THE CRITICAL BETA-SPLITTING RANDOM TREE I: HEIGHTS AND RELATED RESULTS

• 成果类型: Article
• 署名作者: Aldous, David; Pittel, Boris
• 署名单位: University of California System; University of California Berkeley; University System of Ohio; Ohio State University
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/24-AAP2112
• 发表日期: 2025
• 页码: 158-195
• 关键词: models

摘要

In the critical beta-splitting model of a random n-leaf binary tree, leaf- sets are recursively split into subsets, and a set of m leaves is split into subsets containing i and m - i leaves with probabilities proportional to 1/i(m - i). We study the continuous-time model in which the holding time before that split is exponential with rate hm-1, the harmonic number. We (sharply) evaluate the first two moments of the time-height Dn and of the edge-height Ln of a uniform random leaf (i.e., the length of the path from the root to the leaf), and prove the corresponding CLTs. We study the correlation between the heights of two random leaves of the same tree realization, and analyze the expected number of splits necessary for a set of t leaves to partially or completely break away from each other. We give tail bounds for the time-height and the edge-height of the tree, that is, the maximal leaf heights. We show that there is a limit distribution for the size of a uniform random subtree, and derive the asymptotics of the mean size. Our proofs are based on asymptotic analysis of the attendant (sum-type) recurrences. The essential idea is to replace such a recursive equality by a pair of recursive inequalities for which matching asymptotic solutions can be found, allowing one to bound, both ways, the elusive explicit solution of the recursive equality. This reliance on recursive inequalities necessitates usage of Laplace transforms rather than Fourier characteristic functions.