26 citations · 99 across the 8 of their papers we have counts for
8 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…
Inferring redshift and energy distributions of fast radio bursts from the first CHIME/FRB catalog
Li Tang, Hai-Nan Lin, Xin Li
We reconstruct the extragalactic dispersion measure \ -- redshift relation ( relation) from well-localized fast radio bursts (FRBs) using Bayesian inference method. T…
Revised constraints on the photon mass from well-localized fast radio bursts
Hai-Nan Lin, Li Tang, Rui Zou
We constrain the photon mass from well-localized fast radio bursts (FRBs) using Bayes inference method. The probability distributions of dispersion measures (DM) of host galaxy and…
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…
Search for the correlations between host properties and of fast radio bursts: constraints on the baryon mass fraction in IGM
Hai-Nan Lin, Xin Li, Li Tang
The application of fast radio bursts (FRBs) as probes to investigate astrophysics and cosmology requires the proper modelling of the dispersion measures of Milky Way (${\rm DM_{MW}…
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…
Comparing the dark matter models, modified Newtonian dynamics and modified gravity in accounting for the galaxy rotation curves
Xin Li, Li Tang, Hai-Nan Lin
We compare six models (including the baryonic model, two dark matter models, two modified Newtonian dynamics models and one modified gravity model) in accounting for the galaxy rot…