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Related papers: Vlasov scaling for stochastic dynamics of continuo…

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We show that, in the continuum limit, the dynamics of Hamiltonian systems defined on a lattice with long-range couplings is well described by the Vlasov equation. This equation can be linearized around the homogeneous state and a dispersion…

Chaotic Dynamics · Physics 2015-03-31 Romain Bachelard , F. Staniscia , Thierry Dauxois , Giovanni De Ninno , Stefano Ruffo

We construct the time evolution for states of Glauber dynamics for a spatial infinite particle system in terms of generating functionals. This is carried out by an Ovsjannikov-type result in a scale of Banach spaces, leading to a local (in…

Mathematical Physics · Physics 2012-07-23 Dmitri L. Finkelshtein , Yuri G. Kondratiev , Maria João Oliveira

In this paper we investigate the continuum limits of a class of Markov chains. The investigation of such limits is motivated by the desire to model very large networks. We show that under some conditions, a sequence of Markov chains…

Networking and Internet Architecture · Computer Science 2011-06-22 Yang Zhang , Edwin K. P. Chong , Jan Hannig , Donald Estep

A stochastic representation for the solutions of the Poisson-Vlasov equation, with several charged species, is obtained. The representation involves both an exponential and a branching process and it provides an intuitive characterization…

Plasma Physics · Physics 2010-08-31 Elena Floriani , R. Lima , R. Vilela Mendes

Biochemical reaction networks frequently consist of species evolving on multiple timescales. Stochastic simulations of such networks are often computationally challenging and therefore various methods have been developed to obtain sensible…

Molecular Networks · Quantitative Biology 2017-04-20 Jae Kyoung Kim , Grzegorz A. Rempala , Hye-Won Kang

An individual-based model of an infinite system of point particles in $\mathbb{R}^d$ is proposed and studied. In this model, each particle at random produces a finite number of new particles and disappears afterwards. The phase space for…

Dynamical Systems · Mathematics 2015-10-27 Agnieszka Tanaś

For Markov processes evolving on multiple time-scales a combination of large component scalings and averaging of rapid fluctuations can lead to useful limits for model approximation. A general approach to proving a law of large numbers to a…

Probability · Mathematics 2020-12-29 Lea Popovic

The nonlinear Vlasov equation contains the full nonlinear dynamics and collective effects of a given Hamiltonian system. The linearized approximation is not valid for a variety of interesting systems, nor is it simple to extend to higher…

Plasma Physics · Physics 2016-05-25 Stephen D. Webb

A continuum individual-based model of hopping and coalescing particles is introduced and studied. Its microscopic dynamics are described by a hierarchy of evolution equations obtained in the paper. Then the passage from the micro- to…

Dynamical Systems · Mathematics 2015-09-22 Krzysztof Pilorz

We develop a general theory dealing with stochastic models for dynamical systems that are governed by various nonlinear, ordinary or partial differential, equations. In particular, we address the problem how flows in the random medium…

chao-dyn · Physics 2009-10-31 Piotr Garbaczewski

We consider general convolutional derivatives and related fractional statistical dynamics of continuous interacting particle systems. We apply the subordination principle to construct kinetic fractional statistical dynamics in the continuum…

Mathematical Physics · Physics 2016-10-11 Anatoly N. Kochubei , Yuri Kondratiev

We show the variational convergence of an irreversible Markov jump process describing a finite stochastic particle system to the solution of a countable infinite system of deterministic time-inhomogeneous quadratic differential equations…

Analysis of PDEs · Mathematics 2025-07-08 Jasper Hoeksema , Chun Yin Lam , André Schlichting

We consider the Markov chain approximations for singular stable-like processes. First we obtain properties of some Markov chains. Then we construct the approximating Markov chains and give a necessary condition for weak convergence of these…

Probability · Mathematics 2012-10-11 Fangjun Xu

In this paper, we construct a type of interacting particle systems to approximate a class of stochastic different equations whose coefficients depend on the conditional probability distributions of the processes given partial observations.…

Probability · Mathematics 2024-03-27 Kai Du , Yunzhang Li , Yuyang Ye

With recent advances in structural biology, including experimental techniques and deep learning-enabled high-precision structure predictions, molecular dynamics methods that scale up to large biomolecular systems are required. Current…

Biological Physics · Physics 2022-06-24 Tim Hempel , Simon Olsson , Frank Noé

This project is going to work with one example of stochastic matrix to understand how Markov chains evolve and how to use them to make faster and better decisions only looking to the present state of the system.

Dynamical Systems · Mathematics 2020-12-24 Ricardo Frumento

We study approximations of evolving probability measures by an interacting particle system. The particle system dynamics is a combination of independent Markov chain moves and importance sampling/resampling steps. Under global regularity…

Probability · Mathematics 2011-12-12 Andreas Eberle , Carlo Marinelli

A stochastic representation for the solutions of the Poisson-Vlasov equation is obtained. The representation involves both an exponential and a branching process. The stochastic representation, besides providing an alternative existence…

Plasma Physics · Physics 2007-09-27 R. Vilela Mendes , Fernanda Cipriano

Stochastic phenomena occurring within charged particle beams can be handled using the Vlasov-Fokker-Planck generalization of the Vlasov equation. In particular, this non-deterministic approach can deal with effects due to Coulomb scattering…

Accelerator Physics · Physics 2023-03-29 Jürgen Struckmeier

Macroscopic dynamical descriptions of complex physical systems are crucial for understanding and controlling material behavior. With the growing availability of data and compute, machine learning has become a promising alternative to…

Computational Physics · Physics 2026-03-24 Mengyi Chen , Pengru Huang , Kostya S. Novoselov , Qianxiao Li