.png){kind=icon}
返回
STag: Supernova Tagging and Classification
.png){kind=icon}
OA
AI
DOI：10.3847/1538-4357/ac3422.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Supernovae classes have been defined phenomenologically, based on spectral features and time series data, since the specific details of the physics of the different explosions remain unrevealed. However, the number of these classes is increasing as objects with new features are observed, and the next generation of large surveys will only bring more variety to our attention. We apply the machine learning technique of multi-label classification to the spectra of supernovae. By measuring the probabilities of specific features or tags in the supernova spectra, we can compress the information from a specific object down to that suitable for a human or database scan, without the need to directly assign to a reductive class. We use logistic regression to assign tag probabilities, and then a feed-forward neural network to filter the objects into the standard set of classes, based solely on the tag probabilities. We present STag, a software package that can compute these tag probabilities and make spectral classifications.
Keyword:
ELECTRON-CAPTURE SUPERNOVAE
CORE-COLLAPSE
DATA REDUCTION
IA PROGRAM
REDSHIFT
SPECTROSCOPY
EVOLUTION
SPECTRA
II.
期刊
IF:
5.4
论文数:
8.3W
被引数:
32.0W
机构
引用论文
.png){kind=icon}
Bioreductive deposition of palladium (0) nanoparticles onShewanella oneidensiswith catalytic activity towards reductive dechlorination of polychlorinated biphenyls钯 (0) 纳米颗粒在 Shewanella oneidensis 上的生物还原沉积，对多氯联苯的还原脱氯具有催化活性
PREAI
分享收藏Modeling atrial fibrosis in vitro—Generation and characterization of a novel human atrial fibroblast cell line模拟心房纤维化 体外 -新型人心房成纤维细胞系的产生和表征
OAAI
OAAI分享收藏
查看更多内容