Project 4: Imaging Galaxy Distortions with Uncertainty

Lead PIs: Emma Alexander (NU), Tjitske Starkenburg (NU)
Co-PIs: Chihway Chang (UC), Alex Drlica-Wagner (UC), Joshua Frieman (UC), Aggelos Katsaggelos (NU), Rebecca Willett (UC), Michael Zevin (Adler)
Collaborators: Aadya Agrawal (UIUC), Bilguun Batbayar (UC), Vasilis Charisopoulos (UC), Aleksandra Ćiprijanović (Fermilab), Jimena Gonzalez (UW–Madison), Tianao Li (NU), Travis Rector (U Alaska Anchorage)
Project Summary: This project has the following objectives: (1) remove distortions from astrophysical images by modeling the image formation process, (2) initially focus on simpler distortion models (convolution, noising), and (3) subsequently, develop a system to handle gravitational lensing. These objectives will be met using (1) a differentiable image synthesis pipeline comprising three components: (a) implicit image representations (e.g., SIREN) to act as per-image prior, (b) conditional generative model (normalizing flows or diffusion) to capture data distribution, and (c) differentiable nonlinear forward model to capture physics-based distortions (e.g., lensing); and (2) uncertainty quantification.

The SkAI Institute is one of the National Artificial Intelligence Research Institutes funded by the U.S. National Science Foundation and Simons Foundation.
Information on National AI Institutes is available at aiinstitutes.org.