The Global Asteroseismology Project Proof of Concept: Asteroseismology of Massive Stars with Continuous Ground-based Observations

Noi Shitrit,Iair Arcavi

ASTRONOMICAL JOURNAL(2024)

引用 0|浏览0
暂无评分
摘要
Massive (greater than or similar to 8M circle dot) stars are the progenitors of many astrophysical systems, yet key aspects of their structure and evolution are poorly understood. Asteroseismology has the potential to solve these open puzzles; however, sampling both the short period pulsations and long period beat patterns of massive stars poses many observational challenges. Ground-based single-site observations require years or decades to discern the main oscillation modes. Multisite campaigns were able to shorten this time span, but have not been able to scale up to population studies on sample of objects. Space-based observations can achieve both continuous sampling and observe large numbers of objects; however, most lack the multiband data that is often necessary for mode identification and removing model degeneracies. Here, we develop and test a new ground-based observational strategy for discerning and identifying the main oscillation modes of a massive star in a few months, in a way that can be scaled to large samples. We do so using the Las Cumbres Observatory-a unique facility consisting of robotic, homogeneous telescopes operating as a global network, overcoming most of the challenges of previous multisite efforts, but presenting new challenges which we tailor our strategy to address. This work serves as the proof of concept for the Global Asteroseismology Project, which aims to move massive star asteroseismology from single-objects to bulk studies, unleashing its full potential in constraining stellar structure and evolution models. This work also demonstrates the ability of the Las Cumbres Observatory to perform multisite continuous observations for various science goals.
更多
查看译文
关键词
Ground-based astronomy,Astronomical methods,Astronomical techniques,Observational astronomy,Massive stars,Asteroseismology
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要