The maximum of branching Brownian motion in $\mathbb{R}^d$
Yujin H. Kim, Eyal Lubetzky, Ofer Zeitouni

TL;DR
This paper proves that in multi-dimensional branching Brownian motion, the distribution of the maximum particle distance from the origin converges to a shifted Gumbel distribution as time progresses.
Contribution
It establishes the limiting distribution of the maximum particle distance in multi-dimensional BBM, extending known results from one dimension to higher dimensions.
Findings
The maximum distance law converges to a shifted Gumbel distribution.
The convergence holds for dimensions d ≥ 2.
Provides a probabilistic description of extremal particles in multi-dimensional BBM.
Abstract
We show that in branching Brownian motion (BBM) in , , the law of , the maximum distance of a particle from the origin at time , converges as to the law of a randomly shifted Gumbel random variable.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and statistical mechanics · Probability and Risk Models · Stochastic processes and financial applications
