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Register a new userExploring the spectroscopic diversity of Type Ia Supernovae
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The velocities and equivalent widths (EWs) of a set of absorption features are measured for a sample of 28 well-observed Type Ia supernovae (SN Ia) covering a wide range of properties. The values of these quantities at maximum are obtained through interpolation/extrapolation and plotted against the decline rate, and so are various line ratios. The SNe are divided according to their velocity evolution into three classes defined in a previous work of Benetti et al.: low velocity gradient (LVG), high velocity gradient (HVG) and FAINT. It is found that all the LVG SNe have approximately uniform velocities at B maximum, while the FAINT SNe have values that decrease with increasing Delta m_15(B), and the HVG SNe have a large spread. The EWs of the Fe-dominated features are approximately constant in all SNe, while those of Intermediate mass element (IME) lines have larger values for intermediate decliners and smaller values for brighter and FAINT SNe. The HVG SNe have stronger Si II 6355-A lines, with no correlation with Delta m_15(B). It is also shown that the Si II 5972 A EW and three EW ratios, including one analogous to the R(Si II) ratio introduced by Nugent et al., are good spectroscopic indicators of luminosity. The data suggest that all LVG SNe have approximately constant kinetic energy, since burning to IME extends to similar velocities. The FAINT SNe may have somewhat lower energies. The large velocities and EWs of the IME lines of HVG SNe appear correlated with each other, but are not correlated with the presence of high-velocity features in the Ca II infrared triplet in the earliest spectra for the SNe for which such data exist.
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We present 2603 spectra of 462 nearby Type Ia supernovae (SN Ia) obtained during 1993-2008 through the Center for Astrophysics Supernova Program. Most of the spectra were obtained with the FAST spectrograph at the FLWO 1.5m telescope and reduced in a consistent manner, making data set well suited for studies of SN Ia spectroscopic diversity. We study the spectroscopic and photometric properties of SN Ia as a function of spectroscopic class using the classification schemes of Branch et al. and Wang et al. The width-luminosity relation appears to be steeper for SN Ia with broader lines. Based on the evolution of the characteristic Si II 6355 line, we propose improved methods for measuring velocity gradients, revealing a larger range than previously suspected, from ~0 to ~400 km/s/day considering the instantaneous velocity decline rate at maximum light. We find a weaker and less significant correlation between Si II velocity and intrinsic B-V color at maximum light than reported by Foley et al., owing to a more comprehensive treatment of uncertainties and host galaxy dust. We study the extent of nuclear burning and report new detections of C II 6580 in 23 early-time spectra. The frequency of C II detections is not higher in SN Ia with bluer colors or narrower light curves, in conflict with the recent results of Thomas et al. Based on nebular spectra of 27 SN Ia, we find no relation between the FWHM of the iron emission feature at ~4700 A and Dm15(B) after removing the two low-luminosity SN 1986G and SN 1991bg, suggesting that the peak luminosity is not strongly dependent on the kinetic energy of the explosion for most SN Ia. Finally, we confirm the correlation of velocity shifts in some nebular lines with the intrinsic B-V color of SN Ia at maximum light, although several outliers suggest a possible non-monotonic behavior for the largest blueshifts.
The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate identification of subtypes of SNeIa through the establishment of a hierarchical group structure in the continuous space of spectral diversity formed by these objects. Using Deep Learning, we were capable of performing such identification in a 4 dimensional feature space (+1 for time evolution), while the standard Principal Component Analysis barely achieves similar results using 15 principal components. This is evidence that the progenitor system and the explosion mechanism can be described by a small number of initial physical parameters. As a proof of concept, we show that our results are in close agreement with a previously suggested classification scheme and that our proposed method can grasp the main spectral features behind the definition of such subtypes. This allows the confirmation of the velocity of lines as a first order effect in the determination of SNIa subtypes, followed by 91bg-like events. Given the expected data deluge in the forthcoming years, our proposed approach is essential to allow a quick and statistically coherent identification of SNeIa subtypes (and outliers). All tools used in this work were made publicly available in the Python package Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy (DRACULA) and can be found within COINtoolbox (https://github.com/COINtoolbox/DRACULA).
Ultraviolet (UV) observations of Type Ia supernovae (SNe Ia) probe the outermost layers of the explosion, and UV spectra of SNe Ia are expected to be extremely sensitive to differences in progenitor composition and the details of the explosion. Here we present the first study of a sample of high signal-to-noise ratio SN Ia spectra that extend blueward of 2900 A. We focus on spectra taken within 5 days of maximum brightness. Our sample of ten SNe Ia spans the majority of the parameter space of SN Ia optical diversity. We find that SNe Ia have significantly more diversity in the UV than in the optical, with the spectral variance continuing to increase with decreasing wavelengths until at least 1800 A (the limit of our data). The majority of the UV variance correlates with optical light-curve shape, while there are no obvious and unique correlations between spectral shape and either ejecta velocity or host-galaxy morphology. Using light-curve shape as the primary variable, we create a UV spectral model for SNe Ia at peak brightness. With the model, we can examine how individual SNe vary relative to expectations based on only their light-curve shape. Doing this, we confirm an excess of flux for SN 2011fe at short wavelengths, consistent with its progenitor having a subsolar metallicity. While most other SNe Ia do not show large deviations from the model, ASASSN-14lp has a deficit of flux at short wavelengths, suggesting that its progenitor was relatively metal rich.
We present an investigation of the optical spectra of 264 low-redshift (z < 0.2) Type Ia supernovae (SNe Ia) discovered by the Palomar Transient Factory, an untargeted transient survey. We focus on velocity and pseudo-equivalent width measurements of the Si II 4130, 5972, and 6355 A lines, as well those of the Ca II near-infrared (NIR) triplet, up to +5 days relative to the SN B-band maximum light. We find that a high-velocity component of the Ca II NIR triplet is needed to explain the spectrum in ~95 per cent of SNe Ia observed before -5 days, decreasing to ~80 per cent at maximum. The average velocity of the Ca II high-velocity component is ~8500 km/s higher than the photospheric component. We confirm previous results that SNe Ia around maximum light with a larger contribution from the high-velocity component relative to the photospheric component in their Ca II NIR feature have, on average, broader light curves and lower Ca II NIR photospheric velocities. We find that these relations are driven by both a stronger high-velocity component and a weaker contribution from the photospheric Ca II NIR component in broader light curve SNe Ia. We identify the presence of C II in very-early-time SN Ia spectra (before -10 days), finding that >40 per cent of SNe Ia observed at these phases show signs of unburnt material in their spectra, and that C II features are more likely to be found in SNe Ia having narrower light curves.
It has been reported that the extinction law for Type Ia Supernovae (SNe Ia) may be different from the one in the Milky Way, but the intrinsic color of SNe Ia and the dust extinction are observationally mixed. In this study, we examine photometric properties of SNe Ia in the nearby universe ($z lesssim 0.04$) to investigate the SN Ia intrinsic color and the dust extinction. We focus on the Branch spectroscopic classification of 34 SNe Ia and morphological types of host galaxies. We carefully study their distribution of peak colors on the $B-V$, $V-R$ color-color diagram, as well as the color excess and absolute magnitude deviation from the stretch-color relation of the bluest SNe Ia. We find that SNe Ia which show the reddest color occur in early-type spirals and the trend holds when divided into Branch sub-types. The dust extinction becomes close to the Milky-Way like extinction if we exclude some peculiar red Broad Line (BL) sub-type SNe Ia. Furthermore, two of these red BLs occur in elliptical galaxies, less-dusty environment, suggesting intrinsic color diversity in BL sub-type SNe Ia.
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