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We investigate the first-passage properties and extreme-value statistics of an overdamped Brownian particle confined by an external linear potential $V(x)=\mu |x-x_0|$, where $\mu>0$ is the strength of the potential and $x_0>0$ is the…

Statistical Mechanics · Physics 2025-06-17 Feng Huang , Hanshuang Chen

Let $N(t)$ be the collection of particles alive at time $t$ in a branching Brownian motion in $\mathbb{R}^d$, and for $u\in N(t)$, let $\mathbf{X}_u(t)$ be the position of particle $u$ at time $t$. For $\theta\in \mathbb{R}^d$, we define…

Probability · Mathematics 2023-10-31 Haojie Hou , Yan-Xia Ren , Renming Song

Diffusion with stochastic resetting has recently emerged as a powerful modeling tool with a myriad of potential applications. Here, we study local time in this model, covering situations of free and biased diffusion with, and without, the…

Statistical Mechanics · Physics 2019-06-06 Arnab Pal , Rakesh Chatterjee , Shlomi Reuveni , Anupam Kundu

We calculate analytically the probability density $P(t_m)$ of the time $t_m$ at which a continuous-time Brownian motion (with and without drift) attains its maximum before passing through the origin for the first time. We also compute the…

Statistical Mechanics · Physics 2008-02-25 Julien Randon-Furling , Satya N. Majumdar

In this paper, we consider semi-Markov processes whose transition times and transition probabilities depend on a small parameter $\varepsilon$. Understanding the asymptotic behavior of such processes is needed in order to study the…

Probability · Mathematics 2024-11-08 Leonid Koralov , Ishfaaq Mohammed Imtiyas

Suppose that $(X_t)_{t \ge 0}$ is a one-dimensional Brownian motion with negative drift $-\mu$. It is possible to make sense of conditioning this process to be in the state $0$ at an independent exponential random time and if we kill the…

Probability · Mathematics 2019-08-28 Steven N. Evans , Alexandru Hening

Fractional Brownian motion, a Gaussian non-Markovian self-similar process with stationary long-correlated increments, has been identified to give rise to the anomalous diffusion behavior in a great variety of physical systems. The…

We construct a class of one-dimensional diffusion processes on the particles of branching Brownian motion that are symmetric with respect to the limits of random martingale measures. These measures are associated with the extended extremal…

Probability · Mathematics 2018-11-07 Sebastian Andres , Lisa Hartung

We consider a diffusion process with coefficients that are periodic outside of an "interface region" of finite thickness. The question investigated in this article is the limiting long time/large scale behavior of such a process under…

Probability · Mathematics 2011-04-20 Martin Hairer , Charles Manson

We consider one-dimensional branching Brownian motion in which particles are absorbed at the origin. We assume that when a particle branches, the offspring distribution is supercritical, but the particles are given a critical drift towards…

Probability · Mathematics 2021-07-23 Pascal Maillard , Jason Schweinsberg

We study time series concerning rare events. The occurrence of a rare event is depicted as a jump of constant intensity always occurring in the same direction, thereby generating an asymmetric diffusion process. We consider the case where…

Statistical Mechanics · Physics 2007-05-23 Paolo Grigolini , Luigi Palatella , Giacomo Raffaelli

By using the law of the excursions of Brownian motion with drift, we find the distribution of the $n-$th passage time of Brownian motion through a straight line $S(t)= a + bt.$ In the special case when $b = 0,$ we extend the result to a…

Probability · Mathematics 2017-03-03 Mario Abundo

Assuming that a reflected Ornstein-Uhlenbeck state process is observed at discrete time instants, we propose generalized moment estimators to estimate all drift and diffusion parameters via the celebrated ergodic theorem. With the sampling…

Statistics Theory · Mathematics 2020-09-14 Yaozhong Hu , Yuejuan Xi

We prove a limit theorem for an integral functional of a Markov process. The Markovian dynamics is characterized by a linear Boltzmann equation modeling a one-dimensional test particle of mass $\lambda^{-1}\gg 1$ in an external periodic…

Mathematical Physics · Physics 2013-07-22 Jeremy Clark

For a sample of Exponentially distributed durations we aim at point estimation and a confidence interval for its parameter. A duration is only observed if it has ended within a certain time interval, determined by a Uniform distribution.…

Methodology · Statistics 2021-10-19 Rafael Weißbach , Dominik Wied

The separating time for two probability measures on a filtered space is an extended stopping time which captures the phase transition between equivalence and singularity. More specifically, two probability measures are equivalent before…

Probability · Mathematics 2025-02-10 David Criens , Mikhail Urusov

The paper presents a generalization of the local limit theorem on the convergence of inhomogeneous Markov chains to the diffusion limit for the case where the corresponding process coefficients satisfy weak regularity conditions and…

Probability · Mathematics 2025-06-02 I. Bitter , V. Konakov

We describe a two-dimensional model for active particles whose self-propulsion speed is not fixed, but varies in time, and whose motion is subject to both translational and rotational diffusion. In the conventional treatment of active…

Soft Condensed Matter · Physics 2025-10-01 Tayeb Jamali

The molecular motion in heterogeneous media displays anomalous diffusion by the mean-squared displacement $\langle X^2(t) \rangle = 2 D t^\alpha$. Motivated by experiments reporting populations of the anomalous diffusion parameters $\alpha$…

Biological Physics · Physics 2025-10-09 Yann Lanoiselée , Gianni Pagnini , Agnieszka Wyłomańska

Motivated by recent studies of record statistics in relation to strongly correlated time series, we consider explicitly the drawdown time of a Levy process, which is defined as the time since it last achieved its running maximum when…

Probability · Mathematics 2020-02-27 Richard J. Martin , Michael J. Kearney