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Accretion and Feedback in Massive Star Formation

发布时间:2022-10-19

讲座论坛 期数 天文系学术报告
主题 演讲者 Yichen Zhang
时间 2022年10月21日 (周五) 10:00 机构 University of Virginia
地点 物理楼552

itle:Accretion and Feedback in Massive Star Formation

Speaker: Yichen Zhang (online)

Institute: University of Virginia

Time: 10:00-12:00, Friday, October 21

Location: Physics Building 552

Tencent Meeting ID: 576-3815-8985

点击链接入会,或添加至会议列表:

https://meeting.tencent.com/dm/9Cz5G51JgoQW

Abstract:

Recent ALMA high-resolution observations start to reveal accretion and feedback processes in massive star formation with great details, including disk formation, binary formation, outflow launching, and photoionization feedback. In this talk, I will present some of the examples from our recent observational studies. In general, our results show quite ordered behaviors of accretion within 1000 au scale of massive protostars. Our results show the importance of using different tracers, including different types of molecular and recombination lines, in deciphering the dynamics of the innermost region of massive star formation. In particular, our observations have suggested a pattern in which typical hot-core tracers and complex organic molecules tend to trace the envelope/core, while the disks or disk surface can be better traced by refractory molecules, as well as high energy level transitions of simple molecules. In many cases, hydrogen recombination lines are also found, tracing compact rotating structures, or the launch of photoevaporative outflows within 100 au scale. The coexistence of accretion and ionizing feedback suggests that accretion can continue after the onset of photoionization feedback.

Bio:

I obtained my Ph.D. from University of Florida in 2013. I then became a joint postdoc in Yale University and Universidad de Chile for three years. I moved to the RIKEN institute in Japan in 2016 and stayed there for five years. I am currently a postdoc researcher in the Astronomy Department of University of Virginia. My main research topic is star formation, using both theoretical modeling and observation.

Related papers:

https://ui.adsabs.harvard.edu/abs/2022ApJ...936...68Z/abstract

https://ui.adsabs.harvard.edu/abs/202