Sharp concentration for the largest and smallest fragment in a k-regular self-similar fragmentation

Piotr Dyszewski, Nina Gantert, Samuel Johnston, Joscha Prochno, Dominik Schmid

Research output: Contribution to journalArticlepeer-review

Abstract

We study the asymptotics of the k-regular self-similar fragmentation process. For α>0 and an integer k≥2, this is the Markov process (It)t≥0 in which each It is a union of open subsets of [0,1), and independently each subinterval of It of size u breaks into k equally sized pieces at rate uα. Let k−mt and k−Mt be the respective sizes of the largest and smallest fragments in It. By relating (It)t≥0 to a branching random walk, we find that there exist explicit deterministic functions g(t) and h(t) such that |mt−g(t)|≤1 and |Mt−h(t)|≤1 for all sufficiently large t. Furthermore, for each n, we study the final time at which fragments of size k−n exist. In particular, by relating our branching random walk to a certain point process, we show that, after suitable rescaling, the laws of these times converge to a Gumbel distribution as n→∞.
Original languageEnglish
Pages (from-to)1173-1203
Number of pages31
JournalThe Annals of Probability
Volume50
Issue number3
DOIs
Publication statusPublished - 31 May 2022

Bibliographical note

Funding Information:
Funding. SJ and JP are supported by the Austrian Science Fund (FWF) Project P32405 Asymptotic geometric analysis and applications of which JP is principal investigator. DS thanks the Studienstiftung des deutschen Volkes and the TopMath program for financial support. The research of PD was supported by the Alexander von Humboldt Foundation.

Keywords

  • Branching random walk
  • Fragmentation
  • Point process

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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