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Motivated by entropic optimal transport, time reversal of Markov jump processes in $\mathbb{R}^n$ is investigated. Relying on an abstract integration by parts formula for the carr\'e du champ of a Markov process recently obtained by…

Probability · Mathematics 2022-09-05 Giovanni Conforti , Christian Léonard

We prove a robust super-hedging duality result for path-dependent options on assets with jumps, in a continuous time setting. It requires that the collection of martingale measures is rich enough and that the payoff function satisfies some…

Optimization and Control · Mathematics 2020-04-24 Bruno Bouchard , Xiaolu Tan

This paper gives a complete characterization of infinitely divisible semimartingales, i.e., semimartingales whose finite dimensional distributions are infinitely divisible. An explicit and essentially unique decomposition of such…

Probability · Mathematics 2014-05-02 Andreas Basse-O'Connor , Jan Rosinski

We study nonlinear time-inhomogeneous Markov processes in the sense of McKean's seminal work [32]. These are given as families of laws $\mathbb{P}_{s,\zeta}$, $s\geq 0$, on path space, where $\zeta$ runs through a set of admissible initial…

Probability · Mathematics 2024-10-21 Marco Rehmeier , Michael Röckner

We consider a broad class of dynamic programming (DP) problems that involve a partially linear structure and some positivity properties in their system equation and cost function. We address deterministic and stochastic problems, possibly…

Optimization and Control · Mathematics 2026-04-21 Yuchao Li , Dimitri Bertsekas

We refine stochastic calculus for symmetric Markov processes without using time reverse operators. Under some conditions on the jump functions of locally square integrable martingale additive functionals, we extend Nakao's divergence-like…

Probability · Mathematics 2012-11-09 Kazuhiro Kuwae

We consider a discrete time semi-Markov process where the characteristics defining the process depend on a small perturbation parameter. It is assumed that the state space consists of one finite communicating class of states and, in…

Probability · Mathematics 2016-03-21 Mikael Petersson

We propose a novel measure valued process which models the behaviour of chemical reaction networks in spatially heterogeneous systems. It models reaction dynamics between different molecular species and continuous movement of molecules in…

Probability · Mathematics 2022-01-12 Lea Popovic , Amandine Veber

We introduce a mesh-type approach for tackling discrete-time, finite-horizon Markov Decision Processes (MDPs) characterized by state and action spaces that are general, encompassing both finite and infinite (yet suitably regular) subsets of…

Optimization and Control · Mathematics 2024-07-02 Denis Belomestny , John Schoenmakers

In most sampling algorithms, including Hamiltonian Monte Carlo, transition rates between states correspond to the probability of making a transition in a single time step, and are constrained to be less than or equal to 1. We derive a…

Machine Learning · Statistics 2015-10-13 Andrew B. Berger , Mayur Mudigonda , Michael R. DeWeese , Jascha Sohl-Dickstein

This paper presents a numerical method to calculate the value function for a general discounted impulse control problem for piecewise deterministic Markov processes. Our approach is based on a quantization technique for the underlying…

Probability · Mathematics 2011-08-31 Benoîte de Saporta , François Dufour

In this short note we study homogenization of symmetric $d$-dimensional L\'evy processes. Homogenization of one-dimensional pure jump Markov processes has been investigated by Tanaka \emph{et al.} in 1992; their motivation was the work by…

Probability · Mathematics 2021-01-13 René L. Schilling , Toshihiro Uemura

In this article dedicated to the memory of Igor D. Chueshov, I first summarize in a few words the joint results that we obtained over a period of six years regarding the long-time behavior of solutions to a class of semilinear stochastic…

Analysis of PDEs · Mathematics 2017-03-06 Pierre-A Vuillermot

We consider random processes that are history-dependent, in the sense that the distribution of the next step of the process at any time depends upon the entire past history of the process. In general, therefore, the Markov property cannot…

Probability · Mathematics 2019-11-19 Peter Clifford , David Stirzaker

We are concerned with the absolute continuity of stationary distributions corresponding to some piecewise deterministic Markov process, being typically encountered in biological models. The process under investigation involves a…

Probability · Mathematics 2024-03-26 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

In this paper, we consider a type of time-changed Markov process, where the time-change is an inverse killed subordinator. This can be seen as an extension of Chen (Chen, Z., Time fractional equations and probabilistic representation, Chaos…

Probability · Mathematics 2019-12-09 Huiyan Zhao , Siyan xu

In order to give quantitative estimates for approximating the ergodic limit, we investigate probabilistic limit behaviors of time-averaging estimators of numerical discretizations for a class of time-homogeneous Markov processes, by…

Probability · Mathematics 2023-10-13 Chuchu Chen , Tonghe Dang , Jialin Hong , Guoting Song

An action having an acceleration term in addition to the usual velocity term is analyzed. The quantum mechanical system is directly defined for Euclidean time using the path integral. The Euclidean Hamiltonian is shown to yield the…

Quantum Physics · Physics 2015-06-12 Belal E. Baaquie

In this work, we consider an inhomogeneous (discrete time) Markov chain and are interested in its long time behavior. We provide sufficient conditions to ensure that some of its asymptotic properties can be related to the ones of a…

Probability · Mathematics 2017-11-09 Michel Benaïm , Florian Bouguet , Bertrand Cloez

The probabilistic symbol is the right-hand side derivative of the characteristic functions corresponding to the one-dimensional marginals of a stochastic process. This object, as long as the derivative exists, provides crucial information…

Probability · Mathematics 2023-08-31 Sebastian Rickelhoff , Alexander Schnurr
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