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...
| Autores principales: | , |
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| Formato: | Artículo |
| Lenguaje: | English |
| Publicado: |
IOP Publishing
2024-01-01
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| Colección: | The Astrophysical Journal Letters |
| Materias: | |
| Acceso en línea: | https://doi.org/10.3847/2041-8213/ad1ede |