KIPAC researchers used images of strongly lensed galaxies taken with the Hubble Space Telescope to test the performance of neural networks, which promise to speed up complex astrophysical analyses tremendously.

layers. Each layer searches for certain features in the input image (at left). The last layer provides the result of the analysis. The researchers used particular kinds of neural networks, called convolutional neural networks, in which individual computational units (neurons, gray spheres) of each layer are also organized into 2-D slabs that bundle information about the original image into larger computational units.