Related papers: A New Method to Classify Type IIP/IIL Supernovae B…

We investigate polarization spectra of hydrogen-rich core-collapse supernovae (Type~II SNe). The polarization signal from SNe contains two independent components: intrinsic SN polarization and interstellar polarization (ISP). From these…

This paper presents a novel method for determining the probability that a supernova candidate belongs to a known supernova type (such as Ia, Ibc, IIL, \emph{etc.}), using its photometric information alone. It is validated with Monte Carlo,…

We present {\tt deepSIP} (deep learning of Supernova Ia Parameters), a software package for measuring the phase and -- for the first time using deep learning -- the light-curve shape of a Type Ia supernova (SN~Ia) from an optical spectrum.…

In this work, we present classification results on early supernova lightcurves from SCONE, a photometric classifier that uses convolutional neural networks to categorize supernovae (SNe) by type using lightcurve data. SCONE is able to…

We present a semi-supervised method for photometric supernova typing. Our approach is to first use the nonlinear dimension reduction technique diffusion map to detect structure in a database of supernova light curves and subsequently employ…

(abridged) Ongoing supernova (SN) surveys find hundreds of candidates, that require confirmation for their use. Traditional classification based on followup spectroscopy of all candidates is virtually impossible for these large samples. We…

Using the largest spectroscopic dataset of stripped-envelope core-collapse supernovae (stripped SNe), we present a systematic investigation of spectral properties of Type IIb SNe (SNe IIb), Type Ib SNe (SNe Ib), and Type Ic SNe (SNe Ic).…

We use published spectroscopic and photometric data for 8 Type Ia supernovae to construct a dispersion spectrum for this class of object, showing their diversity over the wavelength range 3700A to 7100A. We find that the B and V bands are…

Photometric classification of Type Ia supernovae (SNe Ia) is critical for cosmological studies but remains difficult due to class imbalance and observational noise. While deep learning models have been explored, they are often…

We have publicly released a blinded mix of simulated SNe, with types (Ia, Ib, Ic, II) selected in proportion to their expected rate. The simulation is realized in the griz filters of the Dark Energy Survey (DES) with realistic observing…

Automated classification of supernovae (SNe) based on optical photometric light curve information is essential in the upcoming era of wide-field time domain surveys, such as the Legacy Survey of Space and Time (LSST) conducted by the Rubin…

We examine the relationship between three parameters of Type Ia supernovae (SNe~Ia): peak magnitude, rise time, and photospheric velocity at the time of peak brightness. The peak magnitude is corrected for extinction using an estimate…

While the members of the Type IIn category of supernovae are united by the presence of strong multicomponent Balmer emission lines in their spectra, they are quite heterogeneous with respect to other properties such as Balmer line profiles,…

Herein we analyse late-time (post-plateau; 103 < t < 1229 d) optical spectra of low-redshift (z < 0.016), hydrogen-rich Type IIP supernovae (SNe IIP). Our newly constructed sample contains 91 nebular spectra of 38 SNe IIP, which is the…

We analyse late-time observations, available photometry and spectra, of a sample of type II plateau supernovae (SNe IIP). The possibility of using H$\alpha$ luminosity at the nebular epoch as a tracer of $^{56}$Ni mass in this class of…

Type Ia supernovae (SNe Ia) provide us with a unique tool for measuring extragalactic distances and determining cosmological parameters. As a result, the precise and effective calibration for peak luminosities of SNe Ia becomes extremely…

We present an algorithm to identify the type of an SN spectrum and to determine its redshift and age. This algorithm, based on the correlation techniques of Tonry & Davis, is implemented in the Supernova Identification (SNID) code. It is…

We present a new method to photometrically delineate between various sub-types of type Ia supernovae (SNe Ia). Using the color-stretch parameters, $s_{BV}$ or $s_{gr}$, and the time of i-band primary maximum relative to the B-band or g-band…

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…

The Pan-STARRS1 (PS1) survey has obtained imaging in 5 bands (grizy_P1) over 10 Medium Deep Survey (MDS) fields covering a total of 70 square degrees. This paper describes the search for apparently hostless supernovae (SNe) within the first…