# Optimal real-time detection of a drifting Brownian coordinate

## TL;DR

This paper presents the first exact solution to a Bayesian real-time detection problem for a drifting coordinate in a three-dimensional Brownian motion, optimizing detection speed and accuracy.

## Contribution

It provides a rigorous solution including non-monotone stopping boundaries for the first time in this context.

## Key findings

- Exact Bayesian detection strategy derived
- Optimal stopping boundaries characterized rigorously
- First solution of its kind in the literature

## Abstract

Consider the motion of a Brownian particle in three dimensions, whose two spatial coordinates are standard Brownian motions with zero drift, and the remaining (unknown) spatial coordinate is a standard Brownian motion with a non-zero drift. Given that the position of the Brownian particle is being observed in real time, the problem is to detect as soon as possible and with minimal probabilities of the wrong terminal decisions, which spatial coordinate has the non-zero drift. We solve this problem in the Bayesian formulation, under any prior probabilities of the non-zero drift being in any of the three spatial coordinates, when the passage of time is penalised linearly. Finding the exact solution to the problem in three dimensions, including a rigorous treatment of its non-monotone optimal stopping boundaries, is the main contribution of the present paper. To our knowledge this is the first time that such a problem has been solved in the literature.