5 papers
Extracting redshifts from 2D slitless spectroscopic images using deep learning for the CSST galaxy survey
Xingchen Zhou, Yan Gong, Xin Zhang +4
Wide-field slitless spectroscopic galaxy surveys, such as the one performed by the upcoming Chinese Space Station Survey Telescope (CSST), are crucial for precision cosmology but p…
AI Agent for Source Finding by SoFiA-2 for SKA-SDC2
Xingchen Zhou, Nan Li, Peng Jia +7
Source extraction is crucial in analyzing data from next-generation, large-scale sky surveys in radio bands, such as the Square Kilometre Array (SKA). Several source extraction pro…
GalaxyGenius: Mock galaxy image generator for various telescopes from hydrodynamical simulations
Xingchen Zhou, Hang Yang, Nan Li +11
We introduce GalaxyGenius, a Python package designed to produce synthetic galaxy images tailored to different telescopes based on hydrodynamical simulations. Its implementation wil…
Estimating Photometric Redshifts for Galaxies from the DESI Legacy Imaging Surveys with Bayesian Neural Networks Trained by DESI EDR
Xingchen Zhou, Nan Li, Hu Zou +6
We present a catalogue of photometric redshifts for galaxies from DESI Legacy Imaging Surveys, which includes billion sources covering 14,000 . The photomet…
Accurately Estimating Redshifts from CSST Slitless Spectroscopic Survey using Deep Learning
Xingchen Zhou, Yan Gong, Xin Zhang +10
Chinese Space Station Telescope (CSST) has the capability to conduct slitless spectroscopic survey simultaneously with photometric survey. The spectroscopic survey will measure sli…