Galaxy cluster mass estimation with deep learning and hydrodynamical simulations

24 May 2020 Z. Yan A. J. Mead L. Van Waerbeke G. Hinshaw I. G. McCarthy

We evaluate the ability of Convolutional Neural Networks (CNNs) to predict galaxy cluster masses in the BAHAMAS hydrodynamical simulations. We train four separate single-channel networks using: stellar mass, soft X-ray flux, bolometric X-ray flux, and the Compton $y$ parameter as observational tracers, respectively... (read more)

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  • COSMOLOGY AND NONGALACTIC ASTROPHYSICS