Edge crossings in random linear arrangements
arXiv:1910.03926 · doi:10.1088/1742-5468/ab6845
Abstract
In spatial networks vertices are arranged in some space and edges may cross. When arranging vertices in a 1-dimensional lattice edges may cross when drawn above the vertex sequence as it happens in linguistic and biological networks. Here we investigate the general of problem of the distribution of edge crossings in random arrangements of the vertices. We generalize the existing formula for the expectation of this number in random linear arrangements of trees to any network and derive an expression for the variance of the number of crossings in an arbitrary layout 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, complete bipartite 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 in random linear arrangements. 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.
arXiv commentGeneralised our theory from one-dimensional layouts to practically any type of layout. This helps study the variance of the number of crossings in graphs when their vertices are arranged on the surface of a sphere, or on the plane. Moreover, we also give closed formulae for this variance on particular types of graphs in both linear arrangements and general layouts
References in corpus (13)
- Statistical physics of social dynamics
- Spatial Networks
- Biological network comparison using graphlet degree distribution
- Are crossing dependencies really scarce?
- The scarcity of crossing dependencies: a direct outcome of a specific constraint?
- Random -noncrossing RNA Structures
- A stronger null hypothesis for crossing dependencies
- Non-crossing dependencies: least effort, not grammar
- Hubiness, length, crossings and their relationships in dependency trees
- Crossings as a side effect of dependency lengths
- The scaling of the minimum sum of edge lengths in uniformly random trees
- The sum of edge lengths in random linear arrangements
- Random crossings in dependency trees