4 papers
A widely applicable Galaxy Group finder Using Machine Learning
Juntao Ma, Jie Wang, Tianxiang Mao +4
Galaxy groups are essential for studying the distribution of matter on a large scale in redshift surveys and for deciphering the link between galaxy traits and their associated hal…
Prediction of Individual Halo Concentrations Across Cosmic Time Using Neural Networks
Tianchi Zhang, Tianxiang Mao, Wenxiao Xu +1
The concentration of dark matter haloes is closely linked to their mass accretion history. We utilize the halo mass accretion histories from large cosmological N-body simulations a…
Half a Million Binary Stars from the low resolution spectra of LAMOST
Yingjie Jing, Tian-Xiang Mao, Jie Wang +2
Binary stars are prevalent yet challenging to detect. We present a novel approach using convolutional neural networks (CNNs) to identify binary stars from low-resolution spectra ob…
Estimation of line-of-sight velocities of individual galaxies using neural networks I. Modelling redshift-space distortions at large scales
Hongxiang Chen, Jie Wang, Tianxiang Mao +7
We present a scheme based on artificial neural networks (ANN) to estimate the line-of-sight velocities of individual galaxies from an observed redshift-space galaxy distribution. W…