25 citations · 95 across the 20 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: Galaxies in the Faint Universe
Woowon Byun, Yongmin Yoon, Jongwan Ko +17
Low-surface-brightness (LSB) structures serve as evidence of the intricate mass assembly of galaxies, and dedicatedly studying them promises to give us profound insights into the e…
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…