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High-Resolution CMB Lensing Reconstruction with Deep Learning

2022-05-15 19:58:39
Peikai Li, Ipek Ilayda Onur, Scott Dodelson, Shreyas Chaudhari
arXiv_CV
           
Abstract

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. In the process, we use training sets generated by a variety of power spectra, rather than the one used in testing the methods.

Abstract (translated)

URL

https://arxiv.org/abs/2205.07368

PDF

https://arxiv.org/pdf/2205.07368.pdf

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