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Autori principali: Curien, Nicolas, Hu, Xingjian, Qian, Dongjian
Natura: Preprint
Pubblicazione: 2026
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Accesso online:https://arxiv.org/abs/2603.16408
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author Curien, Nicolas
Hu, Xingjian
Qian, Dongjian
author_facet Curien, Nicolas
Hu, Xingjian
Qian, Dongjian
contents Recently introduced and studied in arXiv:2407.07888, a self-similar Markov tree (ssMt) is a random decorated tree that vastly generalises the fragmentation tree. We study here the critical case that was left aside in arXiv:2407.07888. Borrowing techniques from branching random walk, in particular the recent result of Aïdékon--Hu--Shi arXiv:2409.01048, we can complete the picture by constructing critical ssMt, computing their fractal dimension and studying their associated harmonic and length measures using spinal decomposition.
format Preprint
id arxiv_https___arxiv_org_abs_2603_16408
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Critical Self-Similar Markov Trees
Curien, Nicolas
Hu, Xingjian
Qian, Dongjian
Probability
60J80, 60G18, 60G51
Recently introduced and studied in arXiv:2407.07888, a self-similar Markov tree (ssMt) is a random decorated tree that vastly generalises the fragmentation tree. We study here the critical case that was left aside in arXiv:2407.07888. Borrowing techniques from branching random walk, in particular the recent result of Aïdékon--Hu--Shi arXiv:2409.01048, we can complete the picture by constructing critical ssMt, computing their fractal dimension and studying their associated harmonic and length measures using spinal decomposition.
title Critical Self-Similar Markov Trees
topic Probability
60J80, 60G18, 60G51
url https://arxiv.org/abs/2603.16408