High-Resolution CMB Lensing Reconstruction with Deep Learning

Understand

Next-generation cosmic microwave background (CMB) surveys are expected to provide valuable information about the primordial universe by creating maps of the mass along the line of sight.

• Traditional tools for creating these lensing convergence maps include the quadratic estimator and the maximum likelihood based iterative estimator.
• Here, we apply a generative adversarial network (GAN) to reconstruct the lensing convergence field.
• We compare our results with a previous deep learning approach -- Residual-UNet -- and discuss the pros and cons of each.