Scaling limits of Markov-Branching trees and applications

TL;DR

This paper surveys recent advances in understanding the large-scale structure of random trees using Markov-Branching sequences, highlighting key applications and theoretical developments.

Contribution

It introduces a comprehensive framework for analyzing large random trees and explores new applications within this context.

Findings

Characterization of scaling limits of Markov-Branching trees

Applications to various models of random trees

Insights into the asymptotic behavior of large trees

Abstract

The goal of these lectures is to survey some of the recent progress on the description of large-scale structure of random trees. We use the framework of Markov-Branching sequences of trees and discuss several applications.