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This paper solves a Bayes sequential impulse control problem for a diffusion, whose drift has an unobservable parameter with a change point. The partially-observed problem is reformulated into one with full observations, via a change of…

Optimization and Control · Mathematics 2014-08-19 Lokman A. Abbas-Turki , Ioannis Karatzas , Qinghua Li

Phase transitions are divided into first-order phase transitions and continuous ones in current classification. While the latter shows striking phenomena of scaling and universality, the former is generically characterized by discontinuous…

Statistical Mechanics · Physics 2026-05-04 Jiapeng Yang , Fan Zhong

Dynamical phase transitions (DPTs) arise from qualitative changes in the long-time behavior of stochastic trajectories, often observed in systems with kinetic constraints or driven out of equilibrium. Here we demonstrate that first-order…

Statistical Mechanics · Physics 2024-07-29 Takahiro Kanazawa , Kyogo Kawaguchi , Kyosuke Adachi

In this paper, we study branching Brownian motion with absorption, in which particles undergo Brownian motions with drift and are killed upon reaching the origin. We prove that the extremal process of this branching Brownian motion with…

Probability · Mathematics 2023-10-10 Fan Yang , Yaping Zhu

We consider the inclusion process on the complete graph with vanishing diffusivity, which leads to condensation of particles in the thermodynamic limit. Describing particle configurations in terms of size-biased and appropriately scaled…

Probability · Mathematics 2024-06-10 Paul Chleboun , Simon Gabriel , Stefan Grosskinsky

We consider the Fleming-Viot particle system consisting of $N$ identical particles evolving in $\mathbb{R}_{>0}$ as Brownian motions with constant drift $-1$. Whenever a particle hits $0$, it jumps onto another particle in the interior. It…

Probability · Mathematics 2023-06-07 Oliver Tough

In this paper, a generalized Brownian motion model has been applied to describe the relative particle dispersion problem in more realistic turbulent flows. The fluctuating pressure forces acting on a fluid particle are taken to be a colored…

Fluid Dynamics · Physics 2015-08-07 Bhimsen Shivamoggi

A possible mechanism leading to anomalous diffusion is the presence of long-range correlations in time between the displacements of the particles. Fractional Brownian motion, a non-Markovian self-similar Gaussian process with stationary…

Statistical Mechanics · Physics 2019-04-03 Alexander H O Wada , Alex Warhover , Thomas Vojta

The circular Dyson Brownian motion model refers to the stochastic dynamics of the log-gas on a circle. It also specifies the eigenvalues of certain parameter-dependent ensembles of unitary random matrices. This model is considered with the…

Statistical Mechanics · Physics 2016-08-31 P. J. Forrester , T. Nagao

Inspired by the recent work of Bertini and Posta, who introduced the boundary driven Brownian gas on $[0,1]$, we study boundary driven systems of independent particles in a general setting, including particles jumping on finite graphs and…

Probability · Mathematics 2021-12-24 Gioia Carinci , Simone Floreani , Cristian Giardinà , Frank Redig

We consider a system of $N$ non-crossing Brownian particles in one dimension. We find the exact rate function that describes the long-time large deviation statistics of their occupation fraction in a finite interval in space. Remarkably, we…

Statistical Mechanics · Physics 2023-06-28 Soheli Mukherjee , Naftali R. Smith

We consider the dynamical evolution of a Brownian particle undergoing stochastic resetting, meaning that after random periods of time it is forced to return to the starting position. The intervals after which the random motion is stopped…

Statistical Mechanics · Physics 2022-07-19 Mattia Radice

We derive the first-passage-time statistics of a Brownian motion driven by an exponential time-dependent drift up to a threshold. This process corresponds to the signal integration in a simple neuronal model supplemented with an…

Statistical Mechanics · Physics 2012-04-30 Eugenio Urdapilleta

Motivated by its relevance for the study of perturbations of one-dimensional voter models, including stochastic Potts models at low temperature, we consider diffusively rescaled coalescing random walks with branching and killing. Our main…

Probability · Mathematics 2013-09-24 Charles M. Newman , K. Ravishankar , Emmanuel Schertzer

We study condensation in several particle systems related to the inclusion process. For an asymmetric one-dimensional version with closed boundary conditions and drift to the right, we show that all but a finite number of particles condense…

Statistical Mechanics · Physics 2012-01-09 Stefan Grosskinsky , Frank Redig , Kiamars Vafayi

Local perturbations in conservative particle systems can have a non-local influence on the stationary measure. To capture this phenomenon, we analyze in this paper two toy models. We study the symmetric exclusion process on a countable set…

Probability · Mathematics 2024-10-25 Frank Redig , Ellen Saada

* ACTIVATED RANDOM WALK MODEL * This is a conservative particle system on the lattice, with a Markovian continuous-time evolution. Active particles perform random walks without interaction, and they may as well change their state to…

Probability · Mathematics 2011-03-15 Leonardo T. Rolla

Statistical properties of Brownian motion that arise by analyzing, separately, trajectories over which the system energy increases (upside) or decreases (downside) with respect to a threshold energy level, are derived. This selective…

Statistical Mechanics · Physics 2019-08-02 Galen T. Craven , Abraham Nitzan

We study the dynamics of a Brownian motion with a diffusion coefficient which evolves stochastically. We first study this process in arbitrary dimensions and find the scaling form and the corresponding scaling function of the position…

Statistical Mechanics · Physics 2023-01-30 Ion Santra , Urna Basu , Sanjib Sabhapandit

We study interacting Brownian particles on the half-line whose interaction occurs through boundary local times at the origin. The particle system is given by \[ X_i^n(t)=X^n_{0,i}+W_i^n(t)+L_i^n(t) +\frac{1}{n-1}\sum_{j\ne…

Probability · Mathematics 2026-05-05 Rami Atar
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