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20242026
most citedDynamical Dark Energy in the Crosshairs: A Joint Analysis with DESI, Pantheon plus, and TDCOSMO Constraints

26 citations · 78 across the 13 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

astro-ph.IM2025

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…

astro-ph.IM2025★ 3 cited

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…

astro-ph.CO2025★ 10 cited

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…

astro-ph.CO2025★ 26 cited

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…

astro-ph.CO2025★ 3 cited

Revisiting the Hubble constant, sound horizon and cosmography from late-time Universe observations

Zhiwei Yang, Tonghua Liu, Xiaolei Li

The Hubble tension has become one of the central problems in cosmology. In this work, we determine the Hubble constant and sound horizon by using the combination of Bar…

astro-ph.CO2025

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…