Abstract

Bipartite graphs are often found to represent the connectivity between the components of many systems such as ecosystems. A bipartite graph is a set of nn nodes that is decomposed into two disjoint subsets, having mm and n−mn-m vertices each, such that there are no adjacent vertices within the same set. The connectivity between both sets, which is the relevant quantity in terms of connections, can be quantified by a parameter α∈[0,1]α\in[0,1] that equals the ratio of existent adjacent pairs over the total number of possible adjacent pairs. Here, we study the spectral and localization properties of such random bipartite graphs. Specifically, within a Random Matrix Theory (RMT) approach, we identify a scaling parameter ξ≡ξ(n,m,α)ξ\equivξ(n,m,α) that fixes the localization properties of the eigenvectors of the adjacency matrices of random bipartite graphs. We also show that, when ξ<1/10ξ<1/10 (ξ>10ξ>10) the eigenvectors are localized (extended), whereas the localization--to--delocalization transition occurs in the interval 1/10<ξ<101/10<ξ<10. Finally, given the potential applications of our findings, we round off the study by demonstrating that for fixed ξξ, the spectral properties of our graph model are also universal.

Explore this paper’s authors, topics and related work.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Reviews 0

Write a reviewWrite

No reviews yet.

Discussion 0

Add a commentWrite

No comments yet.