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Main Authors: Hartle, Harrison, Krapivsky, P. L.
Formato: Preprint
Publicado: 2026
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Acceso en liña:https://arxiv.org/abs/2602.01021
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author Hartle, Harrison
Krapivsky, P. L.
author_facet Hartle, Harrison
Krapivsky, P. L.
contents 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 $n_{k,\ell}$, which we derive from its associated multivariate generating function. From $n_{k,\ell}$ we obtain the leafdegree distribution, $m_{\ell}$, as well as the fraction of vertices that are protected (nonleaves with leafdegree zero) as a function of degree, $n_{k,0}$, among numerous other results. We also examine fluctuations and concentration of joint degree-leafdegree empirical counts $N_{k,\ell}$. 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 $n_{k,\ell}$ in two other models: the random recursive tree, and a redirection-based model.
format Preprint
id arxiv_https___arxiv_org_abs_2602_01021
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Leaves of preferential attachment trees
Hartle, Harrison
Krapivsky, P. L.
Statistical Mechanics
Social and Information Networks
Physics and Society
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 $n_{k,\ell}$, which we derive from its associated multivariate generating function. From $n_{k,\ell}$ we obtain the leafdegree distribution, $m_{\ell}$, as well as the fraction of vertices that are protected (nonleaves with leafdegree zero) as a function of degree, $n_{k,0}$, among numerous other results. We also examine fluctuations and concentration of joint degree-leafdegree empirical counts $N_{k,\ell}$. 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 $n_{k,\ell}$ in two other models: the random recursive tree, and a redirection-based model.
title Leaves of preferential attachment trees
topic Statistical Mechanics
Social and Information Networks
Physics and Society
url https://arxiv.org/abs/2602.01021