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...

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Détails bibliographiques
Auteurs principaux: Mark J. Henriksen, Prajwal Panda
Format: Article
Langue:English
Publié: IOP Publishing 2024-01-01
Collection:The Astrophysical Journal Letters
Sujets:
Accès en ligne:https://doi.org/10.3847/2041-8213/ad1ede

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