# A probabilistic approach to extreme statistics of Brownian escape times in dimensions 1, 2, and 3

## TL;DR

This paper develops a probabilistic framework to analyze the extreme statistics of first passage times for multiple Brownian searchers in 1D, 2D, and 3D, revealing how the fastest searcher reaches the target faster than the average single searcher.

## Contribution

It provides rigorous asymptotic analysis of the moments of the fastest FPT among many searchers in various dimensions, extending understanding of extreme first passage events.

## Key findings

- Fastest FPT can be orders of magnitude faster than average FPT.
- The fastest searcher takes an almost direct path to the target.
- Asymptotic behavior of all moments of fastest FPT is characterized.

## Abstract

First passage time (FPT) theory is often used to estimate timescales in cellular and molecular biology. While the overwhelming majority of studies have focused on the time it takes a given single Brownian searcher to reach a target, cellular processes are instead often triggered by the arrival of the first molecule out of many molecules. In these scenarios, the more relevant timescale is the FPT of the first Brownian searcher to reach a target from a large group of independent and identical Brownian searchers. Though the searchers are identically distributed, one searcher will reach the target before the others and will thus have the fastest FPT. This fastest FPT depends on extremely rare events and its mean can be orders of magnitude faster than the mean FPT of a given single searcher. In this paper, we use rigorous probabilistic methods to study this fastest FPT. We determine the asymptotic behavior of all the moments of this fastest FPT in the limit of many searchers in a general class of two- and three-dimensional domains. We establish these results by proving that the fastest searcher takes an almost direct path to the target.