Strong-lensing source reconstruction with variationally optimised Gaussian processes

Understand

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 treatment of the uncertainties of both lens mass distribution and source light, which are typically difficult to quantify.
• In anticipation of future high-resolution datasets, in this work we leverage a range of recent developments in machine learning to develop a new Bayesian strong-lensing image analysis pipeline.