Aims. We present a ground-based, near-infrared search for lensed supernovae behind the massive cluster Abell 1689 at z = 0.18, which is one of the most powerful gravitational telescopes that nature ...provides. Methods. Our survey was based on multi-epoch J-band observations with the HAWK-I instrument on VLT, with supporting optical data from the Nordic Optical Telescope. Results. Our search resulted in the discovery of five photometrically classified, core-collapse supernovae with high redshifts of 0.671 < z < 1.703 and magnifications in the range Δm = − 0.31 to −1.58 mag, as calculated from lensing models in the literature. Owing to the power of the lensing cluster, the survey had the sensitivity to detect supernovae up to very high redshifts, z~3, albeit for a limited region of space. We present a study of the core-collapse supernova rates for 0.4 ≤ z< 2.9, and find good agreement with previous estimates and predictions from star formation history. During our survey, we also discovered two Type Ia supernovae in A 1689 cluster members, which allowed us to determine the cluster Ia rate to be 0.14+0.19-0.09±0.01SNuB h2 (SNuB≡10-12SNe L-1⊙,B yr-1), where the error bars indicate 1σ confidence intervals, statistical and systematic, respectively. The cluster rate normalized by the stellar mass is 0.10+0.13-0.096±0.02 in SNuM h2 (SNuM ≡10-12SNe M-1⊙ yr-1). Furthermore, we explore the optimal future survey for improving the core-collapse supernova rate measurements at z ≳ 2 using gravitational telescopes, and for detections with multiply lensed images, and we find that the planned WFIRST space mission has excellent prospects. Conclusions. Massive clusters can be used as gravitational telescopes to significantly expand the survey range of supernova searches, with important implications for the study of the high-z transient Universe.
Aims. We present a technique to measure lightcurves of time-variable point sources on a spatially structured background from imaging data. The technique was developed to measure lightcurves of SNLS ...supernovae in order to infer their distances. This photometry technique performs simultaneous point spread function (PSF) photometry at the same sky position on an image series. Methods. We describe two implementations of the method: one that resamples images before measuring fluxes, and one which does not. In both instances, we sketch the key algorithms involved and present the validation using semi-artificial sources introduced in real images in order to assess the accuracy of the supernova flux measurements relative to that of surrounding stars. We describe the methods required to anchor these PSF fluxes to calibrated aperture catalogs, in order to derive SN magnitudes. Results. We find a marginally significant bias of 2 mmag of the after-resampling method, and no bias at the mmag accuracy for the non-resampling method. Given surrounding star magnitudes, we determine the systematic uncertainty of SN magnitudes to be less than 1.5 mmag, which represents about one third of the current photometric calibration uncertainty affecting SN measurements. The SN photometry delivers several by-products: bright star PSF flux measurements which have a repeatability of about 0.6%, as for aperture measurements; we measure relative astrometric positions with a noise floor of 2.4 mas for a single-image bright star measurement; we show that in all bands of the MegaCam instrument, stars exhibit a profile linearly broadening with flux by about 0.5% over the whole brightness range.
We show that Type Ia supemovae (SNe Ia) are formed within both very young and old stellar populations, with observed rates that depend on the stellar mass and mean star formation rates (SFRs) of ...their host galaxies. Models in which the SN Ia rate depends solely on host galaxy stellar mass are ruled out with >99% confidence. Our analysis is based on 100 spectroscopically confirmed SNe Ia, plus 24 photometrically classified events, all from the Supernova Legacy Survey (SNLS) and distributed over 0.2 < z < 0.75. We estimate stellar masses and SFRs for the SN Ia host galaxies by fitting their broadband spectral energy distributions with the galaxy spectral synthesis code PEGASE.2. We show that the SN Ia rate per unit mass is proportional to the specific SFR of the parent galaxies--more vigorously star-forming galaxies host more SNe Ia per unit stellar mass, broadly equivalent to the trend of increasing SN Ia rate in later type galaxies seen in the local universe. Following earlier suggestions for a simple "two-component" model approximating the SN Ia rate, we find bivariate linear dependencies of the SN Ia rate on both the stellar masses and the mean SFRs of the host systems. We find that the SN Ia rate can be well represented as the sum of 5.3 c 1.1 x 10 super(-14) SNe yr super(-1) M super(-) sub( ) super(1) and 3.9 c 0.7 x 10 super(-4) SNe yr super(-1) (M sub( )yr super(-1)) super(-1) of star formation. We also demonstrate a dependence of distant SN Ia light-curve shapes on star formation in the host galaxy, similar to trends observed locally. Passive galaxies, with no star formation, preferentially host faster declining/dimmer SNe Ia, while brighter events are found in systems with ongoing star formation.
Aims. We aim to present 70 spectra of 68 new high-redshift type Ia supernovae (SNe Ia) measured at ESO’s VLT during the final two years of operation (2006–2008) of the Supernova Legacy Survey (SNLS). ...This new sample complements the VLT three year spectral set. Altogether, these two data sets form the five year sample of SNLS SN Ia spectra measured at the VLT on which the final SNLS cosmological analysis will partly be based. In the redshift range considered, this sample is unique in terms of homogeneity and number of spectra. We use it to investigate the possibility of a spectral evolution of SNe Ia populations with redshift as well as SNe Ia spectral properties as a function of lightcurve fit parameters and the mass of the host-galaxy. Methods. Reduction and extraction are based on both IRAF standard tasks and our own reduction pipeline. Redshifts are estimated from host-galaxy lines whenever possible or alternatively from supernova features. We used the spectro-photometric SN Ia model SALT2 combined with a set of galaxy templates that model the host-galaxy contamination to assess the type Ia nature of the candidates. Results. We identify 68 new SNe Ia with redshift ranging from z = 0.207 to z = 0.98 for an average redshift of z = 0.62. Each spectrum is presented individually along with its best-fit SALT2 model. Adding this new sample to the three year VLT sample of SNLS, the final dataset contains 209 spectra corresponding to 192 SNe Ia identified at the VLT. We also publish the redshifts of other candidates (host galaxies or other transients) whose spectra were obtained at the same time as the spectra of live SNe Ia. This list provides a new redshift catalog useful for upcoming galaxy surveys. Using the full VLT SNe Ia sample, we build composite spectra around maximum light with cuts in color, the lightcurve shape parameter (“stretch”), host-galaxy mass and redshift. We find that high-z SNe Ia are bluer, brighter and have weaker intermediate mass element absorption lines than their low-z counterparts at a level consistent with what is expected from selection effects. We also find a flux excess in the range 3000–3400 Å for SNe Ia in low mass host-galaxies (M < 1010M⊙) or with locally blue U–V colors, and suggest that the UV flux (or local color) may be used in future cosmological studies as a third standardization parameter in addition to stretch and color.
We present new techniques for improving the efficiency of supernova (SN) classification at high redshift using 64 candidates observed at Gemini North and South during the first year of the Supernova ...Legacy Survey (SNLS). The SNLS is an ongoing 5 year project with the goal of measuring the equation of state of dark energy by discovering and following over 700 high-redshift SNe Ia using data from the Canada-France-Hawaii Telescope Legacy Survey. We achieve an improvement in the SN Ia spectroscopic confirmation rate: at Gemini 71% of candidates are now confirmed as SNe Ia, compared to 54% using the methods of previous surveys. This is despite the comparatively high redshift of this sample, in which the median SN Ia redshift is z = 0.81 (0.155 , z , 1.01). These improvements were realized because we use the unprecedented color coverage and light curve sampling of the SNLS to predict whether a candidate is a SN Ia and to estimate its redshift, before obtaining a spectrum, using a new technique called the "SN photo-z." In addition, we have improved techniques for galaxy subtraction and SN template j super(2) fitting, allowing us to identify candidates even when they are only 15% as bright as the host galaxy. The largest impediment to SN identification is found to be host galaxy contamination of the spectrum - when the SN was at least as bright as the underlying host galaxy the target was identified more than 90% of the time. However, even SNe in bright host galaxies can be easily identified in good seeing conditions. When the image quality was better than 0.55, the candidate was identified 88% of the time. Over the 5 year course of the survey, using the selection techniques presented here, we will be able to add 6170 more confirmed SNe Ia than would be possible using previous methods.
We use three years of data from the Supernova Legacy Survey (SNLS) to study the general properties of core-collapse and type Ia supernovae. This is the first such study using the “rolling search” ...technique which guarantees well-sampled SNLS light curves and good efficiency for supernovae brighter than $i^\prime$~24. Using host photometric redshifts, we measure the supernova absolute magnitude distribution down to luminosities 4.5 mag fainter than normal SNIa. Using spectroscopy and light-curve fitting to discriminate against SNIa, we find a sample of 117 core-collapse supernova candidates with redshifts z < 0.4 (median redshift of 0.29) and measure their rate to be larger than the type Ia supernova rate by a factor 4.5±0.8(stat.)±0.6 (sys.). This corresponds to a core-collapse rate at z = 0.3 of 1.42±0.3(stat.)±0.3(sys.) $\times$10-4 yr-1($h_{\rm 70}^{-1}$ Mpc)-3.
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