English

Leaves of preferential attachment trees

Statistical Mechanics 2026-02-03 v1 Social and Information Networks Physics and Society

Abstract

We provide a local probabilistic description of the limiting statistics of large preferential attachment trees in terms of the ordinary degree (number of neighbors) but augmented with information on leafdegree (number of neighbors that are leaves). The full description is the joint degree-leafdegree distribution nk,n_{k,\ell}, which we derive from its associated multivariate generating function. From nk,n_{k,\ell} we obtain the leafdegree distribution, mm_{\ell}, as well as the fraction of vertices that are protected (nonleaves with leafdegree zero) as a function of degree, nk,0n_{k,0}, among numerous other results. We also examine fluctuations and concentration of joint degree-leafdegree empirical counts Nk,N_{k,\ell}. Although our main findings pertain to the preferential attachment tree, the approach we present is highly generalizable and can characterize numerous existing models, in addition to facilitating the development of tractable new models. We further demonstrate the approach by analyzing nk,n_{k,\ell} in two other models: the random recursive tree, and a redirection-based model.

Keywords

Cite

@article{arxiv.2602.01021,
  title  = {Leaves of preferential attachment trees},
  author = {Harrison Hartle and P. L. Krapivsky},
  journal= {arXiv preprint arXiv:2602.01021},
  year   = {2026}
}

Comments

23 pages, 5 figures

R2 v1 2026-07-01T09:29:52.875Z