A Geometric Chung Lu model and the Drosophila Medulla connectome
Combinatorics
2025-03-04 v1 Social and Information Networks
Neurons and Cognition
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 paper, 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.
Cite
@article{arxiv.2109.00061,
title = {A Geometric Chung Lu model and the Drosophila Medulla connectome},
author = {Susama Agarwala and Franklin Kenter},
journal= {arXiv preprint arXiv:2109.00061},
year = {2025}
}
Comments
28 pages, 13 figures