernovae from targeted surveys w...

We present a new compilation of Type Ia supernovae (SNe Ia), a new data set of low-redshift nearby-Hubble-flow SNe, and new analysis procedures to work with these heterogeneous compilations. This ''Union'' compilation of 414 SNe Ia, which reduces to 307 SNe after selection cuts, includes the recent large samples of SNe Ia from the Supernova Legacy Survey and ESSENCE Survey, the older data sets, as well as the recently extended data set of distant supernovae observed with the Hubble Space Telescope (HST ). A single, consistent, and blind analysis procedure is used for all the various SN Ia subsamples, and a new procedure is implemented that consistently weights the heterogeneous data sets and rejects outliers. We present the latest results from this Union compilation and discuss the cosmological constraints from this new compilation and its combination with other cosmological measurements (CMB and BAO). The constraint we obtain from supernovae on the dark energy density is à ¼ 0:713 þ0:027 À0:029 (stat) þ0:036 À0:039 (sys), for a flat, ÃCDM universe. Assuming a constant equation of state parameter, w, the combined constraints from SNe, BAO, and A CMB give w ¼ À0:969 þ0:059 À0:063 (stat) þ0:063 À0:066 (sys). While our results are consistent with a cosmological constant, we obtain only relatively weak constraints on a w that varies with redshift. In particular, the current SN data do not yet significantly constrain w at z > 1. With the addition of our new nearby Hubble-flow SNe Ia, these resulting cosmological constraints are currently the tightest available.

We present the first public version (v0.2) of the open-source and community-developed Python package, Astropy. This package provides core astronomy-related functionality to the community, including support for domain-specific file formats such as flexible image transport system (FITS) files, Virtual Observatory (VO) tables, and common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions. Significant functionality is under active development, such as a model fitting framework, VO client and server tools, and aperture and point spread function (PSF) photometry tools. The core development team is actively making additions and enhancements to the current code base, and we encourage anyone interested to participate in the development of future Astropy versions.