Related papers: Results from the Supernova Photometric Classificat…
We present $griz$ photometric light curves for the full 5 years of the Dark Energy Survey Supernova program (DES-SN), obtained with both forced Point Spread Function (PSF) photometry on Difference Images (DIFFIMG) performed during survey…
We present ACS, NICMOS, and Keck AO-assisted photometry of 20 Type Ia supernovae SNe Ia from the HST Cluster Supernova Survey. The SNe Ia were discovered over the redshift interval 0.623 < z < 1.415. Fourteen of these SNe Ia pass our strict…
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…
We present a set of new quantitative classification criteria for major subclasses of Type I Supernovae (SNe). We analyze peak spectra of 146 SNe Ia from the Berkeley Supernova Ia Program (BSNIP), 12 SNe Ib, 19 SNe Ic (including 5 SNe Ic-BL)…
We introduce SuperNNova, an open source supernova photometric classification framework which leverages recent advances in deep neural networks. Our core algorithm is a recurrent neural network (RNN) that is trained to classify light-curves…
We present the first cosmological parameter constraints using measurements of type Ia supernovae (SNe Ia) from the Dark Energy Survey Supernova Program (DES-SN). The analysis uses a subsample of 207 spectroscopically confirmed SNe Ia from…
We present the results of a novel new search of the first data-release from the Sloan Digital Sky Survey (SDSS-DR1) for the spectra of supernovae. The use of large spectroscopic galaxy surveys offers the prospect of obtaining improved…
Improvement in the precision of measurements of cosmological parameters with Type Ia Supernovae (SNIa) is expected to come from large photometrically identified (photometric) SN samples. Here we re-analyse the SDSS photometric SN sample,…
We present a measurement of the volumetric Type Ia supernova (SN Ia) rate based on data from the Sloan Digital Sky Survey II (SDSS-II) Supernova Survey. The adopted sample of supernovae (SNe) includes 516 SNe Ia at redshift z \lesssim 0.3,…
Future photometric supernova surveys will produce vastly more candidates than can be followed up spectroscopically, highlighting the need for effective classification methods based on lightcurves alone. Here we introduce boosting and kernel…
We present a new photometric identification technique for SN 1991bg-like type Ia supernovae (SNe Ia), i.e. objects with light-curve characteristics such as later primary maxima and absence of secondary peak in redder filters. This method is…
We present ugriz light curves for 146 spectroscopically confirmed or spectroscopically probable Type Ia supernovae from the 2005 season of the SDSS-II Supernova survey. The light curves have been constructed using a photometric technique…
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 present a new solution to the problem of classifying Type Ia supernovae from their light curves alone given a spectroscopically confirmed but biased training set, circumventing the need to obtain an observationally expensive unbiased…
We study the utility of a large sample of type Ia supernovae that might be observed in an imaging survey that rapidly scans a large fraction of the sky for constraining dark energy. We consider information from the traditional luminosity…
The Vera C. Rubin Observatory will increase the number of observed supernovae (SNe) by an order of magnitude; however, it is impossible to spectroscopically confirm the class for all the SNe discovered. Thus, photometric classification is…
Supernovae Type-Ia (SNeIa) play a significant role in exploring the history of the expansion of the Universe, since they are the best-known standard candles with which we can accurately measure the distance to the objects. Finding large…
The CNIa0.02 project aims to collect a complete, nearby sample of Type Ia supernovae (SNe Ia) light curves, and the SNe are volume-limited with host-galaxy redshifts z_host < 0.02. The main scientific goal is to infer the distributions of…
Large planned photometric surveys will discover hundreds of thousands of supernovae (SNe), outstripping the resources available for spectroscopic follow-up and necessitating the development of purely photometric methods to exploit these…
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,…