Non-Gaussian information from weak lensing data via deep learning

@article{Gupta2018NonGaussianIF,
  title={Non-Gaussian information from weak lensing data via deep learning},
  author={Arushi Gupta and Jos{\'e} Manuel Zorrilla Matilla and Daniel J. Hsu and Zolt{\'a}n Haiman},
  journal={ArXiv},
  year={2018},
  volume={abs/1802.01212}
}
Weak lensing maps contain information beyond two-point statistics on small scales. Much recent work has tried to extract this information through a range of different observables or via nonlinear transformations of the lensing field. Here we train and apply a two-dimensional convolutional neural network to simulated noiseless lensing maps covering 96 different cosmological models over a range of ${{\mathrm{\ensuremath{\Omega}}}_{m},{\ensuremath{\sigma}}_{8}}$. Using the area of the confidence… 

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