2 citations · 2 across the 5 of their papers we have counts for
5 papers · 1 filter
Seeing Wiggles without Seeing Wiggles: BAO Recovery in 21 cm Intensity Mapping with Deep Learning
Kaifeng Yu, Xin Wang
The 21 cm intensity mapping provides a promising probe of the large-scale structure. Astrophysical foregrounds, as the main source of contamination to the cosmological 21 cm signal…
Recovering Cosmic Structure with a Simple Physical Constraint
Tian-Cheng Luan, Xin Wang, Jiacheng Ding +3
Radio observation of the large-scale structure (LSS) of our Universe faces major challenges from foreground contamination, which is many orders of magnitude stronger than the cosmi…
Restoring Missing Modes of 21cm Intensity Mapping with Deep Learning: Impact on BAO Reconstruction
Qian Li, Xin Wang, Xiaodong Li +3
In 21cm intensity mapping of the large-scale structure (LSS), regions in Fourier space could be compromised by foreground contamination. In interferometric observations, this conta…
Correlation-based Beam Calibration of 21cm Intensity Mapping
Jiacheng Ding, Xin Wang, Ue-Li Pen +1
Foreground removal presents a significant obstacle in both current and forthcoming intensity mapping surveys. While numerous techniques have been developed that show promise in sim…
Reconstructing the Baryonic Acoustic Oscillations in the presence of photo- uncertainties
Kwan Chuen Chan, Guoyuan Lu, Xin Wang
The reconstruction method has been widely employed to improve the Baryon Acoustic Oscillations (BAO) measurement in spectroscopic survey data analysis. In this study, we explore th…