# Inferring astrophysical X-ray polarization with deep learning

arXiv: https://arxiv.org/abs/2005.08126 · HTML: https://mlsanity.com/paper/2005.08126/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 May 2020.

## Built on by (most cited first, 2 of 2)

- [HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks](https://mlsanity.com/paper/2101.10897/) (2021)
- [A deep ensemble approach to X-ray polarimetry](https://mlsanity.com/paper/2111.03047/) (2021)

## Abstract (arXiv)

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.