Related papers: ESC Supernova spectroscopy of non-ESC targets

We present a new method for probabilistically classifying supernovae (SNe) without using SN spectral or photometric data. Unlike all previous studies to classify SNe without spectra, this technique does not use any SN photometry. Instead,…

In the era of large all-sky surveys, there will be a need for rapid, automatic classifications of newly discovered transient objects. Our focus here is the classification of supernovae (SNe). We consider random forest machine learning…

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…

With the large amounts of spectroscopic data available today and the very large surveys to come (e.g. Gaia), the need for automatic data analysis software is unquestionable. We thus developed an automatic spectra analysis program for the…

We present a public, open-source relational database (we name kaepora) containing a sample of 4975 spectra of 777 Type Ia supernovae (SNe Ia). Since we draw from many sources, we significantly improve the spectra by inspecting these data…

This chapter describes the current classification scheme of supernovae (SNe). This scheme has evolved over many decades and now includes numerous SN Types and sub-types. Many of these are universally recognized, while there are…

(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…

A Probabilistic Neural Network model has been used for automated classification of ELODIE stellar spectral library consisting of about 2000 spectra into 158 known spectro-luminosity classes. The full spectra with 561 flux bins and a PCA…

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…

In this work, we propose the use of Kernel Principal Component Analysis (KPCA) combined with k = 1 nearest neighbour algorithm (1NN) as a framework for supernovae (SNe) photometric classification. The classification is entirely based on…

We present SNID-SAGE (SuperNova IDentification-Spectral Analysis and Guided Exploration), a framework for supernova spectral classification with both a fully interactive graphical interface and a scriptable command-line pipeline for…

The Sloan Digital Sky Survey II (SDSS-II) Supernova Survey discovered Type Ia supernovae (SNe Ia) in an almost unexplored intermediate redshift range of $0.05 < z < 0.4$ and provided densely sampled multi-color light curves for SN…

Large time-domain sky surveys generate extensive multi-year catalogs of light curves in which scientifically valuable transients, such as supernovae (SNe), are vastly outnumbered by artifacts and routine star variability. While supervised…

In the era of large astronomical surveys, photometric classification of supernovae (SNe) has become an important research field due to limited spectroscopic resources for candidate follow-up and classification. In this work, we present a…

The classification of supernovae (SNe) and its impact on our understanding of the explosion physics and progenitors have traditionally been based on the presence or absence of certain spectral features. However, current and upcoming…

Spectral type recognition is an important and fundamental step of large sky survey projects in the data reduction for further scientific research, like parameter measurement and statistic work. It tends out to be a huge job to manually…

Analyzer of Spectra for Age Determination (ASAD) is a new package that can easily predict the age and reddening of stellar clusters from their observed optical integrated spectra by comparing them to synthesis model spectra. The ages…

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…

Modern supernova (SN) surveys are now uncovering stellar explosions at rates that far surpass what the world's spectroscopic resources can handle. In order to make full use of these SN datasets, it is necessary to use analysis methods that…

An analysis leveraging 170 optical spectra of 35 stripped-envelope (SE) core-collapse supernovae observed by the Carnegie Supernova Project-I and published in a companion paper is presented. Mean template spectra are constructed for the SNe…