A machine learning method to infer clusters of galaxies mass radial profiles from mock Sunyaev-Zel'dovich maps with The Three Hundred clusters
Our study introduces a new machine learning algorithm for estimating 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel'dovich (SZ) effect maps. We generate mock images from 2522 simulated clusters, employing an autoencoder and random forest in our approach. Notably, our model makes no prior assumptions
Ferragamo, A. et al.
Fecha de publicación:
6
2024