4 papers
LSTM-MDNz: Estimating Quasar Photometric Redshifts with an LSTM-Augmented Mixture Density Network
Jianzhen Chen, Zhijian Luo, Liping Fu +4
Quasar photometric redshifts are essential for studying cosmology and large-scale structures. However, their complex spectral energy distributions cause significant redshift-color…
Galaxy Morphology Classification via Deep Semi-Supervised Learning with Limited Labeled Data
Zhijian Luo, Jianzhen Chen, Zhu Chen +4
Galaxy morphology classification plays a crucial role in understanding the structure and evolution of the universe. With galaxy observation data growing exponentially, machine lear…
Meta-Calibration of the Cosmic Magnification Coefficient: Toward Unbiased Weak Lensing Reconstruction by Counting Galaxies
Jian Qin, Pengjie Zhang, Zhu Chen +6
Weak lensing alters galaxy sizes and fluxes, influencing the clustering patterns of galaxies through cosmic magnification. This effect enables the reconstruction of weak lensing co…
Improving Photometric Redshift Estimation for CSST Mock Catalog Using SED Templates Calibrated with Perturbation Algorithm
Yicheng Li, Liping Fu, Zhu Chen +11
Photometric redshifts of galaxies obtained by multi-wavelength data are widely used in photometric surveys because of its high efficiency. Although various methods have been develo…