Deep Forest: Neural Network reconstruction of intergalactic medium temperature
Runxuan Wang,
Rupert A. C. Croft,
Patrick Shaw
Abstract:We explore the use of Deep Learning to infer the temperature of the intergalactic medium from the transmitted flux in the high redshift Ly๐ผ forest. We train Neural Networks on sets of simulated spectra from redshift ๐ง = 2 โ 3 outputs of cosmological hydrodynamic simulations, including high temperature regions added in post-processing to approximate bubbles heated by Helium-II reionization. We evaluate how well the trained networks are able to reconstruct the temperature from the effect of Doppler broadening … Show more
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