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In this paper we study the asymptotic behavior of linear processes having as innovations mean zero, square integrable functions of stationary reversible Markov chains. In doing so we shall preserve the generality of coefficients assuming…

Probability · Mathematics 2012-06-05 Magda Peligrad

Lattice birth-and-death Markov dynamics of particle systems with spins from the set of non-negative integers are constructed as unique solutions to certain stochastic equations. Pathwise uniqueness, strong existence, Markov property and…

Probability · Mathematics 2020-07-07 Viktor Bezborodov , Yuri Kondratiev , Oleksandr Kutoviy

We prove a functional limit theorem for Markov chains that, in each step, move up or down by a possibly state dependent constant with probability $1/2$, respectively. The theorem entails that the law of every one-dimensional regular…

Probability · Mathematics 2020-05-13 Stefan Ankirchner , Thomas Kruse , Mikhail Urusov

A discrete-time Markov chain can be transformed into a new Markov chain by looking at its states along iterations of an almost surely finite stopping time. By the optional stopping theorem, any bounded harmonic function with respect to the…

Probability · Mathematics 2022-05-04 Iddo Ben-Ari , Behrang Forghani

In this article integro-differential Volterra equations whose convolution kernel depends on the vector variable are considered and a connection of these equations with a class of semi-Markov processes is established. The variable order…

Probability · Mathematics 2018-07-19 Mladen Savov , Bruno Toaldo

Matrix Dirichlet processes, in reference to their reversible measure, appear in a natural way in many different models in probability. Applying the language of diffusion operators and the method of boundary equations, we describe Dirichlet…

Probability · Mathematics 2017-07-04 Songzi Li

Reversible Markov chains play a central role in stochastic modelling and in algorithms such as Markov chain Monte Carlo (MCMC). Motivated by the fundamental importance of reversibility in classical settings, this paper develops a…

Probability · Mathematics 2025-10-28 Damjan Škulj

We consider additive functionals of stationary Markov processes and show that under Kipnis-Varadhan type conditions they converge in rough path topology to a Stratonovich Brownian motion, with a correction to the Levy area that can be…

Probability · Mathematics 2019-12-23 Jean-Dominique Deuschel , Tal Orenshtein , Nicolas Perkowski

We characterize the law of the partition function of a Brownian directed polymer model in terms of a diffusion process associated with the quantum Toda lattice. The proof is via a multidimensional generalization of a theorem of Matsumoto…

Probability · Mathematics 2012-03-29 Neil O'Connell

In the present paper, we consider a class of Markov processes on the discrete circle which has been introduced by K\"onig, O'Connell and Roch. These processes describe movements of exchangeable interacting particles and are discrete…

Probability · Mathematics 2026-01-01 Anna Ben-Hamou , Pierre Tarrago

The focus of this article is on entropy and Markov processes. We study the properties of functionals which are invariant with respect to monotonic transformations and analyze two invariant "additivity" properties: (i) existence of a…

Data Analysis, Statistics and Probability · Physics 2013-11-12 A. N. Gorban , P. A. Gorban , G. Judge

We present a nonparametric prior over reversible Markov chains. We use completely random measures, specifically gamma processes, to construct a countably infinite graph with weighted edges. By enforcing symmetry to make the edges undirected…

Machine Learning · Statistics 2014-03-18 Konstantina Palla , David A. Knowles , Zoubin Ghahramani

In the L\'evy construction of Brownian motion, a Haar-derived basis of functions is used to form a finite-dimensional process $W^{N}$ and to define the Wiener process as the almost sure path-wise limit of $W^{N}$ when $N$ tends to infinity.…

Probability · Mathematics 2008-06-10 Thibaud Taillefumier

Discrete convex Sobolev inequalities and Beckner inequalities are derived for time-continuous Markov chains on finite state spaces. Beckner inequalities interpolate between the modified logarithmic Sobolev inequality and the Poincar\'e…

Probability · Mathematics 2016-08-19 Ansgar Jüngel , Wen Yue

A close connection of reverse plane partitions with an integrable dynamical system called the discrete two-dimensional (2D) Toda molecule is clarified. It is shown that a multiplicative partition function for reverse plane partition of…

Combinatorics · Mathematics 2017-01-25 Shuhei Kamioka

We consider several critical wetting models. In the discrete case, these probability laws are known to converge, after an appropriate rescaling, to the law of a reflecting Brownian motion, or of the modulus of a Brownian bridge, according…

Probability · Mathematics 2020-02-04 Jean-Dominique Deuschel , Henri Elad Altman , Tal Orenshtein

Recently, the complete left tail asymptotic for the density of the {\it martingale limit} of the classical Galton-Watson process has been derived. The derivation is based on the properties of a special function (whose inverse Fourier…

Probability · Mathematics 2025-06-24 Anton A Kutsenko

We propose some backward-forward martingale decompositions for functions of reversible Markov chains. These decompositions are used to prove the functional CLT for reversible Markov chains with asymptotically linear variance of partial…

Probability · Mathematics 2018-01-16 Martial Longla

We define the concept of an "open" Markov process, or more precisely, continuous-time Markov chain, which is one where probability can flow in or out of certain states called "inputs" and "outputs". One can build up a Markov process from…

Mathematical Physics · Physics 2017-08-22 John C. Baez , Brendan Fong , Blake S. Pollard

This work shows how exponential concentration inequalities for additive functionals of stochastic processes over a finite time interval can be derived from concentration inequalities for martingales. The approach is entirely probabilistic…

Probability · Mathematics 2020-07-14 Bob Pepin