Related papers: Single-epoch supernova classification with deep co…
A method is presented for automated photometric classification of supernovae (SNe) as Type-Ia or non-Ia. A two-step approach is adopted in which: (i) the SN lightcurve flux measurements in each observing filter are fitted separately; and…
One of the brightest objects in the universe, supernovae (SNe) are powerful explosions marking the end of a star's lifetime. Supernova (SN) type is defined by spectroscopic emission lines, but obtaining spectroscopy is often logistically…
We present an empirical method which measures the distance to a Type Ia supernova (SN Ia) with a precision of ~ 10% from a single night's data. This method measures the supernova's age and luminosity/light-curve parameter from a spectrum,…
Type Ia supernovae (SNe Ia) are one of the major tools to determine the cosmological parameters. Utilizing them as distance indicators, it is possible to geometrically survey the universe. To this end, the intrinsic scatter in 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…
Motivated by the fact that calibrated light curves of Type Ia supernovae (SNe Ia) have become a major tool to determine the expansion history of the Universe, considerable attention has been given to, both, observations and models of these…
We present a novel method of classifying Type Ia supernovae using convolutional neural networks, a neural network framework typically used for image recognition. Our model is trained on photometric information only, eliminating the need for…
Type Ia supernovae (SNe Ia) have been intensively investigated due to its great homogeneity and high luminosity, which make it possible to use them as standardizable candles for the determination of cosmological parameters. In 2011, the…
Type Ia supernovae (SNe Ia) are a prime tool in observational cosmology. A relation between their peak luminosities and the shapes of their light curves allows to infer their intrinsic luminosities and to use them as distance indicators.…
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…
Theoretical and observational cosmology have enjoyed a number of significant successes over the last two decades. Cosmic microwave background measurements from the Wilkinson Microwave Anisotropy Probe and Planck, together with large-scale…
Type Ia supernovae (SNe Ia) are used as distance indicators to infer the cosmological parameters that specify the expansion history of the universe. Parameter inference depends on the criteria by which the analysis SN sample is selected.…
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…
As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multi-band light-curves and host galaxy redshifts. For this analysis, we use the…
Type Ia supernovae (SNe Ia) can be calibrated to be good standard candles at cosmological distances. We propose a supernova pencil beam survey that could yield between dozens to hundreds of SNe Ia in redshift bins of 0.1 up to $z=1.5$,…
Type Ia supernovae (SNe Ia) are standarizable candles whose observed light curves can be used to infer their distances, which can in turn be used in cosmological analyses. As the quantity of observed SNe Ia grows with current and upcoming…
We discuss the extent to which photometric measurements alone can be used to identify Type Ia supernovae (SNIa) and to determine redshift and other parameters of interest for cosmological studies. We fit the light curve data of the type…
Type Ia supernovae (SNe~Ia) are central to studies of cosmic expansion, under the assumption that their absolute magnitude $M_B$ does not evolve with redshift. Even small drifts in brightness can bias cosmological parameters such as $H_0$…
The revolutionary discovery of dark energy and accelerating cosmic expansion was made with just 42 type Ia supernovae (SNe Ia) in 1999. Since then, large synoptic surveys, e.g., Dark Energy Survey (DES), have observed thousands more SNe Ia…
The use of type Ia supernovae (SNe Ia) as cosmological standard candles is fundamental in modern observational cosmology. In this letter, we derive a simple empirical photometric redshift estimator for SNe Ia using a training set of SNe Ia…