English

Scaling limit of the range of tree-valued branching random walks in random environmen

Probability 2026-05-05 v1

Abstract

We study a branching random walk (BRW) taking its values in a random tree \bT\bT (seen as a family tree) with an infinite line of ancestors that is a variant of a supercritical Galton--Watson (GW) tree with offspring distribution ν\nu. The transition probabilities of the BRW are those of a critical biased random walk on \bT\bT: namely, the probability to move from xx to one of its kxk_x children is 1/(mν+kx)1/(\mathtt{m}_\nu+k_x) and the probability to move from xx to the direct parent of xx is mν/(mν+kx)\mathtt{m}_\nu/(\mathtt{m}_\nu+k_x). Here \ttmν\ttm_\nu stands for the mean of ν\nu. The BRW is indexed by a critical GW tree conditioned to have nn {vertices} and whose offspring distribution is in the domain of attraction of an α\alpha-stable law with α\ino(1,2]\alpha \ino (1, 2]. We denote by \cRn\cR_n the range of the BRW, i.e., ~the set of all sites in \bT\bT visited by the BRW. Under a moment assumption for ν\nu, we prove that if we view \cRn\cR_n as a random subtree of \bT\bT equipped with its graph distance dgrd_{\mathtt{gr}} and with its occupation measure \ttmocc(n)\ttm^{_{(n)}}_{{\mathtt{occ}}} then there exists a scaling sequence sn ⁣ ⁣s_n \! \to \! \infty such that conditionally given the environment \bT\bT, the measured metric space (\cRn,sn1dgr,1n\ttmocc(n))(\cR_n, s_n^{-1}d_{\mathtt{gr}} , \frac{_1}{^n}\ttm^{_{(n)}}_{{\mathtt{occ}}} ) weakly converges in the Gromov--Hausdorff--Prokhorov sense to a random measured compact real tree introduced by Curien, Le Gall \& Miermont in \cite{CuLGMi13} called the Brownian cactus with α\alpha-stable branching mechanism. This work extends in random environment the result from D., K., Lin \& Torri \cite{DuKhLiTo22} which deals with the case where \bT\bT is a regular tree.

Keywords

Cite

@article{arxiv.2605.02430,
  title  = {Scaling limit of the range of tree-valued branching random walks in random environmen},
  author = {Thomas Duquesne and Robin Khanfir},
  journal= {arXiv preprint arXiv:2605.02430},
  year   = {2026}
}