Decoding Cosmological Information in Weak-Lensing Mass Maps with Generative Adversarial Networks

28 Nov 2019Masato ShirasakiNaoki YoshidaShiro IkedaTaira OogiTakahiro Nishimichi

Galaxy imaging surveys enable us to map the cosmic matter density field through weak gravitational lensing analysis. The density reconstruction is compromised by a variety of noise originating from observational conditions, galaxy number density fluctuations, and intrinsic galaxy properties... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet