Spectral diversity of supernovae and their classification
A physically motivated classification of stripped-envelope supernovae
... Post-peak spectral similarity We have considered spectra at times before and around max- imum ...several supernovae where the spectra appear to be ...early spectral similarity it is clear that, aside ...
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Bayesian Single-Epoch Photometric Classification of Supernovae
... of supernovae (SNe) to metal enrichment. Traditional classification based on followup spectroscopy of all candidates is virtually impossible for these large ...spectroscopic classification (so the ...
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Bayesian single-epoch photometric classification of supernovae
... Traditional classification based on follow-up spectroscopy of all candidates is virtually impossible for these large ...a classification of SNe on a statistical basis, rather than case by ...spectroscopic ...
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Intelligent Classification of Supernovae Using Artificial Neural Networks
... The classification of supernovae (explosions of certain stars) divides them into two main types, those of type I do not present Hydrogen in the spectrum while those of type II ...the classification ...
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A Spectrograph for the Rapid Analysis of Transients and Classification of Supernovae
... within the dichromated gelatine layer indicates a periodic modulation of the refractive index that creates a dispersing grating. . . . . . . . . 9 1.6 Simulated data processing sequence to eliminate cosmic ray features ...
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Deep recurrent neural networks for supernovae classification
... classify supernovae ( code available at https: // .../ supernovae ) ...the Supernovae Photometric Classi fi cation Challenge ( SPCC ) data, we fi nd that deep networks are capable of learning about ...
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Ultraviolet diversity of Type Ia Supernovae
... 3.3 Spectral model Despite the strong correlations between light-curve shape and flux, there is additional spectral diversity that is not described by this single ...
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Exploring the spectroscopic diversity of type Ia supernovae with DRACULA: a machine learning approach
... However, our final goal is to be able to identify what different spectral characteristics separate the groups found with our method. Thus, we show in Fig. 8.4 the mean spec- trum of each group in both ...
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Spectral Diversity Successfully Estimates the α-Diversity of Biocrust-Forming Lichens
... Figure 4. ROC curves of the genera classifications and the derived AUC values of the wet samples. The classification of the wet dataset had an average AUC of 0.95 (Figure 4), a kappa coefficient of 0.97 and an ...
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Spectral diversity successfully estimates the α-diversity of biocrust-forming lichens
... Figure 4. ROC curves of the genera classifications and the derived AUC values of the wet samples. The classification of the wet dataset had an average AUC of 0.95 (Figure 4), a kappa coefficient of 0.97 and an ...
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On the diversity of superluminous supernovae: ejected mass as the dominant factor
... The Public ESO Spectroscopic Survey of Transient Ob- jects (PESSTO) has a strategy designed to classify un- usual types of transients early in their evolution, using light curve information from feeder surveys such as La ...
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A statistical approach to identify superluminous supernovae and probe their diversity
... We investigate the identi fication of hydrogen-poor superluminous supernovae (SLSNe I) using a photometric analysis, without including an arbitrary magnitude threshold. We assemble a homogeneous sample of ...
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Spectral Classification of Stars
... Luminosity Classes: I, II, III, IV, V Over the years, astronomers have developed a system for classifying stars according to the widths of their spectral lines. Because the line width depends on pressure in the ...
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Spectral Descriptors for Data Clustering and Classification
... Abstract Spectral Descriptors for Data Clustering and Classification Ramandeep Kaur Grewal Spectral descriptors have received much attention in recent years due in large part to their versatility as well as ...
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Diversity in extinction laws of Type Ia supernovae measured between 0.2 and 2 μm
... respectively. The light curves are then used to calculate the (X − V ) 0 colours shown in Figure 5. As explained in § 4 we also need a template of the spec- tral energy density of the unreddened object in order to be ...
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Spectral Semi Supervised Discourse Relation Classification
... ˆ p(r i ) H(r i ) In this equation, H(r i ) represented the entropy of the distribution of label predictions for the rela- tion r i generated by the current spectral model, which is a measure of the model’s ...
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Vowel and Consonant Classification through Spectral Decomposition
... The spectral universal we have empirically determined is that these two subsets of Ω almost perfectly separate the vowels and con- sonants of the writing system utilized by ...
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Spectral classification features of some Australian soils
... the spectral absorptions of minor amounts of metal oxides, cations and anions, or by anomalies of spectral peaks due to the addition of these elements into the mineral structures (Van der Marel 1976, Nguyen ...
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A Joint Spectral Similarity Measure for Graphs Classification
... graph spectral theory and in many other applications dealing with ...joint spectral similarity (JSS) measure for graphs classification is ...good classification accuracies achieved by JSS ...
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Leaf chemical and spectral diversity in Australian tropical forests
... taxonomic diversity of tropical forest canopies remains difficult to assess at any ecological or geographic ...chemical diversity of species within certain plant families can nearly match that of a forest ...
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