No Arabic abstract
We present a sample of normal type Ia supernovae from the Nearby Supernova Factory dataset with spectrophotometry at sufficiently late phases to estimate the ejected mass using the bolometric light curve. We measure $^{56}$Ni masses from the peak bolometric luminosity, then compare the luminosity in the $^{56}$Co-decay tail to the expected rate of radioactive energy re- lease from ejecta of a given mass. We infer the ejected mass in a Bayesian context using a semi-analytic model of the ejecta, incorporating constraints from contemporary numerical models as priors on the density structure and distribution of $^{56}$Ni throughout the ejecta. We find a strong correlation between ejected mass and light curve decline rate, and consequently $^{56}$Ni mass, with ejected masses in our data ranging from 0.9-1.4 $M_odot$. Most fast-declining (SALT2 $x_1 < -1$) normal SNe Ia have significantly sub-Chandrasekhar ejected masses in our fiducial analysis.
We present bolometric light curves constructed from multi-wavelength photometry of Type Ia supernovae (SNe Ia) from the Carnegie Supernova Project and the CfA Supernova Group, using near-infrared observations to provide robust constraints on host galaxy dust extinction. This set of light curves form a well-measured reference set for comparison with theoretical models. Ejected mass and synthesized $^{56}$Ni mass are inferred for each SN Ia from its bolometric light curve using a semi-analytic Bayesian light curve model, and fitting formulae provided in terms of light curve width parameters from the SALT2 and SNooPy light curve fitters. A weak bolometric width-luminosity relation is confirmed, along with a correlation between ejected mass and the bolometric light curve width. SNe Ia likely to have sub-Chandrasekhar ejected masses belong preferentially to the broad-line and cool-photosphere spectroscopic subtypes, and have higher photospheric velocities and populate older, higher-mass host galaxies than SNe Ia consistent with Chandrasekhar-mass explosions. Two peculiar events, SN 2006bt and SN 2006ot, have normal peak luminosities but appear to have super-Chandrasekhar ejected masses.
We present photometric and spectroscopic observations of galaxies hosting Type Ia supernovae (SNe Ia) observed by the Nearby Supernova Factory (SNfactory). Combining GALEX UV data with optical and near infrared photometry, we employ stellar population synthesis techniques to measure SN Ia host galaxy stellar masses, star-formation rates (SFRs), and reddening due to dust. We reinforce the key role of GALEX UV data in deriving accurate estimates of galaxy SFRs and dust extinction. Optical spectra of SN Ia host galaxies are fitted simultaneously for their stellar continua and emission lines fluxes, from which we derive high precision redshifts, gas-phase metallicities, and Halpha-based SFRs. With these data we show that SN Ia host galaxies present tight agreement with the fiducial galaxy mass-metallicity relation from SDSS for stellar masses log(M_*/M_Sun)>8.5 where the relation is well-defined. The star-formation activity of SN Ia host galaxies is consistent with a sample of comparable SDSS field galaxies, though this comparison is limited by systematic uncertainties in SFR measurements. Our analysis indicates that SN Ia host galaxies are, on average, typical representatives of normal field galaxies.
We analyze the rise and fall times of type Ia supernova (SN Ia) light curves discovered by the SDSS-II Supernova Survey. From a set of 391 light curves k-corrected to the rest frame B and V bands, we find a smaller dispersion in the rising portion of the light curve compared to the decline. This is in qualitative agreement with computer models which predict that variations in radioactive nickel yield have less impact on the rise than on the spread of the decline rates. The differences we find in the rise and fall properties suggest that a single stretch correction to the light curve phase does not properly model the range of SN Ia light curve shapes. We select a subset of 105 light curves well-observed in both rise and fall portions of the light curves and develop a 2-stretch fit algorithm which estimates the rise and fall times independently. We find the average time from explosion to B-band peak brightness is 17.38 +/- 0.17 days. Our average rise time is shorter than the 19.5 days found in previous studies; this reflects both the different light curve template used and the application of the 2-stretch algorithm. We find that slow declining events tend to have fast rise times, but that the distribution of rise minus fall time is broad and single-peaked. This distribution is in contrast to the bimodality in this parameter that was first suggested by Strovink (2007) from an analysis of a small set of local SNe Ia. We divide the SDSS-II sample in half based on the rise minus fall value, tr-tf <= 2 days and tr-tf>2 days, to search for differences in their host galaxy properties and Hubble residuals; we find no difference in host galaxy properties or Hubble residuals in our sample.
Context. Our Local Group of galaxies appears to be moving relative to the cosmic microwave background with the source of the peculiar motion still uncertain. While in the past this has been studied mostly using galaxies as distance indicators, the weight of type Ia supernovae (SNe Ia) has increased recently with the continuously improving statistics of available low-redshift supernovae. Aims. We measured the bulk flow in the nearby universe ($0.015 < z < 0.1$) using 117 SNe Ia observed by the Nearby Supernova Factory, as well as the Union2 compilation of SN Ia data already in the literature. Methods. The bulk flow velocity was determined from SN data binned in redshift shells by including a coherent motion (dipole) in a cosmological fit. Additionally, a method of spatially smoothing the Hubble residuals was used to verify the results of the dipole fit. To constrain the location and mass of a potential mass concentration (e.g., the Shapley supercluster) responsible for the peculiar motion, we fit a Hubble law modified by adding an additional mass concentration. Results. The analysis shows a bulk flow that is consistent with the direction of the CMB dipole up to $z sim 0.06$, thereby doubling the volume over which conventional distance measures are sensitive to a bulk flow. We see no significant turnover behind the center of the Shapley supercluster. A simple attractor model in the proximity of the Shapley supercluster is only marginally consistent with our data, suggesting the need for another, more distant source. In the redshift shell $0.06 < z < 0.1$, we constrain the bulk flow velocity to $< 240~textrm{km s}^{-1}$ (68% confidence level) for the direction of the CMB dipole, in contradiction to recent claims of the existence of a large-amplitude dark flow.
We examine the relationship between Type Ia Supernova (SN Ia) Hubble residuals and the properties of their host galaxies using a sample of 115 SNe Ia from the Nearby Supernova Factory (SNfactory). We use host galaxy stellar masses and specific star-formation rates fitted from photometry for all hosts, as well as gas-phase metallicities for a subset of 69 star-forming (non-AGN) hosts, to show that the SN Ia Hubble residuals correlate with each of these host properties. With these data we find new evidence for a correlation between SN Ia intrinsic color and host metallicity. When we combine our data with those of other published SN Ia surveys, we find the difference between mean SN Ia brightnesses in low and high mass hosts is 0.077 +- 0.014 mag. When viewed in narrow (0.2 dex) bins of host stellar mass, the data reveal apparent plateaus of Hubble residuals at high and low host masses with a rapid transition over a short mass range (9.8 <= log(M_*/M_Sun) <= 10.4). Although metallicity has been a favored interpretation for the origin of the Hubble residual trend with host mass, we illustrate how dust in star-forming galaxies and mean SN Ia progenitor age both evolve along the galaxy mass sequence, thereby presenting equally viable explanations for some or all of the observed SN Ia host bias.