422 citations · 4.5k across the 83 of their papers we have counts for
85 papers
DeepVoid: A Deep Learning Void Detector
Sam Kumagai, Michael S. Vogeley, Miguel A. Aragon-Calvo +3
We present DeepVoid, an application of deep learning trained on a physical definition of cosmic voids to detect voids in density fields and galaxy distributions. By semantically se…
Cosmology with Cosmic Voids
Yan-Chuan Cai, Mark Neyrinck
Cosmic voids are low-mass-density regions on intergalactic scales. They are where cosmic expansion and acceleration are most dominant, important places to understand and analyze fo…
Galaxy and Halo Root Systems: Fingerprints of Mass Assembly
Mark Neyrinck, Miguel Aragón-Calvo, István Szapudi
We discuss what we call halo or galaxy root systems, collections of particle pathlines that show the infall of matter from the initial uniform distribution into a collapsed structu…
The three phases of self-gravitating scalar field ground states
Anthony E. Mirasola, Nathan Musoke, Mark C. Neyrinck +2
It is generally assumed that scalar field dark matter halos would contain solitonic cores -- spherically symmetric ground state configurations -- at their centers. This is especial…
Baryon Acoustic Oscillations analyses with Density-Split Statistics
Tengpeng Xu, Yan-Chuan Cai, Yun Chen +3
Accurate modeling for the evolution of the Baryon Acoustic Oscillations (BAO) is essential for using it as a standard ruler to probe cosmology. We explore the non-linearity of the…
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…