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We start from the observation that, anytime two Markov generators share an eigenvalue, the function constructed from the product of the two eigenfunctions associated to this common eigenvalue is a duality function. We push further this…

Probability · Mathematics 2023-09-08 Frank Redig , Federico Sau

We provide a systematic study of the notion of duality of Markov processes with respect to a function. We discuss the relation of this notion with duality with respect to a measure as studied in Markov process theory and potential theory…

Probability · Mathematics 2014-02-18 Sabine Jansen , Noemi Kurt

This survey article gives an elementary introduction to the algebraic approach to Markov process duality, as opposed to the pathwise approach. In the algebraic approach, a Markov generator is written as the sum of products of simpler…

Probability · Mathematics 2018-02-21 Anja Sturm , Jan M. Swart , Florian Völlering

The theory of monotonicity and duality is developed for general one-dimensional Feller processes. Moreover it is shown that local monotonicity conditions (conditions on the L\'evy kernel) are sufficient to prove the well-posedness of the…

Probability · Mathematics 2022-05-03 Vassili Kolokoltsov

We study three classes of continuous time Markov processes (inclusion process, exclusion process, independent walkers) and a family of interacting diffusions (Brownian energy process). For each model we define a boundary driven process…

Mathematical Physics · Physics 2015-06-12 Gioia Carinci , Cristian Giardina' , Claudio Giberti , Frank Redig

In the context of Markov processes, we show a new scheme to derive dual processes and a duality function based on a boson representation. This scheme is applicable to a case in which a generator is expressed by boson creation and…

Statistical Mechanics · Physics 2015-05-14 Jun Ohkubo

For a series of Markov processes we prove stochastic duality relations with duality functions given by orthogonal polynomials. This means that expectations with respect to the original process (which evolves the variable of the orthogonal…

Probability · Mathematics 2017-02-01 Chiara Franceschini , Cristian Giardinà

We present a theorem which elucidates the connection between self-duality of Markov processes and representation theory of Lie algebras. In particular, we identify sufficient conditions such that the intertwining function between two…

Probability · Mathematics 2018-10-17 Chiara Franceschini , Cristian Giardinà , Wolter Groenevelt

We study self-duality for interacting particle systems, where the particles move as continuous time random walkers having either exclusion interaction or inclusion interaction. We show that orthogonal self-dualities arise from unitary…

Probability · Mathematics 2019-07-15 Gioia Carinci , Chiara Franceschini , Cristian Giardinà , Wolter Groenevelt , Frank Redig

This article develops a general framework for Laplace duality between positive Markov processes in which the one-dimensional Laplace transform of one process can be represented through that of another. We show that a process admits a…

Probability · Mathematics 2026-04-14 Clément Foucart , Matija Vidmar

We introduce a notion of $k$th order stochastic monotonicity and duality that allows one to unify the notion used in insurance mathematics (sometimes refereed to as Siegmund's duality) for the study of ruin probability and the duality…

Probability · Mathematics 2022-05-03 Vassili Kolokoltsov

Consider a system $X = ((x_\xi(t)), \xi \in \Omega_N)_{t \geq 0}$ of interacting Fleming-Viot diffusions with mutation and selection which is a strong Markov process with continuous paths and state space $(\CP(\I))^{\Omega_N}$, where $\I$…

Probability · Mathematics 2011-04-07 Donald A. Dawson , Andreas Greven

We study the permutation complexity of finite-state stationary stochastic processes based on a duality between values and orderings between values. First, we establish a duality between the set of all words of a fixed length and the set of…

Chaotic Dynamics · Physics 2011-12-13 Taichi Haruna , Kohei Nakajima

Markov Population Models are a widespread formalism used to model the dynamics of complex systems, with applications in Systems Biology and many other fields. The associated Markov stochastic process in continuous time is often analyzed by…

Machine Learning · Computer Science 2021-06-25 Francesca Cairoli , Ginevra Carbone , Luca Bortolussi

Many continuous reaction-diffusion models on $\mathbb{Z}$ (annihilating or coalescing random walks, exclusion processes, voter models) admit a rich set of Markov duality functions which determine the single time distribution. A common…

Probability · Mathematics 2025-06-26 Alexander Povolotsky , Pavel Pyatov , Roger Tribe , Bruce Westbury , Oleg Zaboronski

We find all factorized duality functions for a class of interacting particle systems. The functions we recover are self-duality functions for interacting particle systems such as zero-range processes, symmetric inclusion and exclusion…

Probability · Mathematics 2018-08-01 Frank Redig , Federico Sau

We develop the theory of strong stationary duality for diffusion processes on compact intervals. We analytically derive the generator and boundary behavior of the dual process and recover a central tenet of the classical Markov chain theory…

Probability · Mathematics 2015-04-20 James Allen Fill , Vince Lyzinski

We consider the fluctuations of a time-integrated particle current around an atypical value in a generic stochastic Markov process involving classical particles with two-site interaction and hardcore repulsion on a finite one-dimensional…

Statistical Mechanics · Physics 2016-01-20 Pegah Torkaman , Farhad H. Jafarpour

This paper develops a systematic treatment of monotonicity-based pathwise dualities for Markov processes taking values in partially ordered sets. We show that every Markov process that takes values in a finite partially ordered set and…

Probability · Mathematics 2016-10-26 Anja Sturm , Jan M. Swart

We prove that Sch\"{u}tz's ASEP Markov duality functional is also a Markov duality functional for the stochastic six vertex model. We introduce a new method that uses induction on the number of particles to prove the Markov duality.

Probability · Mathematics 2019-07-22 Yier Lin
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