Differentiable strong lensing: uniting gravity and neural nets through differentiable probabilistic programming

  title={Differentiable strong lensing: uniting gravity and neural nets through differentiable probabilistic programming},
  author={Marco Chianese and Adam Coogan and Paul Hofma and Sydney Otten and Christoph Weniger},
  journal={Monthly Notices of the Royal Astronomical Society},
Since upcoming telescopes will observe thousands of strong lensing systems, creating fully automated analysis pipelines for these images becomes increasingly important. In this work, we make a step towards that direction by developing the first end-to-end differentiable strong lensing pipeline. Our approach leverages and combines three important computer science developments: (i) convolutional neural networks (CNNs), (ii) efficient gradient-based sampling techniques, and (iii) deep… 

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    Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019)
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