Variability in higher order structure of noise added to weighted networks

Abstract

A common problem in reconstructing weighted networks to represent real-world systems is that low-weight edges might appear due to noise, affecting the topology of the inferred network. Here, the authors propose a method based on persistent homology that allows one to investigate the higher-order network organization that can be created by low-weight, noisy edges.