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We consider the stochastic ranking process with space-time dependent jump rates for the particles. The process is a simplified model of the time evolution of the rankings such as sales ranks at online bookstores. We prove that the joint…

Probability · Mathematics 2013-01-01 Tetsuya Hattori , Seiichiro Kusuoka

The dynamics of an infinite continuum system of randomly jumping and coalescing point particles is studied. The states of the system are probability measures on the corresponding configuration space $\Gamma$ the evolution of which is…

Dynamical Systems · Mathematics 2018-07-20 Yuri Kozitsky , Krzysztof Pilorz

We consider Vlasov-type scaling for Markov evolution of birth-and-death type in continuum, which is based on a proper scaling of corresponding Markov generators and has an algorithmic realization in terms of related hierarchical chains of…

Functional Analysis · Mathematics 2015-01-27 Dmitri Finkelshtein , Yuri Kondratiev , Oleksandr Kutoviy

In complex systems, the interplay between nonlinear and stochastic dynamics, e.g., J. Monod's necessity and chance, gives rise to an evolutionary process in Darwinian sense, in terms of discrete jumps among attractors, with punctuated…

Adaptation and Self-Organizing Systems · Physics 2013-03-18 Hong Qian

We deal with two following classes of equilibrium stochastic dynamics of infinite particle systems in continuum: hopping particles (also called Kawasaki dynamics), i.e., a dynamics where each particle randomly hops over the space, and…

Probability · Mathematics 2007-09-17 E. Lytvynov , P. T. Polara

We study a general class of interacting particle systems over a countable state space $V$ where on each site $x \in V$ the particle mass $\eta(x) \geq 0$ follows a stochastic differential equation. We construct the corresponding Markovian…

Probability · Mathematics 2023-08-16 Viktor Bezborodov , Luca Di Persio , Martin Friesen , Peter Kuchling

We introduce a model of long-range interacting particles evolving under a stochastic Monte Carlo dynamics, in which possible increase or decrease in the values of the dynamical variables is accepted with preassigned probabilities. For…

Statistical Mechanics · Physics 2013-12-03 Shamik Gupta , Thierry Dauxois , Stefano Ruffo

We study the existence of densities for distributions of piecewise deterministic Markov processes. We also obtain relationships between invariant densities of the continuous time process and that of the process observed at jump times. In…

Probability · Mathematics 2020-06-03 Piotr Gwiżdż , Marta Tyran-Kamińska

We study a class of interacting particle systems on $\mathbb{R}$ with two types. Particles evolve by independent jumps sampled from a fixed distribution, with type-dependent jump rates $v_+$, $v_-$ and stochastic type switching driven by…

Probability · Mathematics 2026-05-14 Sayan Banerjee , Andrew Nguyen

We study non oscillating bifurcations of non homogeneous steady states of the Vlasov equation, a situation occurring in galactic models, or for Bernstein-Greene-Kruskal modes in plasma physics. We show that resonances are strongly…

Statistical Mechanics · Physics 2016-04-20 J. Barré , D. Métivier , Y. Y. Yamaguchi

Bisimulation is a concept that captures behavioural equivalence. It has been studied extensively on nonprobabilistic systems and on discrete-time Markov processes and on so-called continuous-time Markov chains. In the latter time is…

Logic in Computer Science · Computer Science 2024-01-31 Linan Chen , Florence Clerc , Prakash Panangaden

In this paper, we introduce a new jump process modeling which involves a particular kind of non-Gaussian stochastic processes with random jumps at random time points. The main goal of this study is to provide an accurate tracking technique…

Applications · Statistics 2019-02-13 Seyyed Hamed Fouladi , Ehsan Hajiramezanali

We consider a particle moving in continuous time as a Markov jump process; its discrete chain is given by an ordinary random walk on ${\mathbb Z}^d$ , and its jump rate at $({\mathbf x},t)$ is given by a fixed function $\varphi$ of the…

Probability · Mathematics 2025-01-03 Luiz Renato Fontes , Pablo Almeida Gomes , Maicon Aparecido Pinheiro

Nonequilibrium response theory is a fundamental framework for understanding how physical systems respond to perturbations. Recently, a mutual linearity has been discovered for Markov jump processes using linear algebra analysis. This mutual…

Statistical Mechanics · Physics 2026-04-08 Jiming Zheng , Zhiyue Lu

We provide quantitative bounds for the long time behavior of a class of Piecewise Deterministic Markov Processes with state space Rd \times E where E is a finite set. The continuous component evolves according to a smooth vector field that…

Probability · Mathematics 2012-12-07 Michel Benaïm , Stéphane Le Borgne , Florent Malrieu , Pierre-André Zitt

In this paper we prove the convergence to the stochastic Burgers equation from one-dimensional interacting particle systems, whose dynamics allow the degeneracy of the jump rates. To this aim, we provide a new proof of the second order…

Probability · Mathematics 2017-08-30 Oriane Blondel , Patricia Gonçalves , Marielle Simon

We describe a general approach to the construction of a state evolution corresponding to the Markov generator of a spatial birth-and-death dynamics in $\mathbb{R}^d$. We present conditions on the birth-and-death intensities which are…

Functional Analysis · Mathematics 2015-01-27 Dmitri Finkelshtein , Yuri Kondratiev , Oleksandr Kutoviy

A simplified kinetic description of rapid granular media leads to a nonlocal Vlasov-type equation with a convolution integral operator that is of the same form as the continuity equations for aggregation-diffusion macroscopic dynamics.…

Numerical Analysis · Mathematics 2024-03-20 José A. Carrillo , Ruiwen Shu , Li Wang , Wuzhe Xu

This paper presents a nonparametric method for estimating the conditional density associated to the jump rate of a piecewise-deterministic Markov process. In our framework, the estimation needs only one observation of the process within a…

Statistics Theory · Mathematics 2012-07-12 Romain Azaïs , François Dufour , Anne Gégout-Petit

Many time series are effectively generated by a combination of deterministic continuous flows along with discrete jumps sparked by stochastic events. However, we usually do not have the equation of motion describing the flows, or how they…

Machine Learning · Computer Science 2020-01-09 Junteng Jia , Austin R. Benson