Statistical analysis of the light curve characteristics and energy sources of superluminous supernovae
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摘要: 统计了91颗贫氢超亮超新星的光变特征，并结合3种供能模型进行了蒙特卡罗模拟，以探究实际观测对其能源机制的约束. 结果显示：这些超亮超新星在g波段的平均峰值绝对星等为（−21.34±0.8）等，上升和下降时标分别分布在7~79 d和14~114 d，并呈现显著正相关；模拟结果表明磁星和相互作用机制都可能为大部分超亮超新星供能，在相互作用模型中，基于壳层分布假设的模拟结果与观测符合得更好. 国内各大巡天项目（如CSST、司天工程）未来将探测到更多高红移超亮超新星，以期为相关科研人员深入了解宇宙中的恒星演化和爆炸过程提供重要数据.Abstract: Superluminous supernovae have been the focus of supernova research for nearly two decades. Their high luminosity makes them of great significance for studying the first-generation stars and the early universe. However, the underlying energy mechanism remains unclear. In this study, we collected 91 hydrogen-poor superluminous supernovae （SLS-I） with well-sampled light curves （LCs）, and extracted their LC characteristics for statistical analysis. Markov Chain Monte Carlo （MCMC） simulations were carried out to reproduce these observables considering three power mechanisms. The constraints combining observations on their energy mechanism were systematically explored. The results show that the average peak absolute magnitude of SLS-I at g band was −21.34 ± 0.8 mag, and the rising and declining time scales were distributed in 7~79 days and 14~114 days, where a strong correlation exists. The simulation results show that both the magnetar and the interaction mechanism can power most SLS-I. Under the interaction framework, the shell-like scenario is preferred based on the comparison with observations. In the future, domestic telescopes and all-sky surveys （such as CSST and SiTian） will detect more superluminous supernovae at high redshift, providing important information for a more comprehensive understanding of massive star evolution and explosions.
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Key words:
- supernovae /
- light curves /
- magnetars /
- Markov Chain Monte Carlo
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