E2-215

12-1pm

Ryan Hausen (PhD student, CSE at UCSC)

Title: Morpheus: A Deep Learning Model for Pixel-Level Morphological Classification

Abstract: The majority of astronomy begins with images filled with stars and galaxies of various sizes in arrays that can be hundreds of millions of pixels. From these images, one may study galaxies by their shape yet classifying by morphology can be difficult and often involves an element of subjectivity. Furthermore, doing so with astronomical-scale images is both time and cost-prohibitive if one were to rely on human resources alone. The Computational Astrophysics Research Group at UCSC is leveraging current methods and innovating new techniques in Deep Learning to develop new and more efficient approaches this problem. One such way is Morpheus, a deep learning model that morphologically classifies astronomical images with pixel-level precision. Using Morpheus, astronomers can extract a detailed analysis of the morphological composition galaxies and stars of an image. This kind of information is key to understanding how galaxies form and evolve.