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For each of the four particle processes given by Dieker and Warren [arXiv:0707.1843], we show the $n$-step transition kernels are given by the (dual) (weak) refined symmetric Grothendieck functions up to a simple overall factor. We do so by…

Combinatorics · Mathematics 2026-01-14 Shinsuke Iwao , Kohei Motegi , Travis Scrimshaw

We consider n-point sticky Brownian motions: a family of n diffusions that evolve as independent Brownian motions when they are apart, and interact locally so that the set of coincidence times has positive Lebesgue measure with positive…

Probability · Mathematics 2020-10-09 Guillaume Barraquand , Mark Rychnovsky

We consider the stochastic continuity equation driven by Brownian motion. We use the techniques of the Malliavin calculus to show that the law of the solution has a density with respect to the Lebesgue measure. We also prove that the…

Probability · Mathematics 2018-03-19 David A. C. Mollinedo , Christian Olivera , Ciprian A. Tudor

The monograph is devoted to the study of stochastic area functionals of Brownian motions and of the associated heat kernels on Lie groups and Riemannian manifolds. It is essentially self-contained and as such can serve as a textbook on the…

Probability · Mathematics 2023-08-24 Fabrice Baudoin , Nizar Demni , Jing Wang

We consider matrix-valued stochastic processes known as isotropic Brownian motions, and show that these can be solved exactly over complex fields. While these processes appear in a variety of questions in mathematical physics, our main…

Mathematical Physics · Physics 2017-08-23 J. R. Ipsen , H. Schomerus

Brownian motion is a building block in modern probability theory. In this paper, we describe a formalization of Brownian motion using the Lean theorem prover. We build on the existing measure-theoretic foundations in Lean's mathematical…

Probability · Mathematics 2025-12-03 Rémy Degenne , David Ledvinka , Etienne Marion , Peter Pfaffelhuber

We introduce a notion of generalized stochastic flows on mani- folds, that extends to the viscous case the one defined by Brenier for perfect fluids. Their kinetic energy extends the classical kinetic energy to Brownian flows, defined as…

Probability · Mathematics 2013-10-22 Alexandra Antoniouk , Marc Arnaudon , Ana Bela Cruzeiro

Langevin (stochastic differential) equations are routinely used to describe particle-laden flows. They predict Gaussian probability density functions (PDFs) of a particle's trajectory and velocity, even though experimentally observed…

Mathematical Physics · Physics 2024-03-11 Daniel Domínguez-Vázquez , Gustaaf B. Jacobs , Daniel M. Tartakovsky

We consider multiple chordal Schramm-Loewner evolution (SLE) with $\kappa\in (0,4]$. Under common-time parameterization, we show that the transition density of the driving function of multiple chordal SLEs can be given by the transition…

Probability · Mathematics 2025-09-03 Chongzhi Huang , Hao Wu , Lu Yang

This paper suggests a perfect-information game, along the lines of Levy's characterization of Brownian motion, that formalizes the process of Brownian motion in game-theoretic probability. This is perhaps the simplest situation where…

Probability · Mathematics 2008-01-09 Vladimir Vovk

In this paper, we introduce branching processes in a L\'evy random environment. In order to define this class of processes, we study a particular class of non-negative stochastic differential equations driven by Brownian motions and Poisson…

Probability · Mathematics 2016-07-13 S. Palau , J. C. Pardo

We introduce fractional Brownian motion processes (fBm) as an alternative model for the turbulent index of refraction. These processes allow to reconstruct most of the refractive index properties, but they are not differentiable. We…

Optics · Physics 2007-05-23 Dario G. Perez

In this paper, we develop a Young integration theory in dimension 2 which will allow us to solve a non-linear one dimensional wave equation driven by an arbitrary signal whose rectangular increments satisfy some H\"{o}lder regularity…

Probability · Mathematics 2007-05-23 Lluis Quer-Sardanyons , Samy Tindel

We prove a conjecture of Lalley and Sellke [Ann. Probab. 15 (1987)] asserting that the empirical (time-averaged) distribution function of the maximum of branching Brownian motion converges almost surely to a double exponential, or Gumbel,…

Probability · Mathematics 2012-01-10 Louis-Pierre Arguin , Anton Bovier , Nicola Kistler

Let $Mat_{\mathbb{C}}(K,N)$ be the space of $K\times N$ complex matrices. Let $\mathbf{B}_t$ be Brownian motion on $Mat_{\mathbb{C}}(K,N)$ starting from the zero matrix and $\mathbf{M}\in Mat_{\mathbb{C}}(K,N)$. We prove that, with $K\ge…

Probability · Mathematics 2022-05-31 Theodoros Assiotis

In this paper, we rely on the additive decomposition in law satisfied by a class of stochastic processes, combined with the well-known regulariy properties of fractional Brownian motion, to establish Besov-Orlicz regularity of their sample…

Probability · Mathematics 2026-05-11 Rachid Belfadli , Brahim Boufoussi , Youssef Ouknine

In this work we present a condition for the regularity, in both space and Malliavin sense, of strong solutions to SDEs driven by Brownian motion. We conjecture that this condition is optimal. As a consequence, we are able to improve the…

Probability · Mathematics 2015-09-11 David Banos , Torstein Nilssen

Dynamics of quantum systems which are perturbed by linear coupling to the reservoir stochastically can be studied in terms of quantum stochastic differential equations (for example, quantum stochastic Liouville equation and quantum Langevin…

Mathematical Physics · Physics 2007-05-23 A. E. Kobryn , T. Hayashi , T. Arimitsu

We consider a mixed stochastic differential equation driven by possibly dependent fractional Brownian motion and Brownian motion. Under mild regularity assumptions on the coefficients, it is proved that the equation has a unique solution.

Probability · Mathematics 2011-11-09 Yuliya Mishura , Georgiy Shevchenko

The aim of this paper is to present an elementary computable theory of probability, random variables and stochastic processes. The probability theory is baed on existing approaches using valuations and lower integrals. Various approaches to…

Probability · Mathematics 2015-10-14 Pieter Collins
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