Vol 17, No 9

Mapping the Milky Way with LAMOST I: method and overview

Chao Liu, Yan Xu, Jun-Chen Wan, Hai-Feng Wang, Jeffrey L. Carlin, Li-Cai Deng, Heidi Jo Newberg, Zi-Huang Cao, Yong-Hui Hou, Yue-Fei Wang, Yong Zhang


Abstract We present a statistical method to derive the stellar density profiles of the Milky Way from spectroscopic survey data, taking into account selection effects. We assume the selection function, which can be altered during observations and data reductions, of the spectroscopic survey is based on photometric colors and magnitude. Then the underlying selection function for a line-of-sight can be recovered well by comparing the distribution of the spectroscopic stars in a color-magnitude plane with that of the photometric dataset. Subsequently, the stellar density profile along a line-of-sight can be derived from the spectroscopically measured stellar density profile multiplied by the selection function. The method is validated using Galaxia mock data with two different selection functions. We demonstrate that the derived stellar density profiles reconstruct the true ones well not only for the full set of targets, but also for sub-populations selected from the full dataset. Finally, the method is applied to map the density profiles for the Galactic disk and halo, using the LAMOST RGB stars. The Galactic disk extends to about R = 19 kpc, where the disk still contributes about 10% to the total stellar surface density. Beyond this radius, the disk smoothly transitions to the halo without any truncation, bending or breaking. Moreover, no over-density corresponding to the Monoceros ring is found in the Galactic anti-center direction. The disk shows moderate north–south asymmetry at radii larger than 12 kpc. On the other hand, the R–Z tomographic map directly shows that the stellar halo is substantially oblate within a Galactocentric radius of 20 kpc and gradually becomes nearly spherical beyond 30 kpc.


Keywords methods: statistical — Galaxy: structure — Galaxy: disk — Galaxy: halo — surveys: LAMOST

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