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 Ω m = 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.

The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias and the halo mass function through state-of-the-art modeling prescriptions available in the literature. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. A rigorous validation procedure, based on comparisons between CCL and independent software packages, allows us to establish a well-defined numerical accuracy for each predicted quantity. As a result, predictions for correlation functions of galaxy clustering, galaxy-galaxy lensing and cosmic shear are demonstrated to be within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is an open source software package written in C, with a python interface and publicly available at https://github.com/LSSTDESC/CCL.