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We give a necessary and sufficient condition for a homogeneous Markov process taking values in $\R^n$ to enjoy the time-inversion property of degree $\alpha$. The condition sets the shape for the semigroup densities of the process and…

Probability · Mathematics 2007-05-23 Stephan Lawi

This paper introduces Discrete Markov Probabilistic Models (DMPMs), a novel discrete diffusion algorithm for discrete data generation. The algorithm operates in discrete bit space, where the noising process is a continuous-time Markov chain…

Machine Learning · Statistics 2025-10-09 Le-Tuyet-Nhi Pham , Dario Shariatian , Antonio Ocello , Giovanni Conforti , Alain Durmus

We study the Parallel Replica Dynamics in a general setting. We introduce a trajectory fragment framework that can be used to design and prove consistency of Parallel Replica algorithms for generic Markov processes. We use our framework to…

Numerical Analysis · Mathematics 2022-04-22 David Aristoff

Using elliptic regularity results in weighted spaces, stochastic calculus and the theory of non-symmetric Dirichlet forms, we first show weak existence of non-symmetric distorted Brownian motion for any starting point in some domain $E$ of…

Probability · Mathematics 2016-11-16 Michael Röckner , Jiyong Shin , Gerald Trutnau

This article presents a variant of Fleming-Viot particle systems, which are a standard way to approximate the law of a Markov process with killing as well as related quantities. Classical Fleming-Viot particle systems proceed by simulating…

Probability · Mathematics 2019-11-14 Frédéric Cérou , Arnaud Guyader , Mathias Rousset

In this paper we study an asymptotic expansion for the distribution of a random motion of a particle driven by a Markov process in diffusion approximation. We show that the singularly perturbed equation of a Markovian random motion can be…

Probability · Mathematics 2012-03-21 A. Pogorui

This paper investigates the position (state) distribution of the single step binomial (multi-nomial) process on a discrete state / time grid under the assumption that the velocity process rather than the state process is Markovian. In this…

Mathematical Finance · Quantitative Finance 2014-06-03 Johan GB Beumee , Chris Cormack , Peyman Khorsand , Manish Patel

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

We present a comprehensive discretization scheme for linear and nonlinear stochastic differential equations (SDEs) driven by either Brownian motions or $\alpha$-stable processes. Our approach utilizes compound Poisson particle…

Probability · Mathematics 2023-07-14 Xicheng Zhang

Consider the continuous-time Markov Branching Process. In critical case we consider a situation when the generating function of intensity of transformation of particles has the infinite second moment, but its tail regularly varies in sense…

Probability · Mathematics 2022-01-07 Azam Imomov

We consider the convergence of a continuous-time Markov chain approximation X^h, h>0, to an R^d-valued Levy process X. The state space of X^h is an equidistant lattice and its Q-matrix is chosen to approximate the generator of X. In…

Probability · Mathematics 2014-07-02 Aleksandar Mijatović , Matija Vidmar , Saul Jacka

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

In this paper we study a reflected Markov-modulated Brownian motion with a two sided reflection in which the drift, diffusion coefficient and the two boundaries are (jointly) modulated by a finite state space irreducible continuous time…

Probability · Mathematics 2011-04-27 Bernardo D'Auria , Offer Kella

Consider a continuous-state branching population constructed as a flow of nested subordinators. Inverting the subordinators and reversing time give rise to a flow of coalescing Markov processes (with negative jumps) which correspond to the…

Probability · Mathematics 2018-12-04 Clément Foucart , Chunhua Ma , Bastien Mallein

Through a regularization procedure, few approximation schemes of the local time of a large class of one dimensional processes are given. We mainly consider the local time of continuous semimartingales and reversible diffusions, and the…

Probability · Mathematics 2007-09-05 Blandine Berard Bergery , Pierre Vallois

This paper develops a novel operator theoretic framework to study the contraction properties of Markov semigroups with respect to a general class of Kantorovich semi-distances, which notably includes Wasserstein distances. The rather simple…

Probability · Mathematics 2026-03-04 Pierre Del Moral , Mathieu Gerber

Consider a non-symmetric generalized diffusion $X(\cdot)$ in ${\bbR}^d$ determined by the differential operator $A(\msx)=-\sum_{ij} \partial_ia_{ij}(\msx)\partial_j +\sum_i b_i(\msx)\partial_i$. In this paper the diffusion process is…

Probability · Mathematics 2010-03-16 Nedzad Limić

We are concerned with Mosco type convergence for a non-symmetric $n$-particle Fleming-Viot system $\{X_1,\ldots,X_n\}$ in a bounded $d$-dimensional domain $D$ with smooth boundary. Moreover, we are interested in relative compactness of the…

Probability · Mathematics 2014-09-29 Jörg-Uwe Löbus

Given a (conservative) symmetric Markov process on a metric space we consider related bilinear forms that generalize the energy form for a particle in an electromagnetic field. We obtain one bilinear form by semigroup approximation and…

Probability · Mathematics 2015-08-04 Michael Hinz

Quantum Krylov subspace diagonalization is a prominent candidate for early fault tolerant quantum simulation of many-body and molecular systems, but so far the focus has been mainly on computing ground-state energies. We go beyond this by…