Zobrazeno 1 - 10
of 680
pro vyhledávání: '"Cristiano, G."'
Autor:
Paudel, Sanjaya, Sabiu, Cristiano G., Yoon, Suk-Jin, Duc, Pierre-Alain, Yoo, Jaewon, Müller, Oliver
We report the discovery of a rare isolated group of five dwarf galaxies located at z = 0.0086 ($D$ = 36 Mpc). All member galaxies are star-forming, blue, and gas-rich with $g-r$ indices ranging from 0.2 to 0.6 mag, and two of them show signs of ongoi
Externí odkaz:
http://arxiv.org/abs/2411.10045
We present a new simulated galaxy cluster catalog based on the IllustrisTNG simulation. We use the Mulguisin (MGS) algorithm to identify galaxy overdensities. Our cluster identification differs from the previous FoF cluster identification in two aspe
Externí odkaz:
http://arxiv.org/abs/2405.17738
Autor:
Yoo, Jaewon, Park, Changbom, Sabiu, Cristiano G., Singh, Ankit, Ko, Jongwan, Lee, Jaehyun, Pichon, Christophe, Jee, M. James, Gibson, Brad K., Snaith, Owain, Kim, Juhan, Shin, Jihye, Kim, Yonghwi, Kim, Hyowon
One intriguing approach for studying the dynamical evolution of galaxy clusters is to compare the spatial distributions among various components, such as dark matter, member galaxies, gas, and intracluster light (ICL). Utilizing the recently introduc
Externí odkaz:
http://arxiv.org/abs/2402.17958
We present a novel approach for estimating cosmological parameters, $\Omega_m$, $\sigma_8$, $w_0$, and one derived parameter, $S_8$, from 3D lightcone data of dark matter halos in redshift space covering a sky area of $40^\circ \times 40^\circ$ and r
Externí odkaz:
http://arxiv.org/abs/2304.08192
Publikováno v:
JCAP06(2023)062
The distribution of matter that is measured through galaxy redshift and peculiar velocity surveys can be harnessed to learn about the physics of dark matter, dark energy, and the nature of gravity. To improve our understanding of the matter of the Un
Externí odkaz:
http://arxiv.org/abs/2302.02087
We introduce a new clustering algorithm, MulGuisin (MGS), that can identify distinct galaxy over-densities using topological information from the galaxy distribution. This algorithm was first introduced in an LHC experiment as a Jet Finder software,
Externí odkaz:
http://arxiv.org/abs/2301.03278
Autor:
Yoo, Jaewon, Ko, Jongwan, Sabiu, Cristiano G., Shin, Jihye, Chun, Kyungwon, Hwang, Ho Seong, Kim, Juhan, Jee, M. James, Kim, Hyowon, Smith, Rory
In a galaxy cluster, the relative spatial distributions of dark matter, member galaxies, gas, and intracluster light (ICL) may connote their mutual interactions over the cluster evolution. However, it is a challenging problem to provide a quantitativ
Externí odkaz:
http://arxiv.org/abs/2205.08161
Autor:
Xiao, Xiaoyuan, Yang, Yizhao, Luo, Xiaolin, Ding, Jiacheng, Huang, Zhiqi, Wang, Xin, Zheng, Yi, Sabiu, Cristiano G., Forero-Romero, Jaime, Miao, Haitao, Li, Xiao-Dong
The mark weighted correlation function (MCF) $W(s,\mu)$ is a computationally efficient statistical measure which can probe clustering information beyond that of the conventional 2-point statistics. In this work, we extend the traditional mark weighte
Externí odkaz:
http://arxiv.org/abs/2203.15986
We present forecasts on the detectability of Ultra-light axion-like particles (ULAP) from future 21cm radio observations around the epoch of reionization (EoR). We show that the axion as the dominant dark matter component has a significant impact on
Externí odkaz:
http://arxiv.org/abs/2108.07972
Autor:
Wu, Ziyong, Zhang, Zhenyu, Pan, Shuyang, Miao, Haitao, Wang, Xin, Sabiu, Cristiano G., Forero-Romero, Jaime, Wang, Yang, Li, Xiao-Dong
Publikováno v:
ApJ, 913, 2 (2021)
We develop a deep learning technique to infer the non-linear velocity field from the dark matter density field. The deep learning architecture we use is an "U-net" style convolutional neural network, which consists of 15 convolution layers and 2 deco
Externí odkaz:
http://arxiv.org/abs/2105.09450