Moriakov, NikitaSamudre, AshwinNegro, MichelaGieseke, FabianOtten, SydneyHendriks, Luc2020-06-092020-06-092020-05-16Nikita Moriakov et al., Inferring astrophysical X-ray polarization with deep learning, https://arxiv.org/abs/2005.08126http://hdl.handle.net/11603/18845Eighth Internation Conference on Learning Representations (ICRL 2020)We investigate the use of deep learning in the context of X-ray polarization detection from astrophysical sources as will be observed by the Imaging X-ray Polarimetry Explorer (IXPE), a future NASA selected space-based mission expected to be operative in 2021. In particular, we propose two models that can be used to estimate the impact point as well as the polarization direction of the incoming radiation. The results obtained show that data-driven approaches depict a promising alternative to the existing analytical approaches. We also discuss problems and challenges to be addressed in the near future.5 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Text