Collaborative Research: Unravelling Stripped Supernovae - Synergy between Observations and Modeling

人们早就知道，宇宙中的大质量恒星死于被称为超新星（SNe）的大规模爆炸。 由大质量恒星核心坍缩产生的超新星被天文学家分为几类。 一种是正常的SNe，其巨大的祖先已经剥离了氢和氦的外壳，因此被称为“剥离超新星”。另一种类型被归类为SNe Ic，有或没有伴随的伽马射线爆发（GRB），它发出高能辐射的相对论喷流。这些爆炸可以在很大的宇宙学距离上看到，对天体物理学的许多领域都很重要。弗吉尼亚大学和密歇根州立大学之间的一项研究合作将解决一些关于SNe的悬而未决的问题，例如哪些大质量的剥离恒星以何种方式死亡，以及这些爆炸的详细祖先构成是什么？ 这项工作将涉及分析来自大量剥离SNe的数据，以及通过名为TARDIS的开源辐射传输软件对这些数据和其他已发布的数据进行建模，并结合使用称为仿真器的机器学习技术来有效扫描大量参数。 此外，为了增加STEM中代表性不足的群体的成员数量，首席调查员将与两个不同的项目合作（一个是弗吉尼亚州中学女生的暑期项目“女孩探索宇宙”，另一个是东兰辛的一所高中，MI）让他们的学生参与不同的研究项目，从为TARDIS代码做贡献到使用拟议的小部件，TARDIS模拟最近观察到的SN光谱。有证据表明，结合实践研究，编码活动和榜样的学龄计划往往会增加女孩和少数民族在STEM职业中的自信心和兴趣。研究人员的目标是解决SN社区最近的两个争议，对恒星演化具有强烈的影响，了解喷气机产生所需的条件，以及激烈争论的SN-GRB祖先模型。清楚地了解SN和GRB的恒星祖先和爆炸参数是将它们用作宇宙学距离上星星形成的指标和评估它们作为宇宙再电离源的重要基础。 拟议的活动将改变剥离SN领域：它们将首次量化模拟这些爆炸的系统和统计不确定性，并将光谱已建模的物体总数增加到至少185个SNe，这构成了世界上最大的剥离SN数据集，并使该领域能够从单个物体完全过渡到群体研究。此外，拟议框架将以统一和一致的方式这样做。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

It has long been known that massive stars in the universe die in massive explosions known as supernovae (SNe). Supernovae resulting from the core collapse of massive stars are classified by astronomers in several ways. One type is normal SNe, whose massive progenitors have been stripped of their hydrogen and helium envelopes, thus known as “stripped supernovae.” Another type is classified as SNe Ic, with or without an accompanying gamma-ray burst (GRB), which emits relativistic jets of high-energy radiation. These explosions can be seen to large cosmological distances and are important for many fields of astrophysics. A research collaboration between the University of Virginia and Michigan State University will address some of the outstanding questions about SNe, such as which massive, stripped stars die in which kinds of deaths, and what is the detailed progenitor makeup for these explosions? The work will involve analyzing data from a large set of stripped SNe, as well as modeling those data and other published data via the open-source radiative transfer software called TARDIS, in combination with use of the machine-learning technology known as emulators for efficiently scanning large sets of parameters. In addition, to increase the number of members of underrepresented groups in STEM, the lead investigators will collaborate with two different programs (one, Girls Exploring the Universe, a summer program for middle school girls in Virginia, and the other at a high school in East Lansing, MI) to involve their students in different research projects that range from contributing to the TARDIS code to using the proposed widget that compares TARDIS simulations to recently observed SN spectra. Evidence suggests that school-age programs incorporating hands-on research, coding activities, and role models tend to increase self-confidence and interest of girls and minorities in STEM careers.The researchers aim to resolve two recent controversies in the SN community, with strong implications for stellar evolution, understanding the conditions needed for jet production, and for the hotly debated SN-GRB progenitor models. A clear understanding of the stellar progenitors and explosion parameters of SN and GRBs is an essential foundation for using them as indicators of star formation over cosmological distances and for assessing them as sources of re-ionizing the Universe. The proposed activities will transform the field of stripped SNe: they will quantify, for the first time, the systematic and statistical uncertainties in modeling these explosions and increase the total number of objects whose spectra have been modeled to at least 185 SNe, which constitutes the largest data set of Stripped SN in the world and allows the field to fully transition from individual objects to population studies. Moreover, the proposed framework will do so in a homogeneous and consistent manner. The proposed rapid and statistically solid theoretical interpretation framework will be made public.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.