Related papers: CCSNscore: A multi-input deep learning tool for cl…

We use the Sloan Digital Sky Survey II Supernova Survey (SDSS-II SNS) data to measure the volumetric core collapse supernova (CCSN) rate in the redshift range (0.03<z<0.09). Using a sample of 89 CCSN we find a volume-averaged rate of (1.06…

Supernova surveys can be used to study a variety of subjects such as: (i) cosmology through type Ia supernovae (SNe), (ii) star-formation rates through core-collapse SNe, and (iii) supernova properties and their connection to host galaxy…

We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are…

The use of Type Ia Supernovae (SNe Ia) to measure cosmological parameters has grown significantly over the past two decades. However, there exists a significant diversity in the SN Ia population that is not well understood. Over-luminous SN…

Observations of core-collapse supernovae (CCSNe) reveal a wealth of information about the dynamics of the supernova ejecta and its composition but very little direct information about the progenitor. Constraining properties of the…

We report updated results for the first 7 years of our program to monitor 27 galaxies within 10 Mpc using the Large Binocular Telescope to search for failed supernovae (SNe) -- core-collapses of massive stars that form black holes without…

The cosmological utility of type Ia Supernovae (SNe) prompted numerous studies of these events, and they are now well characterized observationally, both as individual objects and as a population. In contrast, all other types of SNe (i.e.,…

I present an overview of optical observations (mostly spectra) of Type II, Ib, and Ic supernovae (SNe). SNe II are defined by the presence of hydrogen, and exhibit a very wide variety of properties. SNe II-L tend to show evidence of…

The five-year Dark Energy Survey supernova programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterising the host galaxies of transients plays a…

We constructed 70 SuperNova IDentification (SNID; Blondin & Tonry 2007) supernova (SN) templates using 640 spectra of stripped-envelope core-collapse SNe (SESNe) published by Modjaz et al. (2014). Fifty-six SN templates which are…

Modern time-domain surveys, such as the Zwicky Transient Facility (ZTF), detect far more extragalactic transients than can be spectroscopically classified. Photometric classification offers a scalable alternative, enabling the…

The next Galactic core-collapse supernova (SN) should yield a large number of observed neutrinos. Using Bayesian techniques, we show that with an SN at a known distance up to 25 kpc, the neutrino events in a water Cherenkov detector similar…

Convolutional neural networks (CNNs) have become increasingly popular for solving a variety of computer vision tasks, ranging from image classification to image segmentation. Recently, autonomous vehicles have created a demand for depth…

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.…

We model the distance, extinction, and magnitude probability distributions of a successful Galactic core-collapse supernova (ccSN), its shock breakout radiation, and its massive star progenitor. We find, at very high probability (~100%),…

We present the spectra of 36 Supernovae (SNe) of various types, obtained by the European Supernova Collaboration. Because of the spectral classification and the phase determination at their discovery the SNe did not warrant further study,…

We present 645 optical spectra of 73 supernovae (SNe) of Types IIb, Ib, Ic, and broad-lined Ic. All of these types are attributed to the core collapse of massive stars, with varying degrees of intact H and He envelopes before explosion. The…

Supernova (SN) classification and redshift estimation using photometric data only have become very important for the Large Synoptic Survey Telescope (LSST), given the large number of SNe that LSST will observe and the impossibility of…

The classification of stripped-envelope supernovae (SE-SNe) is revisited using modern data-sets. Spectra are analysed using an empirical method to "blindly" categorise SNe according to spectral feature strength and appearance. This method…

Future time-domain surveys for transient events in the near- and mid-infrared bands will significantly extend our understanding about the physics of the early Universe. In this paper we study the implications of a deep (~27 mag), long-term…