Sublinearity of the number of semi-infinite branches for geometric random trees

TL;DR

This paper investigates the growth of semi-infinite branches in geometric random trees, showing that their expected number crossing large circles grows sublinearly, with results applicable to multiple models.

Contribution

It introduces a method to prove sublinear growth of semi-infinite branches in various geometric random tree models, including RPT, FPP, and LPP.

Findings

Expected number of semi-infinite branches is o(r)

For RPT, hi_r is o(r^{1-\u03b4}) almost surely

Method applies to multiple models, demonstrating robustness

Abstract

The present paper addresses the following question: for a geometric random tree in $\R^{2}$, how many semi-infinite branches cross the circle $\CC_{r}$ centered at the origin and with a large radius $r$? We develop a method ensuring that the expectation of the number $\chi_{r}$ of these semi-infinite branches is $o(r)$. The result follows from the fact that, far from the origin, the distribution of the tree is close to that of an appropriate directed forest which lacks bi-infinite paths. In order to illustrate its robustness, the method is applied to three different models: the Radial Poisson Tree (RPT), the Euclidean First-Passage Percolation (FPP) Tree and the Directed Last-Passage Percolation (LPP) Tree. Moreover, using a coalescence time estimate for the directed forest approximating the RPT, we show that for the RPT $\chi_{r}$ is $o(r^{1-\eta})$, for any $0<\eta<1/4$, almost surely and in expectation.