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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.…

Probability · Mathematics 2018-12-19 Philip Ernst , Goran Peskir , Quan Zhou

Consider the motion of a Brownian particle in $n$ dimensions, whose coordinate processes are standard Brownian motions with zero drift initially, and then at some random/unobservable time, exactly $k$ of the coordinate processes get a…

Probability · Mathematics 2023-05-11 Philip A. Ernst , Hongwei Mei , Goran Peskir

In this paper we resolve an open problem proposed by Lai, Poor, Xin, and Georgiadis (2011, IEEE Transactions on Information Theory). Consider a sequence of Brownian Motions with unknown drift equal to one or zero, which we may be observed…

Probability · Mathematics 2013-06-26 Erhan Bayraktar , Ross Kravitz

We formulate and solve a variant of the quickest detection problem which features false negatives. A standard Brownian motion acquires a drift at an independent exponential random time which is not directly observable. Based on the…

Optimization and Control · Mathematics 2026-02-24 Tiziano De Angelis , Jhanvi Garg , Quan Zhou

We construct a Bayesian sequential test of two simple hypotheses about the value of the unobservable drift coefficient of a Brownian motion, with a possibility to change the initial decision at subsequent moments of time for some penalty.…

Probability · Mathematics 2020-07-28 Mikhail Zhitlukhin

In the classical quickest detection problem, one must detect as quickly as possible when a Brownian motion without drift "changes" into a Brownian motion with positive drift. The change occurs at an unknown "disorder" time with exponential…

Probability · Mathematics 2015-05-29 Robert C. Dalang , Albert N. Shiryaev

The problem of detecting a change in the drift of a Brownian motion is considered. The change point is assumed to have a modified exponential prior distribution with unknown parameters. A worst-case analysis with respect to these parameters…

Statistics Theory · Mathematics 2016-10-11 Taposh Banerjee , George V. Moustakides

We consider an optimal control problem, where a Brownian motion with drift is sequentially observed, and the sign of the drift coefficient changes at jump times of a symmetric two-state Markov process. The Markov process itself is not…

Probability · Mathematics 2019-08-06 Alexey Muravlev , Mikhail Urusov , Mikhail Zhitlukhin

We study interacting systems of linear Brownian motions whose drift vector at every time point is determined by the relative ranks of the coordinate processes at that time. Our main objective has been to study the long range behavior of the…

Probability · Mathematics 2008-01-22 Soumik Pal , Jim Pitman

We consider a fractional Brownian motion with unknown linear drift such that the drift coefficient has a prior normal distribution and construct a sequential test for the hypothesis that the drift is positive versus the alternative that it…

Statistics Theory · Mathematics 2026-01-14 Alexey Muravlev , Mikhail Zhitlukhin

Brownian motion has played important roles in many different fields of science since its origin was first explained by Albert Einstein in 1905. Einstein's theory of Brownian motion, however, is only applicable at long time scales. At short…

Statistical Mechanics · Physics 2013-09-03 Tongcang Li , Mark G. Raizen

We study the dynamical phase transitions (DPTs) appearing for a single Brownian particle without drift. We first explore how first-order DPTs in large deviations can be found even for a single Brownian particle without any force upon…

Statistical Mechanics · Physics 2024-07-22 Takahiro Kanazawa , Kyogo Kawaguchi , Kyosuke Adachi

We consider an $N$-particle system of noncolliding Brownian motion starting from $x_1 \leq x_2 \leq ... \leq x_N$ with drift coefficients $\nu_j, 1 \leq j \leq N$ satisfying $\nu_1 \leq \nu_2 \leq ... \leq \nu_N$. When all of the initial…

Probability · Mathematics 2012-07-10 Makoto Katori

We study a classical Bayesian statistics problem of sequentially testing the sign of the drift of an arithmetic Brownian motion with the $0$-$1$ loss function and a constant cost of observation per unit of time for general prior…

Probability · Mathematics 2015-09-03 Erik Ekström , Juozas Vaicenavicius

Given a Wiener process with unknown and unobservable drift, we try to estimate this drift as effectively but also as quickly as possible, in the presence of a quadratic penalty for the estimation error and of a fixed, positive cost per unit…

Statistics Theory · Mathematics 2019-05-24 Erik Ekström , Ioannis Karatzas , Juozas Vaicenavicius

Brownian motion is the perpetual irregular motion exhibited by small particles immersed in a fluid. Such random motion of the particles is produced by statistical fluctuations in the collisions they suffer with the molecules of the…

Physics Education · Physics 2007-05-23 Kasturi Basu , Kopinjol Baishya

We consider critical branching Brownian motion with absorption, in which there is initially a single particle at $x > 0$, particles move according to independent one-dimensional Brownian motions with the critical drift of $-\sqrt{2}$, and…

Probability · Mathematics 2013-10-01 Julien Berestycki , Nathanael Berestycki , Jason Schweinsberg

We have realized real-time steering of the directed transport in a Brownian motor based on cold atoms in optical lattices, and demonstrate drifts along pre-designed paths. The transport is induced by spatiotemporal asymmetries in the…

Atomic Physics · Physics 2011-02-04 H. Hagman , M. Zelan , C. M. Dion , A. Kastberg

The multiple disorder problem seeks to determine a sequence of stopping times which are as close as possible to the unknown times of disorders at which the observation process changes its probability characteristics. We derive closed form…

Applications · Statistics 2010-11-02 Pavel V. Gapeev

The notion of concept drift refers to the phenomenon that the data generating distribution changes over time; as a consequence machine learning models may become inaccurate and need adjustment. In this paper we consider the problem of…

Machine Learning · Computer Science 2022-05-16 Fabian Hinder , André Artelt , Valerie Vaquet , Barbara Hammer
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