Related papers: PHotometry Assisted Spectral Extraction (PHASE) an…

We present 139 spectra of 124 Type Ia supernovae (SNeIa) that were observed at the ESO/VLT during the first three years of the Canada-France-Hawai Telescope (CFHT) Supernova Legacy Survey (SNLS). This homogeneous data set is used to test…

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are…

We use a new technique to extract the spectrum of a supernova from that of the contaminating background of its host galaxy, and apply it to the specific case of high-redshift Type Ia supernova (SN Ia) spectroscopy. The algorithm is based on…

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…

The aim of the work presented in this paper is to test and optimise supernova detection methods based on the optimal image subtraction technique. The main focus is on applying the detection methods to wide field supernova imaging surveys…

We present new techiques for improving the efficiency of supernova (SN) classification at high redshift using 64 candidates observed at Gemini North and South during the first year of the Supernova Legacy Survey (SNLS). The SNLS is an…

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 upcoming Legacy Survey of Space and Time (LSST) conducted by the Vera C. Rubin Observatory will detect millions of supernovae (SNe) and generate millions of nightly alerts, far outpacing available spectroscopic resources. Rapid,…

We use the wide-field capabilities of the 2dF fibre positioner and the AAOmega spectrograph on the Anglo-Australian Telescope (AAT) to obtain redshifts of galaxies that hosted supernovae during the first three years of the Supernova Legacy…

We present GHOST, a database of 16,175 spectroscopically classified supernovae and the properties of their host galaxies. We have developed a host galaxy association method using image gradients that achieves fewer misassociations for low-z…

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…

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,…

This paper introduces a novel feature extraction technique for the analysis of spectral line Stokes profiles. The procedure is based on the use of an auto-associative artificial neural network containing non-linear hidden layers. The neural…

Context. The SDSS-II Supernova Survey, conducted between 2005 and 2007, was designed to detect a large number of Type Ia supernovae (SNe Ia) around z~0.2, the redshift "gap" between low-z and high-z SN searches. The survey has provided…

We present a technique to measure lightcurves of time-variable point sources on a spatially structured background from imaging data. The technique was developed to measure light curves of SNLS supernovae in order to infer their distances.…

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…

We report the results from spectroscopic observations of the multiple images of the strongly lensed Type Ia supernova (SN Ia), iPTF16geu, obtained with ground based telescopes and the Hubble Space Telescope (HST). From a single epoch of…

We study supernova (SN) classification using the machine learning method of the Recurrent Neural Network (RNN) in the Chinese Space Station Survey Telescope Ultra-Deep Field (CSST-UDF) photometric survey, and explore the improvement of the…

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),…

Local spectral similarity (LSS) algorithm has been developed for detecting homogeneous areas and edges in hyperspectral images (HSIs). The proposed algorithm transforms the 3-D data cube (within a spatial window) into a spectral similarity…