44 citations · 197 across the 18 of their papers we have counts for
6 papers · 1 filter
Identifying Microlensing by Compact Dark Matter through Diffraction Patterns in Gravitational Waves with Machine Learning
Ao Liu, Tonghua Liu, Dejiang Li +5
Gravitational wave lensing, particularly microlensing by compact dark matter (DM), offers a unique avenue to probe the nature of dark matter. However, conventional detection method…
Probing potential redshift-dependent systematics in the Hubble tension: Model-independent constraints from DESI R2
Tonghua Liu, Shuo Cao, Jieci Wang
We present a determination of the Hubble constant () using the latest observational data from multiple cosmological probes, providing an independent geometric calibration of t…
Identification of Strongly Lensed Gravitational Wave Events Using Squeeze-and-Excitation Multilayer Perceptron Data-efficient Image Transformer
Dejiang Li, Tonghua Liu, Ao Liu +4
With the advancement of third-generation gravitational wave detectors, the identification of strongly lensed gravitational wave (GW) events is expected to play an increasingly vita…
Torsion cosmology in the light of DESI, supernovae and CMB observational constraints
Tonghua Liu, Xiaolei Li, Tengpeng Xu +2
In this work, we investigate a torsion-based cosmological model within the Einstei-Cartan framework, constrained by the latest combined datasets including DESI DR2 BAO, PantheonPlu…
Dynamical Dark Energy in the Crosshairs: A Joint Analysis with DESI, Pantheon plus, and TDCOSMO Constraints
Tonghua Liu, Xiaolei Li, Jieci Wang
In this work, we perform a comprehensive joint analysis of three representative dark energy models - , the Chevallier-Polarski-Linder (CPL) parametrization, and the Gene…
Advancing Cosmological Parameter Estimation and Hubble Parameter Reconstruction with Long Short-Term Memory and Efficient-Kolmogorov-Arnold Networks
Jiaxing Cui, Marek Biesiada, Ao Liu +3
In this work, we propose a novel approach for cosmological parameter estimation and Hubble parameter reconstruction using Long Short-Term Memory (LSTM) networks and Efficient-Kolmo…