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We derive the Markov-modulated generalized Ornstein-Uhlenbeck process by embedding a Markov-modulated random recurrence equation in continuous time. The obtained process turns out to be the unique solution of a certain stochastic…

Probability · Mathematics 2020-12-22 Anita Behme , Apostolos Sideris

Motivated by applications in telecommunications, computer scienceand physics, we consider a discrete-time Markov process withrestart. At each step the process eitherwith a positive probability restarts from a given distribution, orwith the…

Performance · Computer Science 2017-03-13 Konstantin Avrachenkov , Alexey Piunovskiy , Yi Zhang

Markov random fields are used to model high dimensional distributions in a number of applied areas. Much recent interest has been devoted to the reconstruction of the dependency structure from independent samples from the Markov random…

Computational Complexity · Computer Science 2010-03-09 Guy Bresler , Elchanan Mossel , Allan Sly

Recently, a new formalism describing the anomalous diffusion processes, based on the Onsager-Machlup fluctuation theory, has been suggested \cite{Smain, Spub}. We study particles performing this new type of motion, under the action of…

Statistical Mechanics · Physics 2025-08-26 A. S. Bodrova , S. I. Serdyukov

The state of many physical, biological and socio-technical systems evolves by combining smooth local transitions and abrupt resetting events to a set of reference values. The inclusion of the resetting mechanism not only provides the…

Statistical Mechanics · Physics 2022-12-21 Oriol Artime

In this paper we introduce a general stochastic representation for an important class of processes with resetting. It allows to describe any stochastic process intermittently terminated and restarted from a predefined random or non-random…

Probability · Mathematics 2023-10-11 Marcin Magdziarz , Kacper Taźbierski

In this paper we introduce and study renewal-reward processes in random environments where each renewal involves a reward taking values in a Banach space. We derive quenched large deviation principles and identify the associated rate…

Probability · Mathematics 2023-09-18 Frank den Hollander , Marco Zamparo

Consider an N-dimensional Markov chain obtained from N one-dimensional random walks by Doob h-transform with the q-Vandermonde determinant. We prove that as N becomes large, these Markov chains converge to an infinite-dimensional Feller…

Probability · Mathematics 2014-10-03 Alexei Borodin , Vadim Gorin

We develop an Onsager-Machlup-type theory for nonequilibrium semi-Markov processes. Our main result is an exact large time asymptotics for the joint probability of the occupation times and the currents in the system, establishing some…

Statistical Mechanics · Physics 2015-05-13 Christian Maes , Karel Netočný , Bram Wynants

The discrete stochastic dynamics of a random walker in the presence of resetting and memory is analyzed. Resetting and memory effects may compete for certain parameter regime and lead to significant changes in the long time dynamics of the…

Statistical Mechanics · Physics 2023-11-15 Upendra Harbola

We analyse dynamical large deviations of quantum trajectories in Markovian open quantum systems in their full generality. We derive a {\em quantum level-2.5 large deviation principle} for these systems, which describes the joint…

Statistical Mechanics · Physics 2019-04-10 Federico Carollo , Robert L. Jack , Juan P. Garrahan

Extensions of Kemeny's constant, as derived for irreducible finite Markov chains in discrete time, to Markov renewal processes and Markov chains in continuous time are discussed. Three alternative Kemeny's functions and their variants are…

Probability · Mathematics 2018-09-17 Jeffrey J Hunter

The theory of large deviations deals with the probabilities of rare events (or fluctuations) that are exponentially small as a function of some parameter, e.g., the number of random components of a system, the time over which a stochastic…

Statistical Mechanics · Physics 2012-03-01 Hugo Touchette

In Monte-Carlo methods the Markov processes used to sample a given target distribution usually satisfy detailed balance, i.e. they are time-reversible. However, relatively recent results have demonstrated that appropriate reversible and…

Probability · Mathematics 2016-06-29 Luc Rey-Bellet , Konstantinos Spiliopoulos

The probability distribution of the maximum $M_t$ of a single resetting Brownian motion (RBM) of duration $t$ and resetting rate $r$, properly centred and scaled, is known to converge to the standard Gumbel distribution of the classical…

Statistical Mechanics · Physics 2026-01-19 Alexander K. Hartmann , Satya N. Majumdar , Gregory Schehr

The theory of ``Markov-up'' processes is being developed. This is a new class of stochastic processes with ``partial'' markovian features; it could also be called ``one-sided Markov''. Such a behavior may be found in the real world and in…

Probability · Mathematics 2024-07-01 D. O. Kalikaeva

We study the tail behavior of Markov-modulated generalized Ornstein-Uhlenbeck processes -- that is, solutions to Langevin-type stochastic differential equations driven by a background continuous-time Markov chain. To this end, we consider a…

Probability · Mathematics 2026-01-15 Gerold Alsmeyer , Anita Behme

The need to model a Markov renewal on-off process with multiple off-states arise in many applications such as economics, physics, and engineering. Characterization of the occupation time of one specific off-state marginally or two…

Probability · Mathematics 2019-10-01 Chaoran Hu , Vladimir Pozdnyakov , Jun Yan

The effects of a stochastic reset, to its initial configuration, is studied in the exactly solvable one-dimensional coagulation-diffusion process. A finite resetting rate leads to a modified non-equilibrium stationary state. If in addition…

Statistical Mechanics · Physics 2014-02-04 Xavier Durang , Malte Henkel , Hyunggyu Park

We investigate the effects of markovian resseting events on continuous time random walks where the waiting times and the jump lengths are random variables distributed according to power law probability density functions. We prove the…

Statistical Mechanics · Physics 2021-02-10 Vicenç Méndez , Axel Masó-Puigdellosas , Trifce Sandev , Daniel Campos