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Consider the partial sums {S_t} of a real-valued functional F(Phi(t)) of a Markov chain {Phi(t)} with values in a general state space. Assuming only that the Markov chain is geometrically ergodic and that the functional F is bounded, the…

Probability · Mathematics 2007-05-23 Ioannis Kontoyiannis , Sean Meyn

There has been much interest in generalizing Kesten's criterion for amenability in terms of a random walk to other contexts, such as determining amenability of a deck covering group by the bottom of the spectrum of the Laplacian or entropy…

Dynamical Systems · Mathematics 2021-10-06 Rhiannon Dougall

We prove existence of invariant measures for the Markovian semigroup generated by the solution to a parabolic semilinear stochastic PDE whose nonlinear drift term satisfies only a kind of symmetry condition on its behavior at infinity, but…

Analysis of PDEs · Mathematics 2020-04-21 Carlo Marinelli , Luca Scarpa

We study the asymptotics of the $k$-regular self-similar fragmentation process. For $\alpha > 0$ and an integer $k \geq 2$, this is the Markov process $(I_t)_{t \geq 0}$ in which each $I_t$ is a union of open subsets of $[0,1)$, and…

Probability · Mathematics 2021-02-18 Piotr Dyszewski , Nina Gantert , Samuel G. G. Johnston , Joscha Prochno , Dominik Schmid

A finite ergodic Markov chain exhibits cutoff if its distance to equilibrium remains close to its initial value over a certain number of iterations and then abruptly drops to near 0 on a much shorter time scale. Originally discovered in the…

Probability · Mathematics 2018-01-23 Charles Bordenave , Pietro Caputo , Justin Salez

Given a $k$-graph $\Lambda $ we construct a Markov space $M_\Lambda $, and a collection of $k$ pairwise commuting cellular automata on $M_\Lambda $, providing for a factorization of Markov's shift. Iterating these maps we obtain an action…

Operator Algebras · Mathematics 2018-09-14 R. Exel , B. Steinberg

For a controllable linear time-varying (LTV) pair $(\boldsymbol{A}_t,\boldsymbol{B}_t)$ and $\boldsymbol{Q}_{t}$ positive semidefinite, we derive the Markov kernel for the It\^{o} diffusion…

Optimization and Control · Mathematics 2025-04-23 Alexis M. H. Teter , Wenqing Wang , Sachin Shivakumar , Abhishek Halder

We study an inverse problem on a finite connected graph G = (X, E), on whose vertices a conductivity {\gamma} is defined. Our data consists in a sequence of partial observations of a fractional random walk on G. The observations are partial…

Analysis of PDEs · Mathematics 2026-04-13 Giovanni Covi , Matti Lassas

A Markov Additive Process is a bi-variate Markov process $(\xi,J)=\big((\xi_t,J_t),t\geq0\big)$ which should be thought of as a multi-type L\'evy process: the second component $J$ is a Markov chain on a finite space $\{1,\ldots,K\}$, and…

Probability · Mathematics 2018-10-04 Robin Stephenson

According to the theory of functional inequalities, a non-symmetric Markov semigroup has better properties than the corresponding symmetric one. For instance, there exist non-symmetric Markov semigroups which are hypercontractive (and thus…

Probability · Mathematics 2017-01-31 Feng-Yu Wang

We consider periodic Markov chains with absorption. Applying to iterates of this periodic Markov chain criteria for the exponential convergence of conditional distributions of aperiodic absorbed Markov chains, we obtain exponential…

Probability · Mathematics 2022-11-08 Nicolas Champagnat , Denis Villemonais

Consider $N$ particles performing random walks on the $\epsilon$-grid $(\epsilon Z)^d$, $\epsilon>0$ with branching and density-dependent selection: When one of the particles branches, a particle is removed from the most populated site. The…

Probability · Mathematics 2026-01-30 Rami Atar , Leonid Mytnik , Gershon Wolansky

We are interested in the connection between a metastable continuous state space Markov process (satisfying e.g. the Langevin or overdamped Langevin equation) and a jump Markov process in a discrete state space. More precisely, we use the…

Probability · Mathematics 2017-02-08 Giacomo Di Gesù , Tony Lelièvre , Dorian Le Peutrec , Boris Nectoux

We introduce a novel class of generative models based on piecewise deterministic Markov processes (PDMPs), a family of non-diffusive stochastic processes consisting of deterministic motion and random jumps at random times. Similarly to…

Machine Learning · Statistics 2024-11-06 Andrea Bertazzi , Dario Shariatian , Umut Simsekli , Eric Moulines , Alain Durmus

K. It\^{o} characterised in \cite{ito} zero-mean stationary Gauss Markov-processes evolving on a class of infinite-dimensional spaces. In this work we extend the work of It\^{o} in the case of Hilbert spaces: Gauss-Markov families that are…

Probability · Mathematics 2013-07-11 Ben Goldys , Szymon Peszat , Jerzy Zabczyk

In this article, we discuss ergodicity properties of a diffusion process given through an It\^{o} stochastic differential equation. We identify conditions on the drift and diffusion coefficients which result in sub-geometric ergodicity of…

Probability · Mathematics 2020-06-03 Petra Lazić , Nikola Sandrić

With view to applications, we here give an explicit correspondence between the following two: (i) the set of symmetric and positive measures $\rho$ on one hand, and (ii) a certain family of generalized Markov transition measures $P$, with…

Functional Analysis · Mathematics 2018-12-04 Sergey Bezuglyi , Palle E. T. Jorgensen

We describe random walk boundaries (in particular, the Poisson--Furstenberg, or PF-boundary) for a vast family of groups in terms of the hyperbolic boundary of a special free subgroup. We prove that almost all trajectories of the random…

Geometric Topology · Mathematics 2008-09-15 A. V. Malyutin , A. M. Vershik

We present recent results about the asymptotic behavior of ergodic products of isometries of a metric space X. If we assume that the displacement is integrable, then either there is a sublinear diffusion or there is, for almost every…

Dynamical Systems · Mathematics 2011-11-01 Anders Karlsson , François Ledrappier

In this work we introduce correlated random walks on $\Z$. When picking suitably at random the coefficient of correlation, and taking the average over a large number of walks, we obtain a discrete Gaussian process, whose scaling limit is…

Probability · Mathematics 2007-05-23 Enriquez Nathanael