Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks. (arXiv:2211.07807v1 [astro-ph.CO])

We present a Bayesian graph neural network (BGNN) that can estimate the weak
lensing convergence ($\kappa$) from photometric measurements of galaxies along
a given line of sight. The method is of particular interest in strong
gravitational time delay cosmography (TDC), where characterizing the "external
convergence" ($\kappa_{\rm ext}$) from the lens environment and line of sight
is necessary for precise inference of the Hubble constant ($H_0$). Starting
from a large-scale simulation with a $\kappa$ resolution of $\sim$1$'$, we
introduce fluctuations on …

arxiv astro bayesian convergence graph graph neural networks hierarchical inference networks neural networks