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...
Main Authors: | Alexandre Adam, Laurence Perreault-Levasseur, Yashar Hezaveh, Max Welling |
---|---|
Format: | Article |
Language: | English |
Published: |
IOP Publishing
2023-01-01
|
Series: | The Astrophysical Journal |
Subjects: | |
Online Access: | https://doi.org/10.3847/1538-4357/accf84 |
Similar Items
-
A Framework for Obtaining Accurate Posteriors of Strong Gravitational Lensing Parameters with Flexible Priors and Implicit Likelihoods Using Density Estimation
by: Ronan Legin, et al.
Published: (2023-01-01) -
MPBoot: fast phylogenetic maximum parsimony tree inference and bootstrap approximation
by: Diep Thi Hoang, et al.
Published: (2018-02-01) -
Nonparametric Representation of Neutron Star Equation of State Using Variational Autoencoder
by: Ming-Zhe Han, et al.
Published: (2023-01-01) -
nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference
by: Sebastian Calonico, et al.
Published: (2019-10-01) -
Twelve-Year Analysis of NO<sub>2</sub> Concentration Measurements at Belisario Station (Quito, Ecuador) Using Statistical Inference Techniques
by: Wilmar Hernandez, et al.
Published: (2020-10-01)