相关论文: Using Multi-Band Photometry to Classify Supernovae

This paper presents spectroscopy of supernovae discovered in the first season of the Sloan Digital Sky Survey-II Supernova Survey. This program searches for and measures multi-band light curves of supernovae in the redshift range z = 0.05 -…

Due to their high intrinsic brightness, type II supernovae (SN) can be used as lighthouses to constrain distances in the Universe using variants of the Baade-Wesselink method. Based on a large set of CMFGEN models (Hillier & Miller 1998)…

The SuperNovae Analysis aPplication (SNAP) is a new tool for the analysis of SN observations and validation of SN models. SNAP consists of an open source relational database with (a) observational light curve, (b) theoretical light curve,…

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…

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…

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 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…

We present ultravioliet (UV) observations of supernovae (SNe) obtained with the UltraViolet/Optical Telescope (UVOT) on board the Swift spacecraft. This is the largest sample of UV light curves from any single instrument and covers all…

We present a comprehensive analysis of the early spectra of type II and type IIb supernovae (SNe) to explore their diversity and distinguishable characteristics. Using 866 publicly available spectra from 393 SNe, 407 from type IIb SNe (SNe…

This paper presents a novel method for determining the probability that a supernova candidate belongs to a known supernova type (such as Ia, Ibc, IIL, \emph{etc.}), using its photometric information alone. It is validated with Monte Carlo,…

The classification of stripped-envelope supernovae (SE-SNe) is revisited using modern data-sets. Spectra are analysed using an empirical method to "blindly" categorise SNe according to spectral feature strength and appearance. This method…

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…

Upcoming photometric surveys will discover tens of thousands of Type Ia supernovae (SNe Ia), vastly outpacing the capacity of our spectroscopic resources. In order to maximize the science return of these observations in the absence of…

We present an empirical model of Type Ia supernovae spectro-photometric evolution with time. The model is built using a large data set including light-curves and spectra of both nearby and distant supernovae, the latter being observed by…

We present the discovery of a Type Ia supernova (SN) at redshift $z = 1.914$ from the CANDELS multi-cycle treasury program on the \textit{Hubble Space Telescope (HST)}. This SN was discovered in the infrared using the Wide-Field Camera 3,…

Accurate classification of transients obtained from spectroscopic data are important to understand their nature and discover new classes of astronomical objects. For supernovae (SNe), SNID, NGSF (a Python version of SuperFit), and DASH are…

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…

Superluminous supernovae (SLSNe) have been detected to $z\sim4$ and can be detected to $z\gtrsim15$ using current and upcoming facilities. SLSNe are extremely UV luminous, and hence objects at $z\gtrsim7$ are detected exclusively via their…

With the number of supernovae observed expected to drastically increase thanks to large-scale surveys like the Dark Energy Spectroscopic Instrument (DESI), it is necessary that the tools we use to classify these objects keep up with this…

We present the snapshot distance method (SDM), a modern incarnation of a proposed technique for estimating the distance to a Type Ia supernova (SN Ia) from minimal observations. Our method, which has become possible owing to recent work in…