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...

Полное описание

Библиографические подробности
Главные авторы: Mark J. Henriksen, Prajwal Panda
Формат: Статья
Язык:English
Опубликовано: IOP Publishing 2024-01-01
Серии:The Astrophysical Journal Letters
Предметы:
Online-ссылка:https://doi.org/10.3847/2041-8213/ad1ede