2024年3月03日, 星期日

【DoA Colloquium】January 2nd by Xiangxiang Xue

日历
研讨会日历
Date
01.02.2024 4:00 pm - 5:00 pm

Description

Title: Mapping the Milky Way halo using LAMOST 

Speaker: Xiangxiang Xue 


Abstract: The stellar halo of the Milky Way comprises only a small fraction of all stars in our Galaxy, but these stars are high diagnostic value for probing the Milky Way’s dark matter halo and formation history. Stars extending to ~100 kpc make for an excellent dynamical probe of the halo mass profile, and the long dynamical periods at such large radii (~1 Gyr) mean that the dynamical formation imprint is still very apparent, e.g. in so called sub-structures. However, our knowledge of the halo is fragmentary, at least partly because of the paucity of halo stars, with known 3D positions, radial velocities and abundances. Nowadays, with the development of large-scale sky surveys and space astrometry mission, such as 2MASS, SDSS, PanSTARRS1, LAMOST and Gaia, halo star samples are now of sufficient size and quality to boost the study of the Galactic halo. In this talk, I will show you how to map the Milky Way halo using halo stars drown from LAMOST survey. 

 
Bio: Dr. Xiangxiang Xue is a professor at the National Astronomical Observatory of the Chinese Academy of Sciences (NAOC). She received her Ph.D. degree from NAOC in 2009, and then moved to Germany to carrying out postdoctoral research at the Max Planck-Institute for Astronomy from 2011 to 2016. She joined NAOC in 2016. Throughout her career, she was selected as a Humboldt fellow and then for the National Program for Overseas High-level Talents. She has long been engaged in the study of the dynamics, structure, and formation history of the Galactic halo using the large sky surveys, including SDSS, LAMOST, and Gaia. She has published over 50 SCI papers with more than 2000 citations. 

 

Time: 16:00-17:00PM, 2/Jan, Tuesday

Venue: Room 508 (large seminar room), Department of Astronomy 

 

You can also access the colloquium via :

https://m.koushare.com/topic-sc/i/physics_sjtu