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...
Autors principals: | , |
---|---|
Format: | Article |
Idioma: | English |
Publicat: |
IOP Publishing
2024-01-01
|
Col·lecció: | The Astrophysical Journal Letters |
Matèries: | |
Accés en línia: | https://doi.org/10.3847/2041-8213/ad1ede |