Related papers: Extracting clean supernova spectra
We develop a method to measure the strength of the absorption features in Type Ia supernova (SN Ia) spectra and use it to make a quantitative comparison between the spectra of Type Ia supernovae at low and high redshifts. In this case…
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…
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…
Type Ia Supernovae (SNe Ia) spectra are compared regarding the coefficient of the largest wavelet scale in their decomposition. Two distinct subgroups were identified and their occurrence is discussed in light of use of SNe Ia as…
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…
The Nancy Grace Roman Space Telescope will carry out a wide-field imaging and slitless spectroscopic survey of Type Ia Supernovae to improve our understanding of dark energy. Crucial to this endeavor is obtaining supernova spectra…
The light from distant supernovae (SNe) can be magnified through gravitational lensing when a foreground galaxy is located along the line of sight. This line-up allows for detailed studies of SNe at high redshift that otherwise would not be…
Large photometric surveys of transient phenomena, such as Pan-STARRS and LSST, will locate thousands to millions of type Ia supernova candidates per year, a rate prohibitive for acquiring spectroscopy to determine each candidate's type and…
[Abridged] We investigate the use of a wide variety of spectroscopic measurements to determine distances to low-redshift Type Ia supernovae (SN Ia). We consider linear models for predicting distances to SN Ia using light-curve width and…
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…
GMOS optical long-slit spectroscopy at the Gemini-North telescope was used to classify targets from the Supernova Legacy Survey (SNLS) from July 2005 and May 2006 - May 2008. During this time, 95 objects were observed. Where possible the…
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 a method for selecting high-redshift type Ia supernovae (SNe Ia) located via rolling SN searches. The technique, using both color and magnitude information of events from only 2-3 epochs of multi-band real-time photometry, is…
We present data from the Supernova Cosmology Project for five high redshift Type Ia supernovae (SNe Ia) that were obtained using the NICMOS infrared camera on the Hubble Space Telescope. We add two SNe from this sample to a rest-frame…
Type Ia supernovae (SNe Ia) are powerful tools for measuring the expansion history of the universe, but the impact of dust around SNe Ia remains unknown and is a critical systematic uncertainty. One way to improve our empirical description…
The Supernova Cosmology Project has conducted the `See Change' programme, aimed at discovering and observing high-redshift (1.13 $\leq$ z $\leq$ 1.75) Type Ia supernovae (SNe Ia). We used multi-filter Hubble Space Telescope (HST)…
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…
It is now established that there is a dependence of the luminosity of type Ia supernovae (SNe Ia) on environment: SNe Ia in young, star-forming, metal-poor stellar populations appear fainter after light-curve shape corrections than those in…
We present an algorithm to identify the types of supernova spectra, and determine their redshift and phase. This algorithm, based on the correlation techniques of Tonry & Davis, is implemented in the SuperNova IDentification code (SNID). It…
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…