A machine-learning approach to measuring the escape of ionizing radiation from galaxies in the …

A machine-learning approach to measuring the escape of ionizing radiation from galaxies in the reionization epoch Hannes Jensen1†, Erik Zackrisson, Kristiaan Pelckmans, Christian Binggeli, Kristiina Ausmees, Ulrika Lundholm 1Lund Observatory, Sweden †Listed affiliation is based on previous publications and was not specified in this preprint. ArXiv #: 1603.09610 (PDF, PS, ADS, Papers, Other) Comments: 12 pages, 10 figures. Submitted to ApJ Originally posted by astro-ph from Unaffiliated on 03/31/2016 GA 5 ‘s: danichao (NTHU), hcferguson (STScI/JHU Galaxies), Maxime Trebitsch (CRAL), kuanghan (UCD), mkmprescott (NMSU) Recent observations of galaxies at $z gtrsim 7$, along with the low value of the electron scattering optical depth measured by the Planck mission, make galaxies plausible as dominant sources of ionizing photons during the epoch of reionization. However, scenarios of galaxy-driven reionization hinge on the…


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