Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems Using Recurrent Inference Machines

Modeling strong gravitational lenses in order to quantify distortions in the images of background sources and to reconstruct the mass density in foreground lenses has been a difficult computational challenge. As the quality of gravitational lens images increases, the task of fully exploiting the inf...

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Autors principals:	Alexandre Adam, Laurence Perreault-Levasseur, Yashar Hezaveh, Max Welling
Format:	Artigo
Idioma:	Inglês
Publicat:	IOP Publishing 2023-01-01
Col·lecció:	The Astrophysical Journal
Matèries:	Convolutional neural networks Astronomical simulations Nonparametric inference
Accés en línia:	https://doi.org/10.3847/1538-4357/accf84
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