Inferring astrophysical X-ray polarization with deep learning

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dc.contributor.authorMoriakov, Nikita
dc.contributor.authorSamudre, Ashwin
dc.contributor.authorNegro, Michela
dc.contributor.authorGieseke, Fabian
dc.contributor.authorOtten, Sydney
dc.contributor.authorHendriks, Luc
dc.date.accessioned2020-06-09T15:49:57Z
dc.date.available2020-06-09T15:49:57Z
dc.date.issued2020-05-16
dc.descriptionEighth Internation Conference on Learning Representations (ICRL 2020)en
dc.description.abstractWe 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.en
dc.description.sponsorshipWe want to thank the DarkMachines collaboration for bringing us together and for fruitful discussions. Michela Negro wants to acknowledge the IXPE team and in particular Niccoló Di Lalla and Alberto Manfreda for providing the simulated data samples.en
dc.description.urihttps://arxiv.org/abs/2005.08126en
dc.format.extent5 pagesen
dc.genreconference papers and proceedings preprintsen
dc.identifierdoi:10.13016/m2sfov-uo4v
dc.identifier.citationNikita Moriakov et al., Inferring astrophysical X-ray polarization with deep learning, https://arxiv.org/abs/2005.08126en
dc.identifier.urihttp://hdl.handle.net/11603/18845
dc.language.isoenen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Center for Space Sciences and Technology
dc.relation.ispartofUMBC Physics Department
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis 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.
dc.titleInferring astrophysical X-ray polarization with deep learningen
dc.typeTexten

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