Fingerprinting Type I Supernovae: Quantifying Their Diversity and Sharpening Their Utility

I 型超新星指纹识别：量化其多样性并增强其实用性

• 批准号: 1413260
• 负责人: Maryam Modjaz
• 金额: $ 34.43万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1413260&HistoricalAwards=false
• 关键词: Fingerprinting; Type; Supernovae; Quantifying; Their

Exploding stars that show no Hydrogen in their spectra are called Type 1 supernovovae. They are vital for many areas of astrophysics. The most famous sub-class are the Type Ia, which have yielded exciting results about the accelerating expansion of the universe. However, for the next step in precision cosmology, identifications are needed of Type Ia at very large distances, which is difficult, because they are easily confused with other types of Type I supernovae, namely Type Ib/c. This survey will study the observed differences between these supernova types to eliminate mistaken classifications and thus enable a better understanding of the acceleration of our universe at earlier stages in its expansion, billions of years in the past. While Type Ia are the result of thermonuclear explosions of a C-O white dwarf in a binary system, Type Ib/c are core-collapse explosions from massive stars, which have been removed of their outermost H layer. Type Ib/c observations cannot be used to derive accurate distance measurements; however, because their spectra look like Type 1a supernovae, they can contaminate large supernova surveys. This award is to conduct a thorough statistical analysis of optical spectra and lightcurves (records of light emitted over time) of thousands of supernovae in order to distinguish between Type Ia supernova and Types 1b and 1c and remove the impostors from the surveys. This project will develop the tools needed to quickly and automatically identify and remove Type 1b/c supernovae from surveys. The PI will provide these tools and methods to the community for future observations with other telescopes, such as the Large Synoptic Survey Telescope (LSST), which is expected to yield thousands of new supernova candidates per night. The data will also be used to test models of core-collapse explosions of massive stars, which will improve knowledge of stellar evolution. The PI will train and mentor a graduate student and undergraduate student in research, and she will also collaborate with an external organization to recruit a promising high school student from an underrepresented group in the fields of Science, Technology, Engineering and Math (STEM). The work will be done through a two-pronged approach: 1) utilizing the traditional spectral template approach with well-established algorithms, and then 2) employing Principal Component Analysis (PCA) to derive eigenspectrum bases, which if found in a robust fashion, can be easily used to construct average spectral time-series templates and to identify any new classification schemes within the available data. In addition, the PI will clarify the link between SN spectral classification for SN Ib/c, including those connected with Gamma-Ray Bursts (GRBs), and their purported stellar progenitors by testing for hidden He in SN Ic. This will be done by comparing observed spectra and light curves of a large set of SN Ib/c, for the first time, with those predicted from two competing models. The PI will use spectra and lightcurves of over 5800 supernova explosions that are recently published (such as WISeREP and SUSPECT) or are in-hand.

光谱中不含氢的爆炸恒星被称为 1 型超新星。 它们对于天体物理学的许多领域都至关重要。最著名的子类是 Ia 型，它产生了关于宇宙加速膨胀的令人兴奋的结果。然而，精密宇宙学的下一步需要在非常远的距离上识别Ia型超新星，这是很困难的，因为它们很容易与其他类型的I型超新星，即Ib/c型混淆。这项调查将研究观察到的这些超新星类型之间的差异，以消除错误的分类，从而更好地了解宇宙在数十亿年前的膨胀早期阶段的加速。 Ia 型是双星系统中 C-O 白矮星热核爆炸的结果，而 Ib/c 型是大质量恒星的核心塌缩爆炸，这些恒星的最外层 H 层已被移除。 Ib/c 类观测结果不能用于得出准确的距离测量结果；然而，由于它们的光谱看起来像 1a 型超新星，它们可能会污染大型超新星勘测。该奖项旨在对数千颗超新星的光谱和光曲线（随时间推移发出的光的记录）进行彻底的统计分析，以区分 Ia 型超新星和 1b 型和 1c 型超新星，并从调查中剔除冒名顶替者。 该项目将开发快速自动识别 1b/c 型超新星并将其从调查中移除所需的工具。 PI 将向社区提供这些工具和方法，以便将来使用其他望远镜进行观测，例如大型综合巡天望远镜 (LSST)，预计每晚将产生数千个新的超新星候选者。 这些数据还将用于测试大质量恒星核心塌缩爆炸的模型，这将提高对恒星演化的了解。 PI 将培训和指导一名研究生和本科生进行研究，她还将与外部组织合作，从科学、技术、工程和数学 (STEM) 领域代表性不足的群体中招募一名有前途的高中生。这项工作将通过双管齐下的方法来完成：1）利用传统的谱模板方法和完善的算法，然后 2）采用主成分分析（PCA）来导出特征谱基础，如果以稳健的方式找到特征谱基础，可以轻松地用于构建平均光谱时间序列模板并识别可用数据中的任何新分类方案。此外，PI 将通过测试 SN Ic 中隐藏的 He 来澄清 SN Ib/c 的 SN 光谱分类之间的联系，包括与伽马射线暴 (GRB) 相关的光谱分类及其所谓的恒星祖细胞。 这将通过首次将大量 SN Ib/c 的观测光谱和光变曲线与两个竞争模型预测的光谱和光变曲线进行比较来完成。 PI 将使用最近发表的（例如 WISeREP 和 SUSPECT）或现有的 5800 多个超新星爆炸的光谱和光曲线。