9 citations · 24 across the 18 of their papers we have counts for
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astro-ph.CO2024
AI-Powered Reconstruction of Dark Matter Velocity Fields from Redshift-Space Halo Distribution
Xu Xiao, Jiacheng Ding, XiaoLin Luo +6
We propose a UNet-based deep learning model to reconstruct the real-space dark matter (DM) velocity field from the redshift-space distribution of sparse DM halos. Using various sta…
astro-ph.CO2024★ 5 cited
Deep learning for cosmological parameter inference from a dark matter halo density field
Zhiwei Min, Xu Xiao, Jiacheng Ding +11
We propose a lightweight deep convolutional neural network (lCNN) to estimate cosmological parameters from simulated three-dimensional dark matter (DM) halo distributions and assoc…
astro-ph.CO2024★ 4 cited
Improving SDSS cosmological constraints through -skeleton weighted correlation functions
Fenfen Yin, Jiacheng Ding, Limin Lai +6
The -skeleton approach can be conveniently utilized to construct the cosmic web based on the spatial geometry distribution of galaxies, particularly in sparse samples. This meth…