Related papers: Photometry is all you need: supernova classificati…
The coming era of large photometric wide-field surveys will increase the detection rate of supernovae by orders of magnitude. Such numbers will restrict spectroscopic follow-up in the vast majority of cases, and hence new methods based…
Mixture models are often used to identify meaningful subpopulations (i.e., clusters) in observed data such that the subpopulations have a real-world interpretation (e.g., as cell types). However, when used for subpopulation discovery,…
Type IIn supernovae (SNe IIn) are a relatively infrequently observed subclass of SNe whose photometric and spectroscopic properties are varied. A common thread among SNe IIn are the complex multiple-component hydrogen Balmer lines. Owing to…
Type Ia supernovae (SNe Ia) are a prime tool in observational cosmology. A relation between their peak luminosities and the shapes of their light curves allows to infer their intrinsic luminosities and to use them as distance indicators.…
The distance and redshift of a type Ia supernova can be determined simultaneously through its multi-band light curves. This fact may be used for imaging surveys that discover and obtain photometry for large numbers of supernovae; so many…
We present a method designed to identify the spectral type of young (less than ~30 days after explosion) and nearby (z < ~0.05) supernovae (SNe) using their broad-band colors. In particular, we show that stripped-core SNe (i.e., hydrogen…
The 5-year project Supernova Legacy Survey (SNLS) delivers $\sim 100$ Type-Ia supernovae (SNe Ia) per year, in the redshift range $0.3 < z < 1.0$, with well-sampled $g'r'i'z'$ lightcurves. The SNLS Collaboration uses the 1 deg$^2$ Megacam…
Accounting for selection effects in supernova type Ia (SN Ia) cosmology is crucial for unbiased cosmological parameter inference -- even more so for the next generation of large, mostly photometric-only surveys. The conventional "bias…
The spectrum of a supernova is a summation of numerous overlapping atomic line signatures. Consequently, empirical measurements are limited in application when compound features are assumed to be due to one or two spectral lines. Here I…
Type Ia supernovae (SNe Ia) can be calibrated to be good standard candles at cosmological distances. We propose a supernova pencil beam survey that could yield between dozens to hundreds of SNe Ia in redshift bins of 0.1 up to $z=1.5$,…
We present the spectroscopy from 5254 galaxies that hosted supernovae (SNe) or other transient events in the Sloan Digital Sky Survey II (SDSS-II). Obtained during SDSS-I, SDSS-II, and the Baryon Oscillation Spectroscopic Survey (BOSS),…
Accurate classification of transients obtained from spectroscopic data are important to understand their nature and discover new classes of astronomical objects. For supernovae (SNe), SNID, NGSF (a Python version of SuperFit), and DASH are…
Wide field surveys will soon be discovering Type Ia supernovae (SNe) at rates of several thousand per year. Spectroscopic follow-up can only scratch the surface for such enormous samples, so these extensive data sets will only be useful to…
The case of SN Ia Hubble diagrams from photometrically selected samples using photometric SN host galaxy redshifts is investigated. The host redshift uncertainties and the contamination by core collapse SNe are addressed. As a test, we use…
We present a sample of 485 photometrically identified Type Ia supernova candidates mined from the first three years of data of the CFHT SuperNova Legacy Survey (SNLS). The images were submitted to a deferred processing independent of the…
This paper introduces SS-MixNet, a lightweight and effective deep learning model for hyperspectral image (HSI) classification. The architecture integrates 3D convolutional layers for local spectral-spatial feature extraction with two…
Type Ib and Ic supernovae (SNe Ib/Ic) are the bright finale of massive stars that have lost their hydrogen envelopes, making them powerful probes of mass stripping in massive star evolution. The advent of modern large photometric and…
We present a new technique to create a bin-averaged Hubble Diagram (HD) from photometrically identified SN~Ia data. The resulting HD is corrected for selection biases and contamination from core collapse (CC) SNe, and can be used to infer…
We propose a method for the unsupervised clustering of hyperspectral images based on spatially regularized spectral clustering with ultrametric path distances. The proposed method efficiently combines data density and geometry to…
In the course of the Sloan Digital Sky Survey (SDSS-I), a large fraction of the surveyed area was observed more than once due to field tiling overlap, usually at different epochs. We utilize some of these data to perform a supernova (SN)…