http://arxiv.org/abs/1801.06381
Next-generation 21cm observations will enable imaging of reionization on very large scales. These images will contain more astrophysical and cosmological information than the power spectrum, and hence providing an alternative way to constrain the contribution of different reionizing sources populations to cosmic reionization. Using Convolutional Neural Networks, we present a simple network architecture that is sufficient to discriminate between Galaxy-dominated versus AGN-dominated models, even in the presence of simulated noise from different experiments such as the HERA and SKA.
S. Hassan, A. Liu, S. Kohn, et. al.
Mon, 22 Jan 2018
40/52
Comments: Contributed talk for the IAU Symposium 333 “Peering towards Cosmic Dawn”, Dubrovnik, October 2-6, 2017; to appear in the proceedings, eds. Vibor Jelic and Thijs van der Hulst [5 pages, 3 figures]