论文标题
基于光谱时期能量分布的超新星的表征：可能的两个SN IB亚型
Characterization of Supernovae Based on the Spectral-Temporal Energy Distribution: Possible two SN Ib Subtypes
论文作者
论文摘要
提出了基于它们的光谱时间序列与多波段光度计的频谱时间序列之间的定量数据驱动比较。我们将无监督的随机森林算法用作一组82个有据可查的SNE的度量，代表所有主要的光谱类型，以将它们嵌入反映对象之间共享相关性的抽象度量空间中。我们在3D中可视化所得的度量空间，从而揭示了与当前光谱分类方案的强烈一致性。嵌入IB型超新星嵌入两组，一个亚组表现出比另一组更广泛，更突出，更高的线条，可能需要提示新的SN IB子类。该方法可能是根据他们与已知事件组的距离对新发现的SNE进行分类，或者最终设计一种新的光谱时空分类方案。这种嵌入也可能取决于隐藏的参数，这可能是可以在物理上可以解释的。
A quantitative data-driven comparison among supernovae (SNe) based on their spectral time series combined with multi-band photometry is presented. We use an unsupervised Random Forest algorithm as a metric on a set of 82 well-documented SNe representing all the main spectroscopic types, in order to embed these in an abstract metric space reflecting shared correlations between the objects. We visualize the resulting metric space in 3D, revealing strong agreement with the current spectroscopic classification scheme. The embedding splits Type Ib supernovae into two groups, with one subgroup exhibiting broader, less prominent, higher-velocity lines than the other, possibly suggesting a new SN Ib subclass is required. The method could be to classify newly discovered SNe according to their distance from known event groups, or ultimately to devise a new, spectral-temporal classification scheme. Such an embedding could also depend on hidden parameters which may perhaps be physically interpretable.
