25 citations · 61 across the 5 of their papers we have counts for
5 papers
Consistency of Pantheon+ supernovae with a large-scale isotropic universe
Li Tang, Hai-Nan Lin, Liang Liu +1
We investigate the possible anisotropy of the universe using the most up-to-date type Ia supernovae, i.e. the Pantheon+ compilation. We fit the full Pantheon+ data with the dipole-…
Constraining the spatial curvature of the local Universe with deep learning
Liang Liu, Li-Juan Hu, Li Tang +1
We use the distance sum rule (DSR) method to constrain the spatial curvature of the Universe with a large sample of 161 strong gravitational lensing (SGL) systems, whose distances…
Deep learning method in testing the cosmic distance duality relation
Li Tang, Hai-Nan Lin, Liang Liu
The cosmic distance duality relation (DDR) is constrained from the combination of type-Ia supernovae (SNe Ia) and strong gravitational lensing (SGL) systems using deep learning met…
Reconstructing the Hubble diagram of gamma-ray bursts using deep learning
Li Tang, Hai-Nan Lin, Xin Li +1
We calibrate the distance and reconstruct the Hubble diagram of gamma-ray bursts (GRBs) using deep learning. We construct an artificial neural network, which combines the recurrent…
Model-independently calibrating the luminosity correlations of gamma-ray bursts using deep learning
Li Tang, Xin Li, Hai-Nan Lin +1
Gamma-ray bursts (GRBs) detected at high redshift can be used to trace the Hubble diagram of the Universe. However, the distance calibration of GRBs is not as easily as that of typ…