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We investigate the nature of genetic drift acting at the leading edge of range expansions, building on recent results in [Hallatschek et al., Proc.\ Natl.\ Acad.\ Sci., \textbf{104}(50): 19926 - 19930 (2007)]. A well mixed population of two…

Populations and Evolution · Quantitative Biology 2010-08-16 Adnan Ali , Stefan Grosskinsky

We construct a two-dimensional diffusion process with rank-dependent local drift and dispersion coefficients, and with a full range of patterns of behavior upon collision that range from totally frictionless interaction, to elastic…

Probability · Mathematics 2012-08-24 E. Robert Fernholz , Tomoyuki Ichiba , Ioannis Karatzas

We introduce a four-parameter extended family of distributions related to the wrapped Cauchy distribution on the circle. The proposed family can be derived by altering the settings of a problem in Brownian motion which generates the wrapped…

Statistics Theory · Mathematics 2013-02-04 Shogo Kato , M. C. Jones

Einstein's explanation of Brownian motion provided one of the cornerstones which underlie the modern approaches to stochastic processes. His approach is based on a random walk picture and is valid for Markovian processes lacking long-term…

Statistical Mechanics · Physics 2009-11-10 I. M. Sokolov , J. Klafter

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

Simultaneous diffusive and inertial motion of Brownian particles in laminar Couette flow is investigated via Lagrangian and Eulerian descriptions to determine the effect of particle inertia on diffusive transport in the long-time. The…

Statistical Mechanics · Physics 2010-08-13 Yannis Drossinos , Michael W. Reeks

We construct a stochastic process, called the Liouville Brownian motion, which is the Brownian motion associated to the metric $e^{\gamma X(z)}\,dz^2$, $\gamma<\gamma_c=2$ and $X$ is a Gaussian Free Field. Such a process is conjectured to…

Probability · Mathematics 2016-09-05 Christophe Garban , Rémi Rhodes , Vincent Vargas

We study a diffusion approximation for a model of stochastic motion of a particle in one spatial dimension. The velocity of the particle is constant but the direction of the motion undergoes random changes with a Poisson clock. Moreover,…

Functional Analysis · Mathematics 2022-04-21 Adam Bobrowski , Tomasz Komorowski

We consider the problem of leakage or effusion of an ensemble of independent stochastic processes from a region where they are initially randomly distributed. The case of Brownian motion, initially confined to the left half line with…

Statistical Mechanics · Physics 2023-06-29 David S. Dean , Satya N. Majumdar , Gregory Schehr

Aiming to understand the distribution of fitness levels of individuals in a large population undergoing selection, we study the particle configurations of branching Brownian motion where each particle independently moves as Brownian motion…

Probability · Mathematics 2022-01-25 Jiaqi Liu , Jason Schweinsberg

We consider a branching particle system where each particle moves as an independent Brownian motion and breeds at a rate proportional to its distance from the origin raised to the power $p$, for $p\in[0,2)$. The asymptotic behaviour of the…

Probability · Mathematics 2014-02-24 Julien Berestycki , Éric Brunet , John W. Harris , Simon C. Harris , Matthew I. Roberts

Single-file diffusion behaves as normal diffusion at small time and as anomalous subdiffusion at large time. These properties can be described by fractional Brownian motion with variable Hurst exponent or multifractional Brownian motion. We…

Statistical Mechanics · Physics 2015-05-13 S. C. Lim , L. P. Teo

The "Brownian bees" model describes a system of $N$ independent branching Brownian particles. At each branching event the particle farthest from the origin is removed, so that the number of particles remains constant at all times.…

Statistical Mechanics · Physics 2021-03-30 Baruch Meerson , Pavel Sasorov

We introduce particle systems in one or more dimensions in which particles perform branching Brownian motion and the population size is kept constant equal to $N > 1$, through the following selection mechanism: at all times only the $N$…

Probability · Mathematics 2013-05-02 Nathanael Berestycki , Lee Zhuo Zhao

In this paper the solutions $u_{\nu}=u_{\nu}(x,t)$ to fractional diffusion equations of order $0<\nu \leq 2$ are analyzed and interpreted as densities of the composition of various types of stochastic processes. For the fractional equations…

Probability · Mathematics 2011-02-24 Enzo Orsingher , Luisa Beghin

Branching Brownian Motion describes a system of particles which diffuse in space and split into offsprings according to a certain random mechanism. In virtue of the groundbreaking work by M. Bramson on the convergence of solutions of the…

Probability · Mathematics 2011-06-28 Louis-Pierre Arguin , Anton Bovier , Nicola Kistler

Brownian motion is a ubiquitous physical phenomenon across the sciences. After its discovery by Brown and intensive study since the first half of the 20th century, many different aspects of Brownian motion and stochastic processes in…

Statistical Mechanics · Physics 2020-01-29 Ralf Metzler

We study the diffusion of Brownian particles on the surface of a sphere and compute the distribution of solid angles enclosed by the diffusing particles. This function describes the distribution of geometric phases in two state quantum…

Condensed Matter · Physics 2009-10-31 M. M. G. Krishna , Joseph Samuel , Supurna Sinha

We consider a stochastic flow in which individual particles follow skew Brownian motions, with each one of these processes driven by the same Brownian motion. One does not have uniqueness for the solutions of the corresponding stochastic…

Probability · Mathematics 2007-05-23 Krzysztof Burdzy , Haya Kaspi

For optimizing a non-convex function in finite dimension, a method is to add Brownian noise to a gradient descent, allowing for transitions between basins of attractions of different minimizers. To adapt this for optimization over a space…

Probability · Mathematics 2025-05-13 Pierre Germain , Pierre Monmarché