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A new weak bisimulation semantics is defined for Markov automata that, in addition to abstracting from internal actions, sums up the expected values of consecutive exponentially distributed delays possibly intertwined with internal actions.…

Logic in Computer Science · Computer Science 2015-09-30 Alessandro Aldini , Marco Bernardo

In this paper, the weak convergence of impulsive recurrent process with Markov switching in the scheme of Levy approximation is proved. For the relative compactness, a method proposed by R. Liptser for semimartingales is used with a…

Probability · Mathematics 2009-11-03 V. S. Koroliuk , N. Limnios , I. V. Samoilenko

We study a class of stochastic models of mass transport on discrete vertex set $V$. For these models, a one-parameter family of homogeneous product measures $\otimes_{i\in V} \nu_\theta$ is reversible. We prove that the set of mixtures of…

Probability · Mathematics 2024-06-04 Cristian Giardinà , Frank Redig , Berend van Tol

The aim of this paper is to study differential and spectral properties of the infinitesimal operator of two dimensional Markov processes with diffusion and discrete components. The infinitesimal operator is now a second-order differential…

Classical Analysis and ODEs · Mathematics 2011-07-20 Manuel D. de la Iglesia

This paper is devoted to the problem of sample path large deviations for the Markov processes on R_+^N having a constant but different transition mechanism on each boundary set {x:x_i=0 for i\notin\Lambda, x_i>0 for i\in\Lambda}. The global…

Probability · Mathematics 2007-05-23 Irina Ignatiouk-Robert

In this paper we study positive self-similar Markov processes obtained by (partially) resurrecting a strictly $\alpha$-stable process at its first exit time from $(0,\infty)$. We construct those processes by using the Lamperti transform. We…

Probability · Mathematics 2023-04-13 Panki Kim , Renming Song , Zoran Vondraček

Motivated by a recent paper of Budd, where a new family of positive self-similar Markov processes associated to stable processes appears, we introduce a new family of L\'evy processes, called the double hypergeometric class, whose…

Probability · Mathematics 2020-07-21 Andreas E. Kyprianou , Juan Carlos Pardo , Matija Vidmar

These lecture notes are devoted to the integrability of discrete systems and their relation to the theory of Yang-Baxter (YB) maps. Lax pairs play a significant role in the integrability of discrete systems. We introduce the notion of Lax…

Exactly Solvable and Integrable Systems · Physics 2019-01-10 Deniz Bilman , Sotiris Konstantinou-Rizos

We consider numerical approximations of overdamped Langevin stochastic differential equations by implicit methods. We show a weak backward error analysis result in the sense that the generator associated with the numerical solution…

Numerical Analysis · Mathematics 2013-10-10 Marie Kopec

Suppose that P_{\theta}(g) is a linear functional of a Dirichlet process with shape \theta H, where \theta >0 is the total mass and H is a fixed probability measure. This paper describes how one can use the well-known Bayesian prior to…

Statistics Theory · Mathematics 2007-06-13 Lancelot F. James

Starting from the overdamped Langevin dynamics in $\mathbb{R}^n$, $$ dX_t = -\nabla V(X_t) dt + \sqrt{2 \beta^{-1}} dW_t, $$ we consider a scalar Markov process $\xi_t$ which approximates the dynamics of the first component $X^1_t$. In the…

Probability · Mathematics 2016-05-10 Frederic Legoll , Tony Lelievre , Stefano Olla

We consider a Markov chain on non-negative integer arrays of a given shape (and satisfying certain constraints) which is closely related to fundamental $SL(r+1,\mathbb{R})$ Whittaker functions and the Toda lattice. In the index zero case…

Probability · Mathematics 2023-12-06 Neil O'Connell

We establish the equivalence of the analytic and probabilistic notions of subharmonicity in the framework of general symmetric Hunt processes on locally compact separable metric spaces, extending an earlier work of the first named author on…

Probability · Mathematics 2009-12-18 Zhen-Qing Chen , Kazuhiro Kuwae

Consider the set of functions $f_{\theta}(x)=|\theta -x|$ on $\mathbb{R}$. Define a Markov process that starts with a point $x_0 \in \mathbb{R}$ and continues with $x_{k+1}=f_{\theta_{k+1}}(x_{k})$ with each $\theta _{k+1}$ picked from a…

Probability · Mathematics 2025-06-30 Aaron Abrams , Henry Landau , Zeph Landau , James Pommersheim , Eric Zaslow

The large deviations at various levels that are explicit for Markov jump processes satisfying detailed-balance are revisited in terms of the supersymmetric quantum Hamiltonian $H$ that can be obtained from the Markov generator via a…

Statistical Mechanics · Physics 2024-07-15 Cecile Monthus

For a strictly stationary sequence of random variables we derive functional convergence of the joint partial sum and partial maxima process under joint regular variation with index $\alpha \in (0,2)$ and weak dependence conditions. The…

Probability · Mathematics 2019-10-08 Danijel Krizmanic

The maximum a posteriori (MAP) configuration of binary variable models with submodular graph-structured energy functions can be found efficiently and exactly by graph cuts. Max-product belief propagation (MP) has been shown to be suboptimal…

Machine Learning · Computer Science 2012-02-19 Daniel Tarlow , Inmar E. Givoni , Richard S. Zemel , Brendan J. Frey

Suppose that a real valued process X is given as a solution to a stochastic differential equation. Then, for any twice continuously differentiable function f, the backward Kolmogorov equation gives a condition for f(t,X) to be a local…

Probability · Mathematics 2008-08-18 George Lowther

A class of stochastic processes, called "weak Dirichlet processes", is introduced and its properties are investigated in detail. This class is much larger than the class of Dirichlet processes. It is closed under C^1$-transformations and…

Probability · Mathematics 2007-05-23 Francois Coquet , Adam Jakubowski , Jean Memin , Leszek Slominski

In this paper, we develop a new mathematical technique which allows us to express the joint distribution of a Markov process and its running maximum (or minimum) through the marginal distribution of the process itself. This technique is an…

Probability · Mathematics 2015-10-27 Erhan Bayraktar , Sergey Nadtochiy