Merging galaxies and Deep Learning

 

Galaxy mergers are very important for the evolution of galaxies, and the overall appearance of our universe today. Together with Dr. Brian Nord and the Deep Skies Lab, I am working on a deep learning algorithm e.g. convolutional neural network (CNN), that will be able to distinguish between merging and non-merging galaxies. CNNs represent a deep learning technique, vastly used in image or video recognition, computer vision, or even recommendation systems, and natural language processing.

The CNN can be trained on simulated data, and through transfer learning this algorithm can later be applied to observational data. This will be very important for searching through large surveys, like DES or LSST. Finding many interacting galaxies in different merger stages, will be crucial for understanding these interacting objects, their physics and the role of mergers in galaxy evolution.

Read more in:

DeepMerge: Classifying High-redshift Merging Galaxies with Deep Neural Networks
 

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