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Fractional Brownian motion is a Gaussian stochastic process with long-range correlations in time; it has been shown to be a useful model of anomalous diffusion. Here, we investigate the effects of mutual interactions in an ensemble of…

Statistical Mechanics · Physics 2025-09-15 Jonathan House , Rashad Bakhshizada , Skirmantas Janušonis , Ralf Metzler , Thomas Vojta

This short note is motivated by a recently discovered connection between a drift-diffusion process in $n$-dimensional Euclidean space with a divergence-free drift sampled from a stationary and isotropic Gaussian ensemble of critical scaling…

Probability · Mathematics 2026-03-20 Sefika Kuzgun , Felix Otto , Christian Wagner

We consider a two-type reducible branching Brownian motion, defined as a particle system on the real line in which particles of two types move according to independent Brownian motion and create offspring at constant rate. Particles of type…

Probability · Mathematics 2021-04-08 Mohamed Ali Belloum , Bastien Mallein

The Mondrian process represents an elegant and powerful approach for space partition modelling. However, as it restricts the partitions to be axis-aligned, its modelling flexibility is limited. In this work, we propose a self-consistent…

Machine Learning · Statistics 2019-03-25 Xuhui Fan , Bin Li , Scott Anthony Sisson

We establish a new spatial Markov property of the Brownian half-plane. According to this property, if one removes a hull centered at a boundary point, the remaining space equipped with an intrinsic metric is still a Brownian half-plane,…

Probability · Mathematics 2025-08-26 Jean-François Le Gall , Armand Riera

We revisit the problem of Brownian diffusion with drift in order to study finite-size effects in the geometric Galton-Watson branching process. This is possible because of an exact mapping between one-dimensional random walks and geometric…

Statistical Mechanics · Physics 2018-07-04 Alvaro Corral , Rosalba Garcia-Millan , Nicholas R. Moloney , Francesc Font-Clos

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

It is known that after scaling a random Motzkin path converges to a Brownian excursion. We prove that the fluctuations of the counting processes of the ascent steps, the descent steps and the level steps converge jointly to linear…

Probability · Mathematics 2019-12-30 Włodzimierz Bryc , Yizao Wang

In this paper we study three self-similar, long-range dependence, Gaussian processes. The first one, with covariance \int_0^{s\wedge t} u^a [(t-u)^b+(s-u)^b]du, parameters a>-1, -1<b\leq 1, |b|\leq 1+a, corresponds to fractional Brownian…

Probability · Mathematics 2012-03-14 Tomasz Bojdecki , Luis G. Gorostiza , Anna Talarczyk

Fractional Brownian motion is a Gaussian stochastic process with stationary, long-time correlated increments and is frequently used to model anomalous diffusion processes. We study numerically fractional Brownian motion confined to a finite…

Statistical Mechanics · Physics 2019-03-22 T. Guggenberger , G. Pagnini , T. Vojta , R. Metzler

The Binary Space Partitioning~(BSP)-Tree process is proposed to produce flexible 2-D partition structures which are originally used as a Bayesian nonparametric prior for relational modelling. It can hardly be applied to other learning tasks…

Machine Learning · Statistics 2019-03-25 Xuhui Fan , Bin Li , Scott Anthony Sisson

The so-called Hadamard fractional Brownian motion, as defined in Beghin et al. (2025) by means of Hadamard fractional operators, is a Gaussian process which shares some properties with standard Brownian motion (such as the one-dimensional…

Probability · Mathematics 2025-07-21 Luisa Beghin , Alessandro De Gregorio , Yuliya Mishura

We study the asymptotic behaviour of the extremal process of a cascading family of branching Brownian motions. This is a particle system on the real line such that each particle has a type in addition to his position. Particles of type $1$…

Probability · Mathematics 2022-02-04 Mohamed Ali Belloum

Fractional Brownian motion can be represented as an integral of a deterministic kernel w.r.t. an ordinary Brownian motion either on infinite or compact interval. In previous literature fractional L\'evy processes are defined by integrating…

Probability · Mathematics 2011-11-11 Heikki Tikanmäki , Yuliya Mishura

Transport of spherical Brownian particles of finite size possessing radii through narrow channels with varying cross-section area is considered. Applying the so-called Fick-Jacobs approximation, i.e. assuming fast equilibration in…

Mesoscale and Nanoscale Physics · Physics 2015-05-19 Wolfgang Riefler , Gerhard Schmid , P Sekhar Burada , Peter Hanggi

We study a stochastic Laplacian growth model, where a set $\mathbf{U}\subseteq\mathbb{R}^{\mathrm{d}}$ grows according to a reflecting Brownian motion in $\mathbf{U}$ stopped at level sets of its boundary local time. We derive a scaling…

Probability · Mathematics 2024-11-11 Amir Dembo , Kevin Yang

In this paper, we study one dimensional Markov processes with spatial delay. Since the seminal work of Feller, we know that virtually any one dimensional, strong, homogeneous, continuous Markov process can be uniquely characterized via its…

Probability · Mathematics 2016-10-07 Michael Salins , Konstantinos Spiliopoulos

Recently, there has been much interest in activity-induced phase separations in concentrated suspensions of "active Brownian particles" (ABPs), self-propelled spherical particles whose direction of motion relaxes through thermal rotational…

Soft Condensed Matter · Physics 2014-02-13 Joakim Stenhammar , Davide Marenduzzo , Rosalind J. Allen , Michael E. Cates

We model the growth of a cell population by a piecewise deterministic Markov branching tree. Each cell splits into two offsprings at a division rate $B(x)$ that depends on its size $x$. The size of each cell grows exponentially in time, at…

Probability · Mathematics 2015-05-29 Marie Doumic , Marc Hoffmann , Nathalie Krell , Lydia Robert

We investigate piecewise-linear stochastic models as with regards to the probability distribution of functionals of the stochastic processes, a question which occurs frequently in large deviation theory. The functionals that we are looking…

Statistical Mechanics · Physics 2015-06-22 Yaming Chen , Wolfram Just
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