Fast Automated Analysis of Strong Gravitational Lenses with Convolutional Neural Networks

Understand

Quantifying image distortions caused by strong gravitational lensing and estimating the corresponding matter distribution in lensing galaxies has been primarily performed by maximum likelihood modeling of observations.

• This is typically a time and resource-consuming procedure, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers.
• Accurate analysis of a single lens can take up to a few weeks and requires the attention of dedicated experts.
• Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys, the analysis of which can be a challenging task.