Exploiting Machine Learning and Disequilibrium in Galaxy Clusters to Obtain a Mass Profile
We use 3D k -means clustering to characterize galaxy substructure in the A2146 cluster of galaxies ( z = 0.2343). This method objectively characterizes the cluster’s substructure using projected position and velocity data for 67 galaxies within a 2.305 Mpc circular region centered on the cluster...
主要な著者: | Mark J. Henriksen, Prajwal Panda |
---|---|
フォーマット: | 論文 |
言語: | English |
出版事項: |
IOP Publishing
2024-01-01
|
シリーズ: | The Astrophysical Journal Letters |
主題: | |
オンライン・アクセス: | https://doi.org/10.3847/2041-8213/ad1ede |
類似資料
-
The El Gordo Galaxy Cluster Challenges ΛCDM for Any Plausible Collision Velocity
著者:: Elena Asencio, 等
出版事項: (2023-01-01) -
Correlations in Relaxed Clusters of Galaxies
著者:: Babyk Iu., 等
出版事項: (2014-03-01) -
Halo Concentrations and the Fundamental Plane of Galaxy Clusters
著者:: Yutaka Fujita, 等
出版事項: (2019-01-01) -
Subhalos in Galaxy Clusters: Coherent Accretion and Internal Orbits
著者:: Chi Han, 等
出版事項: (2024-01-01) -
Measuring the Conditional Luminosity and Stellar Mass Functions of Galaxies by Combining the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 Data
著者:: Yirong Wang, 等
出版事項: (2024-01-01)