Poster
2024 workshop program
Estimating Galaxy Cluster Mass Accretion Rates from Observations using Machine Learning
The work
Abstract
Galaxy clusters are sensitive probes of dark matter physics, cosmology, and astrophysics. The mass accretion rates of galaxy clusters can obscure this information, but could also provide a new means of obtaining it. We present a machine learning model, trained on mock observations of galaxy clusters from the Millennium TNG simulation, that can directly estimate the mass accretion rate of galaxy clusters from observations.