57 citations · 187 across the 21 of their papers we have counts for
5 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…
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…
Physical parameter regression from black hole images via a multiscale adaptive neural network
Jialei Wei, Ao Liu, Dejiang Li +1
High-precision regression of physical parameters from black hole images generated by General Relativistic Ray Tracing (GRRT) is essential for investigating spacetime curvature and…
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…
BCDDM: Branch-Corrected Denoising Diffusion Model for Black Hole Image Generation
Ao liu, Zelin Zhang, Songbai Chen +2
The properties of black holes and accretion flows can be inferred by fitting Event Horizon Telescope (EHT) data to simulated images generated through general relativistic ray traci…