activity
20192022
most citedRecovering the CMB Signal with Machine Learning

26 citations · 34 across the 2 of their papers we have counts for

collaborators

5 papers

astro-ph.CO202226 cited

Recovering the CMB Signal with Machine Learning

Guo-Jian Wang, Hong-Liang Shi, Ye-Peng Yan +4

The cosmic microwave background (CMB), carrying the inhomogeneous information of the very early universe, is of great significance for understanding the origin and evolution of our…

astro-ph.GA2021

Element abundance analysis of the metal-rich stellar halo and high-velocitythick disk in the galaxy

Haifan Zhu, Cuihua Du, Yepeng Yan +3

Based on the second Gaia data release (DR2) and APOGEE (DR16) spectroscopic surveys, wedefined two kinds of star sample: high-velocity thick disk (HVTD) with and metal-…

astro-ph.GA20208 cited

Existence of the Metal-Rich Stellar Halo and High-velocity Thick Disk in the Galaxy

Yepeng Yan, Cuihua Du, Hefan Li +3

Based on the second Gaia data release (DR2), combined with the LAMOST and APOGEE spectroscopic surveys, we study the kinematics and metallicity distribution of the high-velocity st…

astro-ph.GA2019

New nearby hypervelocity stars and their spatial distribution from Gaia DR2

Cuihua Du, Hefan Li, Yepeng Yan +5

Base on about 4,500 large tangential velocity () with high-precision proper motions and parallaxes in Gaia DR2 5D information derived from p…

astro-ph.GA2019

Chemical and Kinematic Properties of the Galactic Disk from the LAMOST and Gaia Sample Stars

Yepeng Yan, Cuihua Du, Shuai Liu +5

We determined the chemical and kinematic properties of the Galactic thin and thick disk using a sample of 307,246 A/F/G/K-type giant stars from the LAMOST spectroscopic survey and…