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...
Główni autorzy: | Mark J. Henriksen, Prajwal Panda |
---|---|
Format: | Artykuł |
Język: | English |
Wydane: |
IOP Publishing
2024-01-01
|
Seria: | The Astrophysical Journal Letters |
Hasła przedmiotowe: | |
Dostęp online: | https://doi.org/10.3847/2041-8213/ad1ede |
Podobne zapisy
-
The El Gordo Galaxy Cluster Challenges ΛCDM for Any Plausible Collision Velocity
od: Elena Asencio, i wsp.
Wydane: (2023-01-01) -
Halo Concentrations and the Fundamental Plane of Galaxy Clusters
od: Yutaka Fujita, i wsp.
Wydane: (2019-01-01) -
Subhalos in Galaxy Clusters: Coherent Accretion and Internal Orbits
od: Chi Han, i wsp.
Wydane: (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
od: Yirong Wang, i wsp.
Wydane: (2024-01-01) -
Toward Accurate Modeling of Galaxy Clustering on Small Scales: Halo Model Extensions and Lingering Tension
od: Gillian D. Beltz-Mohrmann, i wsp.
Wydane: (2023-01-01)