Archival Datasets for SuperNova Artificial Inference by Lstm neural networks (SNAIL)

The spectral-observation dataset (enclosed in the file archival_spec_observations.tar.gz) is comprised of 3091 observed spectra from 361 SNe Ia, largely contributed from CfA (Blondin et al. 2012), BSNIP (Silverman et al. 2012), CSP (Folatelli et al. 2013) and Supernova Polarimetry Program (Wang & Wheeler 2008; Cikota et al. 2019a; Yang et al. 2020). The spectral-template dataset (enclosed in the file archival_spec_templates.tar.gz) includes 361 spectral templates, each of them (covering -15 to +33d with wavelength from 3800 to 7200 A) was generated from the available spectroscopic observations of an individual SN via a LSTM neural network model. The auxiliary photometry dataset (enclosed in the file archival_phot_observations.tar.gz) provides the B & V light curves of these SNe (in total, 196 available SNe Ia), that were used to calibrate the synthetic B-V color of the observed spectra. In additional, the two master catalogs give the detailed information about the 361 SNe and their spectroscopic observations, respectively. These datasets are associated to the paper "Spectroscopic Studies of Type Ia Supernovae Using LSTM Neural Networks" (Hu et al. 2022, ApJ, accepted).本光谱观测数据集（打包于压缩文件archival_spec_observations.tar.gz中）共包含361颗Ia型超新星（SNe Ia）的3091条观测光谱，其数据主要来自CfA（Blondin等人，2012年）、BSNIP（Silverman等人，2012年）、CSP（Folatelli等人，2013年）以及超新星偏振测量项目（Wang & Wheeler，2008年；Cikota等人，2019a；Yang等人，2020年）。本光谱模板数据集（打包于压缩文件archival_spec_templates.tar.gz中）共包含361条光谱模板，每条模板的覆盖范围为-15天至+33天，波长区间为3800至7200埃，均通过长短期记忆网络（Long Short-Term Memory, LSTM）模型，基于单颗超新星的可用光谱观测数据生成。本辅助测光数据集（打包于压缩文件archival_phot_observations.tar.gz中）提供了这些Ia型超新星的B波段与V波段光变曲线（共计196颗可用Ia型超新星），该数据被用于校准观测光谱的合成B-V色指数。此外，两份主星表分别提供了这361颗Ia型超新星及其光谱观测的详细信息。本数据集关联于论文《利用长短期记忆网络开展Ia型超新星光谱研究》（Hu等人，2022年，《天体物理学杂志》，已接收）。