Han Aung, Zuckerman Postdoc Scholar, publishes paper in Astronomy and Computing
The Hebrew University of Jerusalem
We present Classification of Cluster Galaxy Members (C 2-GaMe), a classification algorithm based on a suite of machine learning models that differentiates galaxies into orbiting, infalling, and background (interloper) populations, using phase space information as input. We train and test C 2-GaMe with the galaxies from Universe Machine mock catalogue based on Multi-Dark Planck 2 N-body simulations. We show that probabilistic classification is superior to deterministic classification in estimating the physical properties of clusters, including density profiles and velocity dispersion.