1 citations · 1 across the 3 of their papers we have counts for
7 papers
Revealing Hidden Cosmic Flows through the Zone of Avoidance with Deep Learning
Alexandra Dupuy, Donghui Jeong, Sungwook E. Hong +3
We present a refined deep-learning-based method to reconstruct the three-dimensional dark matter density, gravitational potential, and peculiar velocity fields in the Zone of Avoid…
How Dust Models Shape High-z Galaxy Morphology: Insights from the NewCluster Simulation
Gyeong-Hwan Byun, J. K. Jang, Zachary P. Scofield +10
Dust plays a pivotal role in shaping the observed morphology of galaxies. While traditional cosmological simulations often assume a fixed dust-to-gas (DTG) or dust-to-metal (DTM) m…
Introducing NewCluster: the first half of the history of a high-resolution cluster simulation
San Han, Sukyoung K. Yi, Yohan Dubois +8
We introduce NewCluster, a new high-resolution cluster simulation designed to serve as the massive halo counterpart of the modern cosmological galaxy evolution framework. The zoom-…
Redshift Evolution of the Intrinsic Alignments of Early-Type Galaxies and Subhalos in the Horizon Run 5 Simulation
Sanghyeon Han, Motonari Tonegawa, Ho Seong Hwang +8
We investigate the redshift evolution of intrinsic alignments of the shapes of galaxies and subhalos with the large-scale structures of the universe using the cosmological hydrodyn…
RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES
San Han, Yohan Dubois, Jaehyun Lee +3
Developing an efficient code for large, multiscale astrophysical simulations is crucial in preparing the upcoming era of exascale computing. RAMSES is an astrophysical simulation c…
Emergence of the Galaxy Morphology-Star Formation Activity-Clustercentric Radius Relations in Galaxy Clusters
Sungwook E. Hong, Changbom Park, Preetish K. Mishra +7
We investigate when and how the relations of galaxy morphology and star forming activity with clustercentric radius become evident in galaxy clusters. We identify 162 galaxy cluste…