Horton Law in Self-Similar Trees

Abstract

Self-similarity of random trees is related to the operation of pruning. Pruning $R$ cuts the leaves and their parental edges and removes the resulting chains of degree-two nodes from a finite tree. A Horton-Strahler order of a vertex $v$ and its parental edge is defined as the minimal number of prunings necessary to eliminate the subtree rooted at $v$. A branch is a group of neighboring vertices and edges of the same order. The Horton numbers $N_k[K]$ and $N_{ij}[K]$ are defined as the expected number of branches of order $k$, and the expected number of order-$i$ branches that merged order-$j$ branches, $j>i$, respectively, in a finite tree of order $K$. The Tokunaga coefficients are defined as $T_{ij}[K]=N_{ij}[K]/N_j[K]$. The pruning decreases the orders of tree vertices by unity. A rooted full binary tree is said to be mean-self-similar if its Tokunaga coefficients are invariant with respect to pruning: $T_k:=T_{i,i+k}[K]$. We show that for self-similar trees, the condition $\mathrm{limsup}(T_k{)}^{1/k}<\infty$ is necessary and sufficient for the existence of the strong Horton law: $N_k[K]/N_1[K]\to R^{1-k}$, as $K\to \infty$ for some $R>0$ and every $k\ge 1$. This work is a step toward providing rigorous foundations for the Horton law that, being omnipresent in natural branching systems, has escaped so far a formal explanation.

Cited by in corpus (2)

• Critical Tokunaga model for river networks
• Tokunaga self-similarity arises naturally from time invariance