English

A non-increasing tree growth process for recursive trees and applications

Probability 2021-11-11 v2 Combinatorics

Abstract

We introduce a non-increasing tree growth process ((Tn,σn),n1)((T_n,\sigma_n),\, n\ge 1), where TnT_n is a rooted labeled tree on nn vertices and σn{\sigma}_n is a permutation of the vertex labels. The construction of (Tn,σn)(T_{n},{\sigma}_n) from (Tn1,σn1)(T_{n-1},{\sigma}_{n-1}) involves rewiring a random (possibly empty) subset of edges in Tn1T_{n-1} towards the newly added vertex; as a consequence Tn1⊄TnT_{n-1} \not\subset T_n with positive probability. The key feature of the process is that the shape of TnT_n has the same law as that of a random recursive tree, while the degree distribution of any given vertex is not monotonous in the process. We present two applications. First, while couplings between Kingman's coalescent and random recursive trees where known for any fixed nn, this new process provides a non-standard coupling of all finite Kingman's coalescents. Second, we use the new process and the Chen-Stein method to extend the well-understood properties of degree distribution of random recursive trees to extremal-range cases. Namely, we obtain convergence rates on the number of vertices with degree at least clnnc\ln n, c(1,2)c\in (1,2), in trees with nn vertices. Further avenues of research are discussed.

Keywords

Cite

@article{arxiv.1701.01656,
  title  = {A non-increasing tree growth process for recursive trees and applications},
  author = {Laura Eslava},
  journal= {arXiv preprint arXiv:1701.01656},
  year   = {2021}
}

Comments

27 pages, 3 figures

R2 v1 2026-06-22T17:42:58.899Z