4 citations · 10 across the 14 of their papers we have counts for
4 papers · 1 filter
New classification method for the dynamical state of galaxy clusters with a Gaussian mixture model
Hyowon Kim, Marco Canducci, Rory Smith +5
Galaxy clusters are the largest gravitationally bound systems, and they continue their growth through mergers in a hierarchical ΛCDM Universe. Therefore, we can describe the merger…
K-DRIFT Science Theme: New Theoretical Framework Using the Galaxy Replacement Technique for LSB studies
Kyungwon Chun, Jihye Shin, Rory Smith +13
Low-surface-brightness (LSB) structures provide critical insights into the hierarchical formation of galaxies and galaxy clusters. The KASI Deep Rolling Imaging Fast Telescope (K-D…
Convolutional Neural Networks for classifying galaxy mergers: Can faint tidal features aid in classifying mergers?
Yeonkyung Lee, Hyunmi Song, Jihye Shin +3
Identifying mergers from observational data has been a crucial aspect of studying galaxy evolution and formation. Tidal features, typically fainter than 26 …
K-DRIFT Science Theme: Galactic Cirrus Clouds and Circumgalactic Medium
Kwang-il Seon, Jaehyun Lee, Jongwan Ko +8
In this paper, we review the extended halo material and the circumgalactic medium (CGM), including both dust and gas, and discuss promising science cases that could be realized usi…