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We study the observables of 158 relatively normal Type Ia supernovae (SNe Ia) by dividing them into two groups in terms of the expansion velocity inferred from the absorption minimum of the Si II 6355 line in their spectra near B-band maximum brightness. One group (Normal) consists of normal SNe Ia populating a narrow strip in the Si II velocity distribution, with an average expansion velocity v=10,600+/-400 km/s near B maximum; the other group (HV) consists of objects with higher velocities, v > 11,800 km/s. Compared with the Normal group, the HV one shows a narrower distribution in both the peak luminosity and the luminosity decline rate dm_{15}. In particular, their B-V colors at maximum brightness are found to be on average redder by ~0.1, suggesting that they either are associated with dusty environments or have intrinsically red B-V colors. The HV SNe Ia are also found to prefer a lower extinction ratio Rv~1.6 (versus ~2.4 for the Normal ones). Applying such an absorption-correction dichotomy to SNe Ia of these two groups remarkably reduces the dispersion in their peak luminosity from 0.178 mag to only 0.125 mag.
Type Ia supernovae (SNe Ia) have been used as excellent standardizable candles for measuring cosmic expansion, but their progenitors are still elusive. Here we report that the spectral diversity of SNe Ia is tied to their birthplace environments. We find that those with high-velocity ejecta are substantially more concentrated in the inner and brighter regions of their host galaxies than are normal-velocity SNe Ia. Furthermore, the former tend to inhabit larger and more-luminous hosts. These results suggest that high-velocity SNe Ia likely originate from relatively younger and more metal-rich progenitors than normal-velocity SNe Ia, and are restricted to galaxies with substantial chemical evolution.
The luminosities of Type Ia supernovae (SNe), the thermonuclear explosions of white-dwarf stars, vary systematically with their intrinsic color and the rate at which they fade. From images taken with the Galaxy Evolution Explorer (GALEX), we identified SNe Ia that erupted in environments that have high ultraviolet surface brightness and star-formation surface density. When we apply a steep model extinction law, we calibrate these SNe using their broadband optical light curves to within ~0.065 to 0.075 magnitudes, corresponding to <4% in distance. The tight scatter, probably arising from a small dispersion among progenitor ages, suggests that variation in only one progenitor property primarily accounts for the relationship between their light-curve widths, colors, and luminosities.
A spectral-energy distribution (SED) model for Type Ia supernovae (SNe Ia) is a critical tool for measuring precise and accurate distances across a large redshift range and constraining cosmological parameters. We present an improved model framework, SALT3, which has several advantages over current models including the leading SALT2 model (SALT2.4). While SALT3 has a similar philosophy, it differs from SALT2 by having improved estimation of uncertainties, better separation of color and light-curve stretch, and a publicly available training code. We present the application of our training method on a cross-calibrated compilation of 1083 SNe with 1207 spectra. Our compilation is $2.5times$ larger than the SALT2 training sample and has greatly reduced calibration uncertainties. The resulting trained SALT3.K21 model has an extended wavelength range $2000$-$11000$ angstroms (1800 angstroms redder) and reduced uncertainties compared to SALT2, enabling accurate use of low-$z$ $I$ and $iz$ photometric bands. Including these previously discarded bands, SALT3.K21 reduces the Hubble scatter of the low-z Foundation and CfA3 samples by 15% and 10%, respectively. To check for potential systematic uncertainties we compare distances of low ($0.01<z<0.2$) and high ($0.4<z<0.6$) redshift SNe in the training compilation, finding an insignificant $2pm14$ mmag shift between SALT2.4 and SALT3.K21. While the SALT3.K21 model was trained on optical data, our method can be used to build a model for rest-frame NIR samples from the Roman Space Telescope. Our open-source training code, public training data, model, and documentation are available at https://saltshaker.readthedocs.io/en/latest/, and the model is integrated into the sncosmo and SNANA software packages.
Type Ia supernova cosmology depends on the ability to fit and standardize observations of supernova magnitudes with an empirical model. We present here a series of new models of Type Ia Supernova spectral time series that capture a greater amount of supernova diversity than possible with the models that are currently customary. These are entitled SuperNova Empirical MOdels (textsc{SNEMO}footnote{https://snfactory.lbl.gov/snemo}). The models are constructed using spectrophotometric time series from $172$ individual supernovae from the Nearby Supernova Factory, comprising more than $2000$ spectra. Using the available observations, Gaussian Processes are used to predict a full spectral time series for each supernova. A matrix is constructed from the spectral time series of all the supernovae, and Expectation Maximization Factor Analysis is used to calculate the principal components of the data. K-fold cross-validation then determines the selection of model parameters and accounts for color variation in the data. Based on this process, the final models are trained on supernovae that have been dereddened using the Fitzpatrick and Massa extinction relation. Three final models are presented here: textsc{SNEMO2}, a two-component model for comparison with current Type~Ia models; textsc{SNEMO7}, a seven component model chosen for standardizing supernova magnitudes which results in a total dispersion of $0.100$~mag for a validation set of supernovae, of which $0.087$~mag is unexplained (a total dispersion of $0.113$~mag with unexplained dispersion of $0.097$~mag is found for the total set of training and validation supernovae); and textsc{SNEMO15}, a comprehensive $15$ component model that maximizes the amount of spectral time series behavior captured.
We present two supernovae (SNe) discovered with the Hubble Space Telescope (HST) in the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS), an HST multi-cycle treasury program. We classify both objects as Type Ia SNe and find redshifts of z = 1.80+-0.02 and 2.26 +0.02 -0.10, the latter of which is the highest redshift Type Ia SN yet seen. Using light curve fitting we determine luminosity distances and find that both objects are consistent with a standard Lambda-CDM cosmological model. These SNe were observed using the HST Wide Field Camera 3 infrared detector (WFC3-IR), with imaging in both wide- and medium-band filters. We demonstrate that the classification and redshift estimates are significantly improved by the inclusion of single-epoch medium-band observations. This medium-band imaging approximates a very low resolution spectrum (lambda/delta lambda ~ 100) which can isolate broad spectral absorption features that differentiate Type Ia SNe from their most common core collapse cousins. This medium-band method is also insensitive to dust extinction and (unlike grism spectroscopy) it is not affected by contamination from the SN host galaxy or other nearby sources. As such, it can provide a more efficient - though less precise - alternative to IR spectroscopy for high-z SNe.