Strong-lensing source reconstruction with variationally optimized Gaussian processes

Strong-lensing source reconstruction with variationally optimized Gaussian processes

Strong-lensing images provide a wealth of information both about the magnified source and about the dark matter distribution in the lens. Precision analyses of these images can be used to constrain the nature of dark matter. However, this requires high-fidelity image reconstructions and careful trea...

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Bibliographic Details
Main Authors: Coogan, A. (Author), Karchev, K. (Author), Weniger, C. (Author)
Format: Article
Language:English
Published: Oxford University Press 2022
Subjects:
dark matter
Dark matter
Galaxies
Gaussian distribution
Gaussian noise (electronic)
Gradient methods
Gravitation
gravitational lensing: strong
Gravitational lensing: strong
High-fidelity images
Image analysis
Image reconstruction
Images reconstruction
methods: statistical
Methods:statistical
Optimization
Pipelines
Precision analysis
Source reconstruction
Stochastic models
Stochastic systems
techniques: image processing
Techniques: image processing
Uncertainty
Wealth of information
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