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A maximal coupling of two diffusion processes makes two diffusion particles meet as early as possible. We study the uniqueness of maximal couplings under a sort of "reflection structure" which ensures the existence of such couplings. In…

Probability · Mathematics 2007-05-23 Kazumasa Kuwada

Markovian maximal couplings of Markov processes are characterized by an equality of total variation and a distance of Wasserstein type. If a Markovian maximal coupling is a Feller process, the generator can be calculated, e.g. for…

Probability · Mathematics 2017-10-27 Björn Böttcher

We develop an approach to constructing non-Markovian, non-co-adapted couplings for sub-Riemannian Brownian motions in sub-Riemannian manifolds with large symmetry groups by treating the specific cases of the three-dimensional Heisenberg…

Probability · Mathematics 2025-04-03 Liangbing Luo , Robert W. Neel

The well-known reflection coupling gives a maximal coupling of two one-dimensional Brownian motions with different starting points. Nevertheless, the reflection coupling does not generalize to more than two Brownian motions. In this paper,…

Probability · Mathematics 2022-10-25 Cheuk Ting Li , Venkat Anantharam

This is a case study concerning the rate at which probabilistic coupling occurs for nilpotent diffusions. We focus on the simplest case of Kolmogorov diffusion (Brownian motion together with its time integral, or, slightly more generally,…

Probability · Mathematics 2016-02-11 Sayan Banerjee , Wilfrid S. Kendall

This paper answers a question of \'{E}mery [In S\'{e}minaire de Probabilit\'{e}s XLII (2009) 383-396 Springer] by constructing an explicit coupling of two copies of the Bene\v{s} et al. [In Applied Stochastic Analysis (1991) 121-156 Gordon…

Probability · Mathematics 2015-06-04 Wilfrid S. Kendall

We construct a non-Markovian coupling for hypoelliptic diffusions which are Brownian motions in the three-dimensional Heisenberg group. We then derive properties of this coupling such as estimates on the coupling rate, and upper and lower…

Probability · Mathematics 2017-11-28 Sayan Banerjee , Maria Gordina , Phanuel Mariano

In this paper we introduce three Markovian couplings of Brownian motions on smooth Riemannian manifolds without boundary which sit at the crossroad of two concepts. The first concept is the one of shy coupling put forward in…

Probability · Mathematics 2015-09-29 Mihai N. Pascu , Ionel Popescu

We raise a question on whether a dynamical system driven by Markov process is Markovian, for which we are able to propose a criterion and examples of positive case. This investigation leads us to develop (i) a general construction of…

Probability · Mathematics 2019-08-22 Motoya Machida

The notion of a successful coupling of Markov processes, based on the idea that both components of the coupled system ``intersect'' in finite time with probability one, is extended to cover situations when the coupling is unnecessarily…

Probability · Mathematics 2007-05-23 Michael Blank , Sergey Pirogov

We study optimal Markovian couplings of Markov processes, where the optimality is understood in terms of minimization of concave transport costs between the time-marginal distributions of the coupled processes. We provide explicit…

Probability · Mathematics 2022-10-21 Wilfrid S. Kendall , Mateusz B. Majka , Aleksandar Mijatović

This article presents a review of some old and new results on the long time behavior of reflected diffusions. First, we present a summary of prior results on construction, ergodicity and geometric ergodicity of reflected diffusions in the…

Probability · Mathematics 2022-08-08 Sayan Banerjee , Amarjit Budhiraja

We study Brownian flows on manifolds for which the associated Markov process is strongly mixing with respect to an invariant probability measure and for which the distance process for each pair of trajectories is a diffusion $r$. We provide…

Probability · Mathematics 2015-11-02 Michael Cranston , Benjamin Gess , Michael Scheutzow

Motivated by queues with many servers, we study Brownian steady-state approximations for continuous time Markov chains (CTMCs). Our approximations are based on diffusion models (rather than a diffusion limit) whose steady-state, we prove,…

Probability · Mathematics 2014-09-12 Itai Gurvich

Consider all the possible ways of coupling together two Brownian motions with the same starting position but with different drifts onto the same probability space. It is known that there exist couplings which make these processes agree for…

Probability · Mathematics 2025-07-03 Sebastian Hummel , Adam Quinn Jaffe

We consider different Markovian embedding schemes of non-Markovian stochastic processes that are described by generalized Langevin equations (GLE) and obey thermal detailed balance under equilibrium conditions. At thermal equilibrium…

Statistical Mechanics · Physics 2010-02-08 Peter Siegle , Igor Goychuk , Peter Talkner , Peter Hanggi

We develop a new simulation method for multidimensional diffusions with sticky boundaries. The challenge comes from simulating the sticky boundary behavior, for which standard methods like the Euler scheme fail. We approximate the sticky…

Probability · Mathematics 2021-07-12 Christian Meier , Lingfei Li , Gongqiu Zhang

For every bounded planar domain $D$ with a smooth boundary, we define a `Lyapunov exponent' $\Lambda(D)$ using a fairly explicit formula. We consider two reflected Brownian motions in $D$, driven by the same Brownian motion (i.e., a…

Probability · Mathematics 2007-05-23 Krzysztof Burdzy , Zhen-Qing Chen , Peter Jones

We present a novel approach of coupling two multidimensional and non-degenerate It\^o processes $(X_t)$ and $(Y_t)$ which follow dynamics with different drifts. Our coupling is sticky in the sense that there is a stochastic process $(r_t)$,…

Probability · Mathematics 2016-12-20 Andreas Eberle , Raphael Zimmer

Our object is to formulate and analyze a physically plausible and mathematically sound model to better understand the phenomenon of clumping in colloid dispersions. Our model is stochastic but rigorously derived from a deterministic setup…

Materials Science · Physics 2009-09-29 Peter. Kotelenez , Marshall J. Leitman , J. Adin Mann
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