7 papers
Cosmological Constraints from Bias-Robust Wavelet Scattering Statistics for Stage-IV Galaxy Surveys
Zhujun Jiang, Xu Xiao, Zhiwei Min +5
A central challenge in precision cosmology with galaxy surveys is to extract non-Gaussian information from large-scale structure while controlling systematic uncertainties such as…
Tomographic Alcock-Paczynski Test with Marked Correlation Functions
Liang Xiao, Limin Lai, Zhujun Jiang +2
The tomographic Alcock-Paczynski(AP) method, developed over the past decade, exploits redshift evolution for cosmological determination, aiming to mitigate contamination from redsh…
Extracting Cosmological Information from Lightcone Data: A Comparison of CNNs and Summary-Statistic-Based Approaches
Min Zhiwei, Xiao Xu, Jiang Zhujun +9
Lightcone observations are the natural data format of galaxy surveys, but their evolving geometry breaks the translational symmetry assumed by standard convolutional neural network…
Enhancing cosmological constraints with nonlinear tanh transformations of Hermite-Gaussian Derivative fields
Zhiwei Min, Ye Ma, Zhujun Jiang +4
A key goal in large-scale structure analysis is to extract multi-scale information to improve cosmological parameter constraints. In particular, higher-order derivative fields are…
A New Wavelet Scattering Transform-Based Statistic for Cosmological Analysis of Large-Scale Structure
Zhujun Jiang, Xiaolin Luo, Wenying Du +6
Large-scale structure (LSS) analysis in galaxy surveys is a powerful cosmological probe but is limited by tracer bias, which can obscure underlying information and weaken parameter…
AI-Driven Reconstruction of Large-Scale Structure from Combined Photometric and Spectroscopic Surveys
Wenying Du, Xiaolin Luo, Zhujun Jiang +7
Galaxy surveys are crucial for studying large-scale structure (LSS) and cosmology, yet they face limitations--imaging surveys provide extensive sky coverage but suffer from photo-$…