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First passage under restart has recently emerged as a conceptual framework to study various stochastic processes under restart mechanism. Emanating from the canonical diffusion problem by Evans and Majumdar, restart has been shown to…

Statistical Mechanics · Physics 2021-06-01 Ofek Lauber Bonomo , Arnab Pal

In this article we review the problem of reaction annihilation $A+A \rightarrow \emptyset$ on a real lattice in one dimension, where $A$ particles move ballistically in one direction with a discrete set of possible velocities. We first…

Statistical Mechanics · Physics 2021-12-16 Soham Biswas , Francois Leyvraz

\noindent We address some direct and inverse problems, for the first-exit time (FET) $\tau $ of a drifted Brownian motion with Poissonian resetting ${\cal X}(t)$ from an interval $(0,b)$ and the first-exit area (FEA) $A,$ namely the area…

Probability · Mathematics 2025-02-28 Mario Abundo

We study the diffusive motion of a test particle in a two-dimensional comb structure consisting of a main backbone channel with continuously distributed side branches, in the presence of stochastic Markovian resetting to the initial…

Statistical Mechanics · Physics 2021-05-19 R. K. Singh , T. Sandev , A. Iomin , R. Metzler

We consider a random two-phase process which we call a reset-return one. The particle starts its motion at the origin. The first, displacement, phase corresponds to a stochastic motion of a particle and is finished at a resetting event. The…

Statistical Mechanics · Physics 2020-05-27 Anna S. Bodrova , Igor M. Sokolov

In this paper we consider a random search process with stochastic resetting and a partially accessible target $\calU$. That is, when the searcher finds the target by attaching to its surface $\partial \calU$ it does not have immediate…

Statistical Mechanics · Physics 2025-03-07 Paul C. Bressloff

We consider $N$ Brownian motions diffusing independently on a line, starting at $x_0>0$, in the presence of an absorbing target at the origin. The walkers undergo stochastic resetting under two protocols: (A) each walker resets…

Statistical Mechanics · Physics 2023-11-22 Marco Biroli , Satya N. Majumdar , Gregory Schehr

We consider a run-and-tumble particle (RTP) with stochastic resetting confined to the half line $[0,\infty)$ with a sticky boundary at $x=0$. In the bulk the RTP tumbles at a constant rate $\alpha>0$ between velocity states $\pm v$ with…

Statistical Mechanics · Physics 2026-02-03 Paul C Bressloff , Samantha Linn

We study the first-passage time to the origin of a mortal Brownian particle, with mortality rate $ \mu $, diffusing in one dimension. The particle starts its motion from $ x>0 $ and it is subject to stochastic resetting with constant rate $…

Statistical Mechanics · Physics 2023-03-01 Mattia Radice

Stochastic resetting models diverse phenomena across numerous scientific disciplines. Current understanding stems from the renewal framework, which relates systems subject to global resetting to their non-resetting counterparts. Yet, in…

Statistical Mechanics · Physics 2021-03-10 Asaf Miron , Shlomi Reuveni

Resetting a stochastic process is an important problem describing the evolution of physical, biological and other systems which are continually returned to their certain fixed point. We consider the motion of a subdiffusive particle with a…

Statistical Mechanics · Physics 2024-01-18 Aleksander A. Stanislavsky

We study the dynamics of an overdamped Brownian particle subjected to Poissonian stochastic resetting in a nonthermal bath, characterized by a Poisson white noise and a Gaussian noise. Applying the renewal theory we find an exact analytical…

Statistical Mechanics · Physics 2021-09-13 Koushik Goswami , Rajarshi Chakrabarti

Motion under stochastic resetting serves to model a myriad of processes in physics and beyond, but in most cases studied to date resetting to the origin was assumed to take zero time or a time decoupled from the spatial position at the…

Statistical Mechanics · Physics 2020-10-27 Arnab Pal , Łukasz Kuśmierz , Shlomi Reuveni

Stochastic restarting is a strategy of starting anew. Incorporation of the resetting to the random walks can result in the decrease of the mean first passage time, due to the ability to limit unfavorably meandering, sub-optimal…

Statistical Mechanics · Physics 2023-11-08 Karol Capała , Bartłomiej Dybiec

We investigate the long time behavior of a passive particle evolving in a one-dimensional diffusive random environment, with diffusion constant $D$. We consider two cases: (a) The particle is pulled forward by a small external constant…

Statistical Mechanics · Physics 2018-04-16 François Huveneers

We study an inverse first-hitting problem for a one-dimensional, time-homogeneous diffusion $X(t)$ reflected between two boundaries $a$ and $b,$ which starts from a random position $\eta.$ Let $a \le S \le b$ be a given threshold, such that…

Probability · Mathematics 2014-11-13 Mario Abundo

Particle discretizations of partial differential equations are advantageous for high-dimensional kinetic models in phase space due to their better scalability than continuum approaches with respect to dimension. Complex processes…

Plasma Physics · Physics 2025-12-23 Mark F. Adams , Daniel S. Finn , Matthew G. Knepley , Joseph V. Pusztay

This paper investigates the simultaneous identification of a spatially dependent potential and the initial condition in a subdiffusion model based on two terminal observations. The existence, uniqueness, and conditional stability of the…

Numerical Analysis · Mathematics 2025-10-28 Xu Wu , Jiang Yang , Zhi Zhou

In the classical context, it is well known that, sometimes, if the search does not find its target, it is better to start the process anew again, known as resetting. The quantum counterpart of resetting also indicates speeding up the…

Quantum Physics · Physics 2024-10-01 Pallabi Chatterjee , S. Aravinda , Ranjan Modak

Particle filters are a frequent choice for inference tasks in nonlinear and non-Gaussian state-space models. They can either be used for state inference by approximating the filtering distribution or for parameter inference by approximating…

Machine Learning · Computer Science 2026-02-27 Domonkos Csuzdi , Olivér Törő , Tamás Bécsi
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