A geometric Chung–Lu model and the Drosophila medulla connectome

Abstract

Abstract Many real-world graphs have edges correlated to the distance between them, but in an inhomogeneous manner. While the Chung–Lu model and the geometric random graph models both are elegant in their simplicity, they are insufficient to capture the complexity of these networks. In this article, we develop a generalized geometric random graph model that preserves many graph theoretic aspects of these real-world networks. We test the validity of this model on a graphical representation of the Drosophila medulla connectome.