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Stochastic differential equations (SDEs) using jump-diffusion processes describe many natural phenomena at the microscopic level. Since they are commonly used to model economic and financial evolutions, the calibration and optimal control…

Optimization and Control · Mathematics 2025-05-08 Jan Bartsch , Alfio Borzi , Gabriele Ciaramella , Jan Reichle

The use of stochastic models, in effect piecewise deterministic Markov processes (PDMP), has become increasingly popular especially for the modeling of chemical reactions and cell biophysics. Yet, exact simulation methods, for the…

Numerical Analysis · Mathematics 2015-04-28 Romain Veltz

In this paper we study a particular class of Piecewise deterministic Markov processes (PDMP's) which are semi-stochastic catastrophe versions of deterministic population growth models. In between successive jumps the process follows a flow…

Probability · Mathematics 2021-06-09 Branda Goncalves , Thierry Huillet , Eva Löcherbach

We consider the modeling of the dynamics of the chemostat at its very source. The chemostat is classically represented as a system of ordinary differential equations. Our goal is to establish a stochastic model that is valid at the scale…

Quantitative Methods · Quantitative Biology 2011-07-07 Fabien Campillo , Marc Joannides , Irène Larramendy

Let $\Gamma$ denote the space of all locally finite subsets (configurations) in $R^d$. A stochastic dynamics of binary jumps in continuum is a Markov process on $\Gamma$ in which pairs of particles simultaneously hop over $R^d$. In this…

The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain human behaviour in different contexts. Here we propose a generative model to capture the essential dynamics of survival analysis,…

Physics and Society · Physics 2015-06-18 Trevor Fenner , Mark Levene , George Loizou

This paper presents an algorithm to apply nonlinear control design approaches in the case of stochastic systems with partial state observation. Deterministic nonlinear control approaches are formulated under the assumption of full state…

Systems and Control · Electrical Eng. & Systems 2023-09-19 Mohammad S. Ramadan , Mohammad Alsuwaidan , Ahmed Atallah , Sylvia Herbert

We propose and study a system whose dynamics are governed by predictions of its future states. General formalism and concrete examples are presented. We find that the dynamical characteristics depend on both how to shape predictions as well…

Other Condensed Matter · Physics 2007-05-23 Toru Ohira

Dynamical processes can be classified in various ways as deterministic or stochastic, and continuous or discrete time. All these types can be studied by the path-spaces they generate, and stationary measures on that path-space. Such…

Dynamical Systems · Mathematics 2026-03-19 Suddhasattwa Das

We develop a rigorous theory of external influences on finite discrete dynamical systems, going beyond the perturbation paradigm, in that the external influence need not be a small contribution. Indeed, the covariance condition can be…

Mathematical Physics · Physics 2023-02-09 Carlo Maria Scandolo , Gilad Gour , Barry C. Sanders

In the classical stochastic resetting problem, a particle, moving according to some stochastic dynamics, undergoes random interruptions that bring it to a selected domain, and then, the process recommences. Hitherto, the resetting mechanism…

Statistical Mechanics · Physics 2020-12-08 Carlos A. Plata , Deepak Gupta , Sandro Azaele

This paper addresses the problem of steering an initial probability distribution to a target probability distribution through a deterministic or stochastic linear control system. Our proposed approach is inspired by the flow matching…

Optimization and Control · Mathematics 2025-01-15 Yuhang Mei , Mohammad Al-Jarrah , Amirhossein Taghvaei , Yongxin Chen

Markov jump processes are continuous-time stochastic processes with a wide range of applications in both natural and social sciences. Despite their widespread use, inference in these models is highly non-trivial and typically proceeds via…

Machine Learning · Computer Science 2023-06-01 Patrick Seifner , Ramses J. Sanchez

Modelling is an essential procedure in analyzing and controlling a given logical dynamic system (LDS). It has been proved that deterministic LDS can be modeled as a linear-like system using algebraic state space representation. However, due…

Optimization and Control · Mathematics 2022-03-04 Changxi Li , Jun-e Feng , Daizhan Cheng , Xiao Zhang

Data-driven control strategies for dynamical systems with unknown parameters are popular in theory and applications. An essential problem is to prevent stochastic linear systems becoming destabilized, due to the uncertainty of the…

Systems and Control · Computer Science 2019-05-20 Mohamad Kazem Shirani Faradonbeh , Ambuj Tewari , George Michailidis

We explicitly construct so-called captive jump processes. These are stochastic processes in continuous time, whose dynamics are confined by a time-inhomogeneous bounded domain. The drift and volatility of the captive processes depend on the…

Probability · Mathematics 2021-11-16 Andrea Macrina , Levent A. Mengütürk , Murat C. Mengütürk

This paper is concerned with the relationship between general maximum principle and dynamic programming principle for the stochastic recursive optimal control problem with jumps, where the control domain is not necessarily convex. Relations…

Optimization and Control · Mathematics 2024-06-04 Bin Wang , Jingtao Shi

We study a stochastic two-species chemical reaction system with two mechanisms. One mechanism consists of chemical interactions which govern the overall drift of species amounts in the system; the other mechanism consists of resampling,…

Probability · Mathematics 2014-05-06 John K. McSweeney , Lea Popovic

This work develops asymptotic properties of a class of switching jump diffusion processes. The processes under consideration may be viewed as a number of jump diffusion processes modulated by a random switching mechanism. The underlying…

Probability · Mathematics 2018-10-02 Xiaoshan Chen , Zhen-Qing Chen , Ky Tran , George Yin

We consider stochastic dynamical systems defined by differential equations with a uniform random time delay. The latter equations are shown to be equivalent to deterministic higher-order differential equations: for an $n$-th order equation…

Statistical Mechanics · Physics 2011-10-11 P. L. Krapivsky , J. M. Luck , K. Mallick