Edge crossings in random linear arrangements

10/09/2019
by   Lluís Alemany-Puig, et al.
0

In spatial networks, vertices are arranged in some space and edges may cross. Here we consider the particular case of arranging vertices in a 1-dimensional lattice, where edges may cross when drawn above the vertex sequence as it happens in linguistic and biological networks. Here we investigate the distribution of edge crossings under the null hypothesis of a uniformly random arrangement of the vertices. We generalize the existing formula for the expectation of this number in trees to any network and derive a general expression for the variance of the number of crossings relying on a novel characterization of the algebraic structure of that variance in an arbitrary space. We provide compact formulae for the expectation and the variance in complete graphs, cycle graphs, one-regular graphs and various kinds of trees (star trees, quasi-star trees and linear trees). In these networks, the scaling of expectation and variance as a function of network size is asymptotically power-law-like. Our work paves the way for further research and applications in 1-dimension or investigating the distribution of the number of crossings in lattices of higher dimension or other embeddings.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/06/2020

Fast calculation of the variance of edge crossings in random linear arrangements

The interest in spatial networks where vertices are embedded in a one-di...
research
03/06/2020

Reappraising the distribution of the number of edge crossings of graphs on a sphere

Many real transportation and mobility networks have their vertices place...
research
10/27/2020

Star edge-coloring of some special graphs

The star chromatic index of a multigraph G, denoted by χ_star'(G), is th...
research
06/24/2020

The variation of the sum of edge lengths in linear arrangements of trees

A fundamental problem in network science is the normalization of the top...
research
05/25/2023

Sidorenko-Type Inequalities for Pairs of Trees

Given two non-empty graphs H and T, write H≽ T to mean that t(H,G)^|E(T)...
research
07/13/2020

LSQT: Low-Stretch Quasi-Trees for Bundling and Layout

We introduce low-stretch trees to the visualization community with LSQT,...
research
10/09/2021

Peripherality in networks: theory and applications

We investigate several related measures of peripherality and centrality ...

Please sign up or login with your details

Forgot password? Click here to reset